From b3c3e66c12cb76ddf49ae103f84610b13c3b4724 Mon Sep 17 00:00:00 2001 From: Sander-Timmerman Date: Mon, 24 Mar 2025 07:50:30 +0100 Subject: [PATCH 1/6] remove voltage step without angles Signed-off-by: Sander-Timmerman --- .../State Estimation Assignment.ipynb | 83 ++----------------- 1 file changed, 5 insertions(+), 78 deletions(-) diff --git a/state-estimation-assignment/State Estimation Assignment.ipynb b/state-estimation-assignment/State Estimation Assignment.ipynb index 950e6dd..ddcec9d 100644 --- a/state-estimation-assignment/State Estimation Assignment.ipynb +++ b/state-estimation-assignment/State Estimation Assignment.ipynb @@ -1,7 +1,6 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "a727ce38", "metadata": {}, @@ -28,7 +27,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "9cd12445", "metadata": {}, @@ -70,7 +68,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "50065790", "metadata": {}, @@ -145,7 +142,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "0c2bad59", "metadata": {}, @@ -167,7 +163,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "0234cab7", "metadata": {}, @@ -194,7 +189,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "940d48be", "metadata": {}, @@ -218,7 +212,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "2b013fa7", "metadata": {}, @@ -270,7 +263,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "f4736cc1", "metadata": {}, @@ -286,7 +278,7 @@ "- print the difference in `q_from` between `se_output_data` and `pf_output_data`\n", "- print the difference in `q_to` between `se_output_data` and `pf_output_data`\n", "\n", - "You should see that while the voltages match quite precisely (in the order of microvolts), the *p* and *q* are way off (in the order of megawatts / mega VARs). This is as expected because we used voltage angles of 0.0." + "You should see that both the voltages and the *p* and *q* match quite precisely." ] }, { @@ -311,71 +303,11 @@ ] }, { - "attachments": {}, - "cell_type": "markdown", - "id": "683bb610", - "metadata": {}, - "source": [ - "# Assignment 5: Add voltage angle measurements\n", - "\n", - "Now we will update the model by adding voltage angles to the voltage sensors.\n", - "We could alter the `input_data` and construct a new Model, but for the purpose of this workshop (and efficiency) we'll supply the voltage angles as `update_data`, which could potentially be a *batch* calculation in other usecases.\n", - "\n", - "- initialize an update voltage sensor array\n", - "- create an update dataset\n", - "- perform a state estimation, using the update dataset\n", - "- compare the results (as in assignment 4)\n", - "\n", - "You should see that the voltages match quite precisely (in the order of microvolts), the *p* and *q* do too (in the order of 0.01 watts / VARs), because we used the exact voltage angles from the power flow calculation." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8628b888", - "metadata": {}, - "outputs": [], - "source": [ - "# TODO: Initialize a voltage sensor update array for 3 sensors\n", - "update_sym_voltage_sensor = initialize_array(..., ..., ...)\n", - "update_sym_voltage_sensor[\"id\"] = ...\n", - "update_sym_voltage_sensor[\"u_angle_measured\"] = ...\n", - "\n", - "# TODO: Create an update dataset \n", - "update_data = {\n", - " ...\n", - "}\n", - "\n", - "# TODO: Validate the update data\n", - "assert_valid_batch_data(..., ..., calculation_type=..., symmetric=...)\n", - "\n", - "# Run the (iterative linear) state estimation\n", - "se_output_data_u_angle = model.calculate_state_estimation(\n", - " update_data = update_data,\n", - " symmetric=True,\n", - " error_tolerance=1e-8, \n", - " max_iterations=20, \n", - " calculation_method=CalculationMethod.iterative_linear)\n", - "\n", - "# TODO: Print the delta u for all nodes (se_output_data_u_angle - pf_output_data)\n", - "print(\"-------------- nodes --------------\")\n", - "print(\"delta_u:\", ...)\n", - "\n", - "# TODO: Print the delta p and q for all lines (se_output_data_u_angle - pf_output_data)\n", - "print(\"-------------- lines --------------\")\n", - "print(\"delta_p_from:\", ...)\n", - "print(\"delta_p_to:\", ...)\n", - "print(\"delta_q_from:\", ...)\n", - "print(\"delta_q_to:\", ...)" - ] - }, - { - "attachments": {}, "cell_type": "markdown", "id": "7b054f55", "metadata": {}, "source": [ - "# Assignment 6: Add power sensors to the model\n", + "# Assignment 5: Add power sensors to the model\n", "\n", "In common power grids most voltage sensors only measure the voltage magnitude; not the angle. In this assigment we will again use the `input_data` of assignment 3 (with unknown voltage angles) and we will connect power sensors to the model.\n", "\n", @@ -386,7 +318,7 @@ "- Create a new input data set, including both voltage and power sensors\n", "- Use the print statements of assignment 4 to compare the results\n", "\n", - "You should see that the voltages match quite precisely (in the order of microvolts), the *p* and *q* do too (in the order of watts / VARs)." + "You should see that again the voltages match quite precisely (in the order of microvolts), the *p* and *q* do too (in the order of watts / VARs)." ] }, { @@ -450,7 +382,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "1afd00f1", "metadata": {}, @@ -490,12 +421,11 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "4e48d946", "metadata": {}, "source": [ - "# Assignment 7: Time Series Batch Calculation\n", + "# Assignment 6: Time Series Batch Calculation\n", "\n", "Sometimes, it is desirable to see what the state of the power grid was for a number of measurements at different points in time. A typical use case is to see if the voltage or power requirements were not met over the past day.\n", "\n", @@ -522,7 +452,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "4720b175", "metadata": {}, @@ -580,7 +509,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "fb3bf501", "metadata": {}, @@ -611,7 +539,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "27e42d99", "metadata": {}, @@ -660,7 +587,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.5" } }, "nbformat": 4, From a4f7d323e42b8b4b815bc90224eee5df6889fbf2 Mon Sep 17 00:00:00 2001 From: Sander-Timmerman Date: Mon, 24 Mar 2025 08:24:52 +0100 Subject: [PATCH 2/6] voltage angles are now known Signed-off-by: Sander-Timmerman --- state-estimation-assignment/State Estimation Assignment.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/state-estimation-assignment/State Estimation Assignment.ipynb b/state-estimation-assignment/State Estimation Assignment.ipynb index ddcec9d..5b597ef 100644 --- a/state-estimation-assignment/State Estimation Assignment.ipynb +++ b/state-estimation-assignment/State Estimation Assignment.ipynb @@ -309,7 +309,7 @@ "source": [ "# Assignment 5: Add power sensors to the model\n", "\n", - "In common power grids most voltage sensors only measure the voltage magnitude; not the angle. In this assigment we will again use the `input_data` of assignment 3 (with unknown voltage angles) and we will connect power sensors to the model.\n", + "In common power grids most voltage sensors only measure the voltage magnitude; not the angle. In this assigment we will again use the `input_data` of assignment 3 and we will connect power sensors to the model.\n", "\n", "In our network it would be possible to connect power sensors to the lines, the loads and the source. To assign realistic measurement values to the power sensors we can use the powerflow output.\n", "\n", From fd413deb7465ad570ed6549215c5bdaae960937c Mon Sep 17 00:00:00 2001 From: Sander-Timmerman Date: Fri, 28 Mar 2025 13:48:16 +0100 Subject: [PATCH 3/6] make some new changes, put separate voltage angle step back with a clear not observable error before Signed-off-by: Sander-Timmerman --- ...Estimation Assignment with Solutions.ipynb | 320 ++++++++---------- .../State Estimation Assignment.ipynb | 57 +++- 2 files changed, 195 insertions(+), 182 deletions(-) diff --git a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb index a86957b..bc51fa4 100644 --- a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb +++ b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb @@ -1,7 +1,6 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "a727ce38", "metadata": {}, @@ -28,7 +27,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "9cd12445", "metadata": {}, @@ -40,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 11, "id": "2bc7de1e", "metadata": {}, "outputs": [], @@ -70,7 +68,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "50065790", "metadata": {}, @@ -82,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 12, "id": "760a38b1", "metadata": {}, "outputs": [], @@ -145,7 +142,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "0c2bad59", "metadata": {}, @@ -155,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 13, "id": "02130221", "metadata": {}, "outputs": [ @@ -491,7 +487,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "0234cab7", "metadata": {}, @@ -507,7 +502,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 14, "id": "2baee3cd", "metadata": {}, "outputs": [], @@ -518,7 +513,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "940d48be", "metadata": {}, @@ -532,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 15, "id": "71b39571", "metadata": {}, "outputs": [ @@ -618,19 +612,13 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "2b013fa7", "metadata": {}, "source": [ "# Assignment 3: Initialize the sensors\n", "\n", - "In this assignment we will perform a state estimation based on three voltage sensors that only measure the voltage. \n", - "If you look closely to the data, you'll notice that the number of measurements (3) is not larger than or equal to the number of unknowns (6). \n", - "So the system is not *fully observable* and you might expect the state estimation to fail. \n", - "However, the linear state estimation algorithm will assume the voltage angles (3) to be zero if no value is given. \n", - "In other words, the mathematical core will give us a faulty result, without any warning! \n", - "To prevent this, we need an observability check, which is complex, but will be added to the validation functions in the future.\n", + "In this assignment we will try to perform a state estimation based on three voltage sensors that only measure the voltage. However, because the number of measurements (3) is lower than the number of unknowns (6), the system is not *fully observable*. This should result in an error.\n", "\n", "- initialize the voltage sensors\n", "- extend the input data set, with the voltage sensors\n", @@ -640,10 +628,27 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 22, "id": "88034903", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "NotObservableError", + "evalue": "Not enough measurements available for state estimation.\n\nTry validate_input_data() or validate_batch_data() to validate your data.\n", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNotObservableError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[22], line 18\u001b[0m\n\u001b[0;32m 15\u001b[0m model \u001b[38;5;241m=\u001b[39m PowerGridModel(input_data)\n\u001b[0;32m 17\u001b[0m \u001b[38;5;66;03m# Run the (iterative linear) state estimation\u001b[39;00m\n\u001b[1;32m---> 18\u001b[0m se_output_data \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mcalculate_state_estimation(\n\u001b[0;32m 19\u001b[0m symmetric\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, \n\u001b[0;32m 20\u001b[0m error_tolerance\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e-8\u001b[39m, \n\u001b[0;32m 21\u001b[0m max_iterations\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, \n\u001b[0;32m 22\u001b[0m calculation_method\u001b[38;5;241m=\u001b[39mCalculationMethod\u001b[38;5;241m.\u001b[39miterative_linear)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:595\u001b[0m, in \u001b[0;36mPowerGridModel.calculate_state_estimation\u001b[1;34m(self, symmetric, error_tolerance, max_iterations, calculation_method, update_data, threading, output_component_types, continue_on_batch_error, decode_error)\u001b[0m\n\u001b[0;32m 513\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcalculate_state_estimation\u001b[39m(\n\u001b[0;32m 514\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 515\u001b[0m \u001b[38;5;241m*\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 524\u001b[0m decode_error: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[0;32m 525\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mdict\u001b[39m[ComponentType, np\u001b[38;5;241m.\u001b[39mndarray]:\n\u001b[0;32m 526\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 527\u001b[0m \u001b[38;5;124;03m Calculate state estimation once with the current model attributes.\u001b[39;00m\n\u001b[0;32m 528\u001b[0m \u001b[38;5;124;03m Or calculate in batch with the given update dataset in batch.\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 593\u001b[0m \u001b[38;5;124;03m Exception: In case an error in the core occurs, an exception will be thrown.\u001b[39;00m\n\u001b[0;32m 594\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 595\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_calculate_state_estimation(\n\u001b[0;32m 596\u001b[0m symmetric\u001b[38;5;241m=\u001b[39msymmetric,\n\u001b[0;32m 597\u001b[0m error_tolerance\u001b[38;5;241m=\u001b[39merror_tolerance,\n\u001b[0;32m 598\u001b[0m max_iterations\u001b[38;5;241m=\u001b[39mmax_iterations,\n\u001b[0;32m 599\u001b[0m calculation_method\u001b[38;5;241m=\u001b[39mcalculation_method,\n\u001b[0;32m 600\u001b[0m update_data\u001b[38;5;241m=\u001b[39m(_map_to_component_types(update_data) \u001b[38;5;28;01mif\u001b[39;00m update_data \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m),\n\u001b[0;32m 601\u001b[0m threading\u001b[38;5;241m=\u001b[39mthreading,\n\u001b[0;32m 602\u001b[0m output_component_types\u001b[38;5;241m=\u001b[39moutput_component_types,\n\u001b[0;32m 603\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 604\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 605\u001b[0m )\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:369\u001b[0m, in \u001b[0;36mPowerGridModel._calculate_state_estimation\u001b[1;34m(self, symmetric, error_tolerance, max_iterations, calculation_method, update_data, threading, output_component_types, continue_on_batch_error, decode_error, experimental_features)\u001b[0m\n\u001b[0;32m 359\u001b[0m calculation_type \u001b[38;5;241m=\u001b[39m CalculationType\u001b[38;5;241m.\u001b[39mstate_estimation\n\u001b[0;32m 360\u001b[0m options \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_options(\n\u001b[0;32m 361\u001b[0m calculation_type\u001b[38;5;241m=\u001b[39mcalculation_type,\n\u001b[0;32m 362\u001b[0m symmetric\u001b[38;5;241m=\u001b[39msymmetric,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 367\u001b[0m experimental_features\u001b[38;5;241m=\u001b[39mexperimental_features,\n\u001b[0;32m 368\u001b[0m )\n\u001b[1;32m--> 369\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_calculate_impl(\n\u001b[0;32m 370\u001b[0m calculation_type\u001b[38;5;241m=\u001b[39mcalculation_type,\n\u001b[0;32m 371\u001b[0m symmetric\u001b[38;5;241m=\u001b[39msymmetric,\n\u001b[0;32m 372\u001b[0m update_data\u001b[38;5;241m=\u001b[39mupdate_data,\n\u001b[0;32m 373\u001b[0m output_component_types\u001b[38;5;241m=\u001b[39moutput_component_types,\n\u001b[0;32m 374\u001b[0m options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[0;32m 375\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 376\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 377\u001b[0m experimental_features\u001b[38;5;241m=\u001b[39mexperimental_features,\n\u001b[0;32m 378\u001b[0m )\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:300\u001b[0m, in \u001b[0;36mPowerGridModel._calculate_impl\u001b[1;34m(self, calculation_type, symmetric, update_data, output_component_types, options, continue_on_batch_error, decode_error, experimental_features)\u001b[0m\n\u001b[0;32m 291\u001b[0m \u001b[38;5;66;03m# run calculation\u001b[39;00m\n\u001b[0;32m 292\u001b[0m pgc\u001b[38;5;241m.\u001b[39mcalculate(\n\u001b[0;32m 293\u001b[0m \u001b[38;5;66;03m# model and options\u001b[39;00m\n\u001b[0;32m 294\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_model,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 297\u001b[0m update_data\u001b[38;5;241m=\u001b[39mupdate_ptr,\n\u001b[0;32m 298\u001b[0m )\n\u001b[1;32m--> 300\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_errors(\n\u001b[0;32m 301\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 302\u001b[0m batch_size\u001b[38;5;241m=\u001b[39mbatch_size,\n\u001b[0;32m 303\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 304\u001b[0m )\n\u001b[0;32m 306\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_data\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:236\u001b[0m, in \u001b[0;36mPowerGridModel._handle_errors\u001b[1;34m(self, continue_on_batch_error, batch_size, decode_error)\u001b[0m\n\u001b[0;32m 235\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_handle_errors\u001b[39m(\u001b[38;5;28mself\u001b[39m, continue_on_batch_error: \u001b[38;5;28mbool\u001b[39m, batch_size: \u001b[38;5;28mint\u001b[39m, decode_error: \u001b[38;5;28mbool\u001b[39m):\n\u001b[1;32m--> 236\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_batch_error \u001b[38;5;241m=\u001b[39m handle_errors(\n\u001b[0;32m 237\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 238\u001b[0m batch_size\u001b[38;5;241m=\u001b[39mbatch_size,\n\u001b[0;32m 239\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 240\u001b[0m )\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\error_handling.py:202\u001b[0m, in \u001b[0;36mhandle_errors\u001b[1;34m(continue_on_batch_error, batch_size, decode_error)\u001b[0m\n\u001b[0;32m 199\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m error\n\u001b[0;32m 201\u001b[0m \u001b[38;5;66;03m# raise normal error\u001b[39;00m\n\u001b[1;32m--> 202\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m error\n", + "\u001b[1;31mNotObservableError\u001b[0m: Not enough measurements available for state estimation.\n\nTry validate_input_data() or validate_batch_data() to validate your data.\n" + ] + } + ], "source": [ "# Initialize 3 symmetric voltage sensors, each connected to a different node\n", "sym_voltage_sensor = initialize_array(DatasetType.input, ComponentType.sym_voltage_sensor, 3)\n", @@ -670,12 +675,53 @@ ] }, { - "attachments": {}, + "cell_type": "markdown", + "id": "70cb5b3c", + "metadata": {}, + "source": [ + "# Assignment 4: Add voltage angle measurements\n", + "\n", + "Because the previous result gave an error, we will now add voltage angle measurements. We will alter the `input_data` and construct a new Model\n", + "\n", + "- initialize the voltage sensors again\n", + "- extend the input data set, with the voltage sensors including the voltage angle\n", + "- construct a new model with the new input data\n", + "- run the state estimation calculation" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "c9a7953f", + "metadata": {}, + "outputs": [], + "source": [ + "# Set the voltage angle in the voltage sensor data\n", + "sym_voltage_sensor[\"u_angle_measured\"] = pf_output_data[ComponentType.node][\"u_angle\"]\n", + "\n", + "# Add the sensors to the input data\n", + "input_data[ComponentType.sym_voltage_sensor] = sym_voltage_sensor\n", + "\n", + "# Validate the input data\n", + "assert_valid_input_data(input_data, calculation_type=CalculationType.state_estimation, symmetric=True)\n", + "\n", + "# Create a power grid model\n", + "model = PowerGridModel(input_data)\n", + "\n", + "# Run the (iterative linear) state estimation\n", + "se_output_data = model.calculate_state_estimation(\n", + " symmetric=True, \n", + " error_tolerance=1e-8, \n", + " max_iterations=20, \n", + " calculation_method=CalculationMethod.iterative_linear)" + ] + }, + { "cell_type": "markdown", "id": "f4736cc1", "metadata": {}, "source": [ - "# Assignment 4: Compare the results between the loadflow and state estimation\n", + "# Assignment 5: Compare the results between the loadflow and state estimation\n", "\n", "For all nodes:\n", "- print the difference in `u` between `se_output_data` and `pf_output_data`\n", @@ -686,12 +732,12 @@ "- print the difference in `q_from` between `se_output_data` and `pf_output_data`\n", "- print the difference in `q_to` between `se_output_data` and `pf_output_data`\n", "\n", - "You should see that while the voltages match quite precisely (in the order of microvolts), the *p* and *q* are way off (in the order of megawatts / mega VARs). This is as expected, because we used voltage angles of 0.0." + "You should see that both the voltages and the *p* and *q* match quite precisely. If you use rounded values as input, there might be a little deviation, but it's rather small compared to the absolute value of *p* and *q*" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 24, "id": "a8d298d5", "metadata": { "scrolled": true @@ -702,12 +748,12 @@ "output_type": "stream", "text": [ "-------------- nodes --------------\n", - "delta_u: [-4.95101631e-07 4.55753252e-07 -3.82213329e-07]\n", + "delta_u: [-4.95099812e-07 4.55753252e-07 -3.82213329e-07]\n", "-------------- lines --------------\n", - "delta_p_from: [-8728680.30456089 -3024647.99628876]\n", - "delta_p_to: [8266130.33127038 2959493.85797146]\n", - "delta_q_from: [10436736.61039324 3714027.04294619]\n", - "delta_q_to: [-10806776.58902305 -3766150.35360264]\n" + "delta_p_from: [-0.02546052 0.01986547]\n", + "delta_p_to: [ 0.02106787 -0.01858635]\n", + "delta_q_from: [-0.02036185 0.01583978]\n", + "delta_q_to: [ 0.01685044 -0.01481901]\n" ] } ], @@ -725,87 +771,13 @@ ] }, { - "attachments": {}, - "cell_type": "markdown", - "id": "8db14616", - "metadata": {}, - "source": [ - "# Assignment 5: Add voltage angle measurements\n", - "\n", - "Now we will update the model by adding voltage angles to the voltage sensors.\n", - "We could alter the `input_data` and construct a new Model, but for the purpose of this workshop (and efficiency) we'll supply the voltage angles as `update_data`, which could potentially be a *batch* calculation in other usecases.\n", - "\n", - "- initialize an update voltage sensor array\n", - "- create an update dataset\n", - "- perform a state estimation, using the update dataset\n", - "- compare the results (as in assignment 4)\n", - "\n", - "You should see that the voltages match quite precisely (in the order of microvolts), the *p* and *q* do too (in the order of 0.01 watts / VARs), because we used the exact voltage angles from the power flow calculation." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "baa25a03", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-------------- nodes --------------\n", - "delta_u: [[-4.95103450e-07 4.55753252e-07 -3.82213329e-07]]\n", - "-------------- lines --------------\n", - "delta_p_from: [[-0.02546053 0.01986549]]\n", - "delta_p_to: [[ 0.02106792 -0.01858632]]\n", - "delta_q_from: [[-0.02036191 0.01583975]]\n", - "delta_q_to: [[ 0.01685042 -0.01481904]]\n" - ] - } - ], - "source": [ - "# Initialize a voltage sensor update array for 3 sensors\n", - "update_sym_voltage_sensor = initialize_array(DatasetType.update, ComponentType.sym_voltage_sensor, 3)\n", - "update_sym_voltage_sensor[\"id\"] = [9, 10, 11] # Use the same IDs as the original sensors\n", - "update_sym_voltage_sensor[\"u_angle_measured\"] = pf_output_data[ComponentType.node][\"u_angle\"]\n", - "\n", - "# Create an update dataset \n", - "update_data = {\n", - " ComponentType.sym_voltage_sensor: update_sym_voltage_sensor\n", - "}\n", - "\n", - "# Validate the update data\n", - "assert_valid_batch_data(input_data, update_data, calculation_type=CalculationType.state_estimation, symmetric=True)\n", - "\n", - "# Run the (iterative linear) state estimation\n", - "se_output_data_u_angle = model.calculate_state_estimation(\n", - " update_data = update_data,\n", - " symmetric=True,\n", - " error_tolerance=1e-8, \n", - " max_iterations=20, \n", - " calculation_method=CalculationMethod.iterative_linear)\n", - "\n", - "# Print the delta u for all nodes (se_output_data_u_angle - pf_output_data)\n", - "print(\"-------------- nodes --------------\")\n", - "print(\"delta_u:\", se_output_data_u_angle[ComponentType.node][\"u\"] - pf_output_data[ComponentType.node][\"u\"])\n", - "\n", - "# Print the delta p and q for all lines (se_output_data_u_angle - pf_output_data)\n", - "print(\"-------------- lines --------------\")\n", - "print(\"delta_p_from:\", se_output_data_u_angle[ComponentType.line][\"p_from\"] - pf_output_data[ComponentType.line][\"p_from\"])\n", - "print(\"delta_p_to:\", se_output_data_u_angle[ComponentType.line][\"p_to\"] - pf_output_data[ComponentType.line][\"p_to\"])\n", - "print(\"delta_q_from:\", se_output_data_u_angle[ComponentType.line][\"q_from\"] - pf_output_data[ComponentType.line][\"q_from\"])\n", - "print(\"delta_q_to:\", se_output_data_u_angle[ComponentType.line][\"q_to\"] - pf_output_data[ComponentType.line][\"q_to\"])" - ] - }, - { - "attachments": {}, "cell_type": "markdown", "id": "7b054f55", "metadata": {}, "source": [ "# Assignment 6: Add power sensors to the model\n", "\n", - "In common power grids most voltage sensors only measure the voltage magnitude; not the angle. In this assigment we will again use the `input_data` of assignment 3 (with unknown voltage angles) and we will connect power sensors to the model.\n", + "In common power grids most voltage sensors only measure the voltage magnitude; not the angle. In this assigment we will again use the `input_data` of assignment 3 and we will connect power sensors to the model.\n", "\n", "In our network it would be possible to connect power sensors to the lines, the loads and the source. To assign realistic measurement values to the power sensors we can use the powerflow output.\n", "\n", @@ -814,12 +786,12 @@ "- Create a new input data set, including both voltage and power sensors\n", "- Use the print statements of assignment 4 to compare the results\n", "\n", - "You should see that the voltages match quite precisely (in the order of microvolts), the *p* and *q* do too (in the order of watts / VARs)." + "You should see that again the voltages match quite precisely (in the order of microvolts), the *p* and *q* do too (in the order of watts / VARs)." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "c7cb7bb7", "metadata": {}, "outputs": [ @@ -1057,7 +1029,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "7db83085", "metadata": {}, "outputs": [ @@ -1066,12 +1038,12 @@ "output_type": "stream", "text": [ "-------------- nodes --------------\n", - "delta_u: [0.00028959 0.00037244 0.00042541]\n", + "delta_u: [-0.02183464 -0.02204176 -0.02207393]\n", "-------------- lines --------------\n", - "delta_p_from: [ 1.69415257 -0.19360323]\n", - "delta_p_to: [-1.7813758 0.13951295]\n", - "delta_q_from: [-4.79719471 -1.68604537]\n", - "delta_q_to: [4.70671219 1.61927823]\n" + "delta_p_from: [-73.84315465 -25.57343819]\n", + "delta_p_to: [73.76371305 25.51731618]\n", + "delta_q_from: [-0.57519337 -0.42228019]\n", + "delta_q_to: [1.89164762 1.67790199]\n" ] } ], @@ -1114,7 +1086,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "5f70a3ee", "metadata": {}, @@ -1125,7 +1096,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "e8e2e740", "metadata": {}, "outputs": [ @@ -1136,14 +1107,14 @@ "\n", "u_angle\n", "pf: [-0.00319565 -0.04673618 -0.06415622]\n", - "se: [ 0. -0.04354054 -0.06096058]\n", + "se: [-0.00319523 -0.0467358 -0.06415587]\n", "\n", "u_angle'\n", "pf: [ 0. -0.04354053 -0.06096057]\n", - "se: [ 0. -0.04354054 -0.06096058]\n", + "se: [ 0. -0.04354057 -0.06096064]\n", "\n", "delta_u_angle\n", - "[ 0.00000000e+00 -1.24601555e-08 -1.52941081e-08]\n" + "[ 0.00000000e+00 -4.68560714e-08 -7.37505219e-08]\n" ] } ], @@ -1172,8 +1143,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", + "id": "f9a26251", "metadata": {}, "source": [ "# Assignment 7: Time Series Batch Calculation\n", @@ -1187,7 +1158,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "2d716bad", "metadata": {}, "outputs": [ @@ -1220,33 +1191,33 @@ " \n", " \n", " 2022-01-01 00:00:00\n", - " 10577.173048\n", - " 9485.014140\n", - " 9306.838822\n", + " 10707.811014\n", + " 9413.446713\n", + " 9343.978605\n", " \n", " \n", " 2022-01-01 00:15:00\n", - " 10383.156731\n", - " 9561.238330\n", - " 9196.660220\n", + " 10368.752561\n", + " 9501.354840\n", + " 9372.914376\n", " \n", " \n", " 2022-01-01 00:30:00\n", - " 10468.776002\n", - " 9617.045095\n", - " 9291.992823\n", + " 10420.774821\n", + " 9530.739928\n", + " 9314.295846\n", " \n", " \n", " 2022-01-01 00:45:00\n", - " 10638.726675\n", - " 9581.373664\n", - " 9139.434272\n", + " 10379.607590\n", + " 9806.599094\n", + " 9133.134454\n", " \n", " \n", " 2022-01-01 01:00:00\n", - " 10434.418070\n", - " 9379.770132\n", - " 9145.699301\n", + " 10511.471402\n", + " 9579.444446\n", + " 9268.337312\n", " \n", " \n", " ...\n", @@ -1256,33 +1227,33 @@ " \n", " \n", " 2022-01-01 22:45:00\n", - " 10516.502657\n", - " 9605.883339\n", - " 9271.719113\n", + " 10251.802408\n", + " 9653.555731\n", + " 9258.635850\n", " \n", " \n", " 2022-01-01 23:00:00\n", - " 10551.524508\n", - " 9561.235876\n", - " 9175.353526\n", + " 10451.512435\n", + " 9447.150291\n", + " 9032.962911\n", " \n", " \n", " 2022-01-01 23:15:00\n", - " 10479.990630\n", - " 9369.872727\n", - " 9038.040954\n", + " 10408.350789\n", + " 9626.804841\n", + " 9390.582449\n", " \n", " \n", " 2022-01-01 23:30:00\n", - " 10516.245419\n", - " 9346.977853\n", - " 9345.451576\n", + " 10547.570684\n", + " 9747.520025\n", + " 9132.946240\n", " \n", " \n", " 2022-01-01 23:45:00\n", - " 10524.655959\n", - " 9558.837203\n", - " 9339.719284\n", + " 10449.694745\n", + " 9485.213969\n", + " 9265.480261\n", " \n", " \n", "\n", @@ -1291,17 +1262,17 @@ ], "text/plain": [ " 9 10 11\n", - "2022-01-01 00:00:00 10577.173048 9485.014140 9306.838822\n", - "2022-01-01 00:15:00 10383.156731 9561.238330 9196.660220\n", - "2022-01-01 00:30:00 10468.776002 9617.045095 9291.992823\n", - "2022-01-01 00:45:00 10638.726675 9581.373664 9139.434272\n", - "2022-01-01 01:00:00 10434.418070 9379.770132 9145.699301\n", + "2022-01-01 00:00:00 10707.811014 9413.446713 9343.978605\n", + "2022-01-01 00:15:00 10368.752561 9501.354840 9372.914376\n", + "2022-01-01 00:30:00 10420.774821 9530.739928 9314.295846\n", + "2022-01-01 00:45:00 10379.607590 9806.599094 9133.134454\n", + "2022-01-01 01:00:00 10511.471402 9579.444446 9268.337312\n", "... ... ... ...\n", - "2022-01-01 22:45:00 10516.502657 9605.883339 9271.719113\n", - "2022-01-01 23:00:00 10551.524508 9561.235876 9175.353526\n", - "2022-01-01 23:15:00 10479.990630 9369.872727 9038.040954\n", - "2022-01-01 23:30:00 10516.245419 9346.977853 9345.451576\n", - "2022-01-01 23:45:00 10524.655959 9558.837203 9339.719284\n", + "2022-01-01 22:45:00 10251.802408 9653.555731 9258.635850\n", + "2022-01-01 23:00:00 10451.512435 9447.150291 9032.962911\n", + "2022-01-01 23:15:00 10408.350789 9626.804841 9390.582449\n", + "2022-01-01 23:30:00 10547.570684 9747.520025 9132.946240\n", + "2022-01-01 23:45:00 10449.694745 9485.213969 9265.480261\n", "\n", "[96 rows x 3 columns]" ] @@ -1322,7 +1293,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "aadcedbd", "metadata": {}, @@ -1337,7 +1307,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "dfdcb8fe", "metadata": {}, "outputs": [], @@ -1357,7 +1327,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "582a7323", "metadata": {}, "outputs": [], @@ -1373,7 +1343,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "e74fcd19", "metadata": {}, "outputs": [], @@ -1382,7 +1352,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "fe0fe0fa", "metadata": {}, @@ -1397,7 +1366,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "d7226899", "metadata": {}, "outputs": [ @@ -1405,9 +1374,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "max power load: [21512305.30894372 10581372.96343217]\n", - "min power load: [18554011.90649454 9202715.72274092]\n", - "ratio: [1.15944225 1.14980983]\n" + "max power load: [20391952.52463956 10071512.87572569]\n", + "min power load: [19645670.67656706 9938240.92934767]\n", + "ratio: [1.03798709 1.01341001]\n" ] } ], @@ -1423,7 +1392,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "e7e0f878", "metadata": {}, @@ -1437,13 +1405,13 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "c87c4179", "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1465,6 +1433,14 @@ "plt.ylabel('Loading')\n", "plt.show()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c3d44398", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -1483,7 +1459,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/state-estimation-assignment/State Estimation Assignment.ipynb b/state-estimation-assignment/State Estimation Assignment.ipynb index 5b597ef..b460302 100644 --- a/state-estimation-assignment/State Estimation Assignment.ipynb +++ b/state-estimation-assignment/State Estimation Assignment.ipynb @@ -218,12 +218,7 @@ "source": [ "# Assignment 3: Initialize the sensors\n", "\n", - "In this assignment we will perform a state estimation based on three voltage sensors that only measure the voltage. \n", - "If you look closely to the data, you'll notice that the number of measurements (3) is not larger than or equal to the number of unknowns (6). \n", - "So the system is not *fully observable* and you might expect the state estimation to fail. \n", - "However, the linear state estimation algorithm will assume the voltage angles (3) to be zero if no value is given. \n", - "In other words, the mathematical core will give us a faulty result, without any warning! \n", - "To prevent this, we need an observability check, which is complex, but will be added to the validation functions in the future.\n", + "In this assignment we will try to perform a state estimation based on three voltage sensors that only measure the voltage. However, because the number of measurements (3) is lower than the number of unknowns (6), the system is not *fully observable*. This should result in an error.\n", "\n", "- initialize the voltage sensors\n", "- extend the input data set, with the voltage sensors\n", @@ -262,12 +257,54 @@ " calculation_method=CalculationMethod.iterative_linear)" ] }, + { + "cell_type": "markdown", + "id": "ebf8233b", + "metadata": {}, + "source": [ + "# Assignment 4: Add voltage angle measurements\n", + "\n", + "Because the previous result gave an error, we will now add voltage angle measurements. We will alter the `input_data` and construct a new Model\n", + "\n", + "- initialize the voltage sensors again\n", + "- extend the input data set, with the voltage sensors including the voltage angle\n", + "- construct a new model with the new input data\n", + "- run the state estimation calculation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "225cf098", + "metadata": {}, + "outputs": [], + "source": [ + "# Set the voltage angle in the voltage sensor data\n", + "sym_voltage_sensor[\"u_angle_measured\"] = ...\n", + "\n", + "# Add the sensors to the input data\n", + "input_data[...] = sym_voltage_sensor\n", + "\n", + "# Validate the input data\n", + "assert_valid_input_data(..., calculation_type=..., symmetric=...)\n", + "\n", + "# Create a power grid model\n", + "model = PowerGridModel(input_data)\n", + "\n", + "# Run the (iterative linear) state estimation\n", + "se_output_data = model.calculate_state_estimation(\n", + " symmetric=True, \n", + " error_tolerance=1e-8, \n", + " max_iterations=20, \n", + " calculation_method=CalculationMethod.iterative_linear)" + ] + }, { "cell_type": "markdown", "id": "f4736cc1", "metadata": {}, "source": [ - "# Assignment 4: Compare the results between the loadflow and state estimation\n", + "# Assignment 5: Compare the results between the loadflow and state estimation\n", "\n", "For all nodes:\n", "- print the difference in `u` between `se_output_data` and `pf_output_data`\n", @@ -278,7 +315,7 @@ "- print the difference in `q_from` between `se_output_data` and `pf_output_data`\n", "- print the difference in `q_to` between `se_output_data` and `pf_output_data`\n", "\n", - "You should see that both the voltages and the *p* and *q* match quite precisely." + "You should see that both the voltages and the *p* and *q* match quite precisely. If you use rounded values as input, there might be a little deviation, but it's rather small compared to the absolute value of *p* and *q*" ] }, { @@ -307,7 +344,7 @@ "id": "7b054f55", "metadata": {}, "source": [ - "# Assignment 5: Add power sensors to the model\n", + "# Assignment 6: Add power sensors to the model\n", "\n", "In common power grids most voltage sensors only measure the voltage magnitude; not the angle. In this assigment we will again use the `input_data` of assignment 3 and we will connect power sensors to the model.\n", "\n", @@ -425,7 +462,7 @@ "id": "4e48d946", "metadata": {}, "source": [ - "# Assignment 6: Time Series Batch Calculation\n", + "# Assignment 7: Time Series Batch Calculation\n", "\n", "Sometimes, it is desirable to see what the state of the power grid was for a number of measurements at different points in time. A typical use case is to see if the voltage or power requirements were not met over the past day.\n", "\n", From 0e0ee27416bf1c4acf7c49cb72acfb3b35ad0d9a Mon Sep 17 00:00:00 2001 From: Sander-Timmerman Date: Thu, 3 Apr 2025 10:25:02 +0200 Subject: [PATCH 4/6] updates Signed-off-by: Sander-Timmerman --- ...Estimation Assignment with Solutions.ipynb | 171 +++++++++--------- .../State Estimation Assignment.ipynb | 14 +- 2 files changed, 93 insertions(+), 92 deletions(-) diff --git a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb index bc51fa4..d2202dd 100644 --- a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb +++ b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 1, "id": "2bc7de1e", "metadata": {}, "outputs": [], @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 2, "id": "760a38b1", "metadata": {}, "outputs": [], @@ -151,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 3, "id": "02130221", "metadata": {}, "outputs": [ @@ -502,7 +502,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 4, "id": "2baee3cd", "metadata": {}, "outputs": [], @@ -526,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 5, "id": "71b39571", "metadata": {}, "outputs": [ @@ -628,24 +628,18 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 6, "id": "88034903", "metadata": {}, "outputs": [ { - "ename": "NotObservableError", - "evalue": "Not enough measurements available for state estimation.\n\nTry validate_input_data() or validate_batch_data() to validate your data.\n", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNotObservableError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[22], line 18\u001b[0m\n\u001b[0;32m 15\u001b[0m model \u001b[38;5;241m=\u001b[39m PowerGridModel(input_data)\n\u001b[0;32m 17\u001b[0m \u001b[38;5;66;03m# Run the (iterative linear) state estimation\u001b[39;00m\n\u001b[1;32m---> 18\u001b[0m se_output_data \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mcalculate_state_estimation(\n\u001b[0;32m 19\u001b[0m symmetric\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, \n\u001b[0;32m 20\u001b[0m error_tolerance\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e-8\u001b[39m, \n\u001b[0;32m 21\u001b[0m max_iterations\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, \n\u001b[0;32m 22\u001b[0m calculation_method\u001b[38;5;241m=\u001b[39mCalculationMethod\u001b[38;5;241m.\u001b[39miterative_linear)\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:595\u001b[0m, in \u001b[0;36mPowerGridModel.calculate_state_estimation\u001b[1;34m(self, symmetric, error_tolerance, max_iterations, calculation_method, update_data, threading, output_component_types, continue_on_batch_error, decode_error)\u001b[0m\n\u001b[0;32m 513\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcalculate_state_estimation\u001b[39m(\n\u001b[0;32m 514\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 515\u001b[0m \u001b[38;5;241m*\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 524\u001b[0m decode_error: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[0;32m 525\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mdict\u001b[39m[ComponentType, np\u001b[38;5;241m.\u001b[39mndarray]:\n\u001b[0;32m 526\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 527\u001b[0m \u001b[38;5;124;03m Calculate state estimation once with the current model attributes.\u001b[39;00m\n\u001b[0;32m 528\u001b[0m \u001b[38;5;124;03m Or calculate in batch with the given update dataset in batch.\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 593\u001b[0m \u001b[38;5;124;03m Exception: In case an error in the core occurs, an exception will be thrown.\u001b[39;00m\n\u001b[0;32m 594\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 595\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_calculate_state_estimation(\n\u001b[0;32m 596\u001b[0m symmetric\u001b[38;5;241m=\u001b[39msymmetric,\n\u001b[0;32m 597\u001b[0m error_tolerance\u001b[38;5;241m=\u001b[39merror_tolerance,\n\u001b[0;32m 598\u001b[0m max_iterations\u001b[38;5;241m=\u001b[39mmax_iterations,\n\u001b[0;32m 599\u001b[0m calculation_method\u001b[38;5;241m=\u001b[39mcalculation_method,\n\u001b[0;32m 600\u001b[0m update_data\u001b[38;5;241m=\u001b[39m(_map_to_component_types(update_data) \u001b[38;5;28;01mif\u001b[39;00m update_data \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m),\n\u001b[0;32m 601\u001b[0m threading\u001b[38;5;241m=\u001b[39mthreading,\n\u001b[0;32m 602\u001b[0m output_component_types\u001b[38;5;241m=\u001b[39moutput_component_types,\n\u001b[0;32m 603\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 604\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 605\u001b[0m )\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:369\u001b[0m, in \u001b[0;36mPowerGridModel._calculate_state_estimation\u001b[1;34m(self, symmetric, error_tolerance, max_iterations, calculation_method, update_data, threading, output_component_types, continue_on_batch_error, decode_error, experimental_features)\u001b[0m\n\u001b[0;32m 359\u001b[0m calculation_type \u001b[38;5;241m=\u001b[39m CalculationType\u001b[38;5;241m.\u001b[39mstate_estimation\n\u001b[0;32m 360\u001b[0m options \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_options(\n\u001b[0;32m 361\u001b[0m calculation_type\u001b[38;5;241m=\u001b[39mcalculation_type,\n\u001b[0;32m 362\u001b[0m symmetric\u001b[38;5;241m=\u001b[39msymmetric,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 367\u001b[0m experimental_features\u001b[38;5;241m=\u001b[39mexperimental_features,\n\u001b[0;32m 368\u001b[0m )\n\u001b[1;32m--> 369\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_calculate_impl(\n\u001b[0;32m 370\u001b[0m calculation_type\u001b[38;5;241m=\u001b[39mcalculation_type,\n\u001b[0;32m 371\u001b[0m symmetric\u001b[38;5;241m=\u001b[39msymmetric,\n\u001b[0;32m 372\u001b[0m update_data\u001b[38;5;241m=\u001b[39mupdate_data,\n\u001b[0;32m 373\u001b[0m output_component_types\u001b[38;5;241m=\u001b[39moutput_component_types,\n\u001b[0;32m 374\u001b[0m options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[0;32m 375\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 376\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 377\u001b[0m experimental_features\u001b[38;5;241m=\u001b[39mexperimental_features,\n\u001b[0;32m 378\u001b[0m )\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:300\u001b[0m, in \u001b[0;36mPowerGridModel._calculate_impl\u001b[1;34m(self, calculation_type, symmetric, update_data, output_component_types, options, continue_on_batch_error, decode_error, experimental_features)\u001b[0m\n\u001b[0;32m 291\u001b[0m \u001b[38;5;66;03m# run calculation\u001b[39;00m\n\u001b[0;32m 292\u001b[0m pgc\u001b[38;5;241m.\u001b[39mcalculate(\n\u001b[0;32m 293\u001b[0m \u001b[38;5;66;03m# model and options\u001b[39;00m\n\u001b[0;32m 294\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_model,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 297\u001b[0m update_data\u001b[38;5;241m=\u001b[39mupdate_ptr,\n\u001b[0;32m 298\u001b[0m )\n\u001b[1;32m--> 300\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_errors(\n\u001b[0;32m 301\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 302\u001b[0m batch_size\u001b[38;5;241m=\u001b[39mbatch_size,\n\u001b[0;32m 303\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 304\u001b[0m )\n\u001b[0;32m 306\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_data\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\power_grid_model.py:236\u001b[0m, in \u001b[0;36mPowerGridModel._handle_errors\u001b[1;34m(self, continue_on_batch_error, batch_size, decode_error)\u001b[0m\n\u001b[0;32m 235\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_handle_errors\u001b[39m(\u001b[38;5;28mself\u001b[39m, continue_on_batch_error: \u001b[38;5;28mbool\u001b[39m, batch_size: \u001b[38;5;28mint\u001b[39m, decode_error: \u001b[38;5;28mbool\u001b[39m):\n\u001b[1;32m--> 236\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_batch_error \u001b[38;5;241m=\u001b[39m handle_errors(\n\u001b[0;32m 237\u001b[0m continue_on_batch_error\u001b[38;5;241m=\u001b[39mcontinue_on_batch_error,\n\u001b[0;32m 238\u001b[0m batch_size\u001b[38;5;241m=\u001b[39mbatch_size,\n\u001b[0;32m 239\u001b[0m decode_error\u001b[38;5;241m=\u001b[39mdecode_error,\n\u001b[0;32m 240\u001b[0m )\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\power_grid_model\\_core\\error_handling.py:202\u001b[0m, in \u001b[0;36mhandle_errors\u001b[1;34m(continue_on_batch_error, batch_size, decode_error)\u001b[0m\n\u001b[0;32m 199\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m error\n\u001b[0;32m 201\u001b[0m \u001b[38;5;66;03m# raise normal error\u001b[39;00m\n\u001b[1;32m--> 202\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m error\n", - "\u001b[1;31mNotObservableError\u001b[0m: Not enough measurements available for state estimation.\n\nTry validate_input_data() or validate_batch_data() to validate your data.\n" + "name": "stdout", + "output_type": "stream", + "text": [ + "Not enough measurements available for state estimation.\n", + "\n", + "Try validate_input_data() or validate_batch_data() to validate your data.\n", + "\n" ] } ], @@ -667,11 +661,14 @@ "model = PowerGridModel(input_data)\n", "\n", "# Run the (iterative linear) state estimation\n", - "se_output_data = model.calculate_state_estimation(\n", - " symmetric=True, \n", - " error_tolerance=1e-8, \n", - " max_iterations=20, \n", - " calculation_method=CalculationMethod.iterative_linear)" + "try:\n", + " se_output_data = model.calculate_state_estimation(\n", + " symmetric=True,\n", + " error_tolerance=1e-8,\n", + " max_iterations=20,\n", + " calculation_method=CalculationMethod.iterative_linear)\n", + "except Exception as e:\n", + " print(e)" ] }, { @@ -691,7 +688,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 7, "id": "c9a7953f", "metadata": {}, "outputs": [], @@ -737,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 8, "id": "a8d298d5", "metadata": { "scrolled": true @@ -791,7 +788,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "c7cb7bb7", "metadata": {}, "outputs": [ @@ -1029,7 +1026,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "7db83085", "metadata": {}, "outputs": [ @@ -1038,12 +1035,12 @@ "output_type": "stream", "text": [ "-------------- nodes --------------\n", - "delta_u: [-0.02183464 -0.02204176 -0.02207393]\n", + "delta_u: [-0.00024486 -0.00016916 -0.00011817]\n", "-------------- lines --------------\n", - "delta_p_from: [-73.84315465 -25.57343819]\n", - "delta_p_to: [73.76371305 25.51731618]\n", - "delta_q_from: [-0.57519337 -0.42228019]\n", - "delta_q_to: [1.89164762 1.67790199]\n" + "delta_p_from: [-0.13340325 -0.80568118]\n", + "delta_p_to: [0.04635401 0.75155294]\n", + "delta_q_from: [-4.68525673 -1.66030508]\n", + "delta_q_to: [4.62875468 1.62549793]\n" ] } ], @@ -1096,7 +1093,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "e8e2e740", "metadata": {}, "outputs": [ @@ -1107,14 +1104,14 @@ "\n", "u_angle\n", "pf: [-0.00319565 -0.04673618 -0.06415622]\n", - "se: [-0.00319523 -0.0467358 -0.06415587]\n", + "se: [-0.00319578 -0.04673632 -0.06415637]\n", "\n", "u_angle'\n", "pf: [ 0. -0.04354053 -0.06096057]\n", - "se: [ 0. -0.04354057 -0.06096064]\n", + "se: [ 0. -0.04354054 -0.06096058]\n", "\n", "delta_u_angle\n", - "[ 0.00000000e+00 -4.68560714e-08 -7.37505219e-08]\n" + "[ 0.00000000e+00 -1.32612176e-08 -1.66927135e-08]\n" ] } ], @@ -1158,7 +1155,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "2d716bad", "metadata": {}, "outputs": [ @@ -1191,33 +1188,33 @@ " \n", " \n", " 2022-01-01 00:00:00\n", - " 10707.811014\n", - " 9413.446713\n", - " 9343.978605\n", + " 10505.071297\n", + " 9556.358042\n", + " 8979.453846\n", " \n", " \n", " 2022-01-01 00:15:00\n", - " 10368.752561\n", - " 9501.354840\n", - " 9372.914376\n", + " 10472.366122\n", + " 9590.359109\n", + " 9158.149264\n", " \n", " \n", " 2022-01-01 00:30:00\n", - " 10420.774821\n", - " 9530.739928\n", - " 9314.295846\n", + " 10430.783413\n", + " 9571.307686\n", + " 9361.661032\n", " \n", " \n", " 2022-01-01 00:45:00\n", - " 10379.607590\n", - " 9806.599094\n", - " 9133.134454\n", + " 10496.095778\n", + " 9721.916002\n", + " 9087.858887\n", " \n", " \n", " 2022-01-01 01:00:00\n", - " 10511.471402\n", - " 9579.444446\n", - " 9268.337312\n", + " 10456.970477\n", + " 9732.933301\n", + " 9149.232895\n", " \n", " \n", " ...\n", @@ -1227,33 +1224,33 @@ " \n", " \n", " 2022-01-01 22:45:00\n", - " 10251.802408\n", - " 9653.555731\n", - " 9258.635850\n", + " 10463.871386\n", + " 9591.701667\n", + " 9181.804136\n", " \n", " \n", " 2022-01-01 23:00:00\n", - " 10451.512435\n", - " 9447.150291\n", - " 9032.962911\n", + " 10557.345322\n", + " 9493.200006\n", + " 9206.088224\n", " \n", " \n", " 2022-01-01 23:15:00\n", - " 10408.350789\n", - " 9626.804841\n", - " 9390.582449\n", + " 10411.855598\n", + " 9370.505307\n", + " 9217.738430\n", " \n", " \n", " 2022-01-01 23:30:00\n", - " 10547.570684\n", - " 9747.520025\n", - " 9132.946240\n", + " 10463.747896\n", + " 9622.379641\n", + " 9064.659914\n", " \n", " \n", " 2022-01-01 23:45:00\n", - " 10449.694745\n", - " 9485.213969\n", - " 9265.480261\n", + " 10407.162675\n", + " 9487.929498\n", + " 9247.524005\n", " \n", " \n", "\n", @@ -1262,17 +1259,17 @@ ], "text/plain": [ " 9 10 11\n", - "2022-01-01 00:00:00 10707.811014 9413.446713 9343.978605\n", - "2022-01-01 00:15:00 10368.752561 9501.354840 9372.914376\n", - "2022-01-01 00:30:00 10420.774821 9530.739928 9314.295846\n", - "2022-01-01 00:45:00 10379.607590 9806.599094 9133.134454\n", - "2022-01-01 01:00:00 10511.471402 9579.444446 9268.337312\n", + "2022-01-01 00:00:00 10505.071297 9556.358042 8979.453846\n", + "2022-01-01 00:15:00 10472.366122 9590.359109 9158.149264\n", + "2022-01-01 00:30:00 10430.783413 9571.307686 9361.661032\n", + "2022-01-01 00:45:00 10496.095778 9721.916002 9087.858887\n", + "2022-01-01 01:00:00 10456.970477 9732.933301 9149.232895\n", "... ... ... ...\n", - "2022-01-01 22:45:00 10251.802408 9653.555731 9258.635850\n", - "2022-01-01 23:00:00 10451.512435 9447.150291 9032.962911\n", - "2022-01-01 23:15:00 10408.350789 9626.804841 9390.582449\n", - "2022-01-01 23:30:00 10547.570684 9747.520025 9132.946240\n", - "2022-01-01 23:45:00 10449.694745 9485.213969 9265.480261\n", + "2022-01-01 22:45:00 10463.871386 9591.701667 9181.804136\n", + "2022-01-01 23:00:00 10557.345322 9493.200006 9206.088224\n", + "2022-01-01 23:15:00 10411.855598 9370.505307 9217.738430\n", + "2022-01-01 23:30:00 10463.747896 9622.379641 9064.659914\n", + "2022-01-01 23:45:00 10407.162675 9487.929498 9247.524005\n", "\n", "[96 rows x 3 columns]" ] @@ -1307,7 +1304,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "dfdcb8fe", "metadata": {}, "outputs": [], @@ -1327,7 +1324,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "582a7323", "metadata": {}, "outputs": [], @@ -1343,7 +1340,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "e74fcd19", "metadata": {}, "outputs": [], @@ -1366,7 +1363,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "d7226899", "metadata": {}, "outputs": [ @@ -1374,9 +1371,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "max power load: [20391952.52463956 10071512.87572569]\n", - "min power load: [19645670.67656706 9938240.92934767]\n", - "ratio: [1.03798709 1.01341001]\n" + "max power load: [20380848.76970243 10070427.34573025]\n", + "min power load: [19640596.79998607 9936984.59368392]\n", + "ratio: [1.03768989 1.0134289 ]\n" ] } ], @@ -1405,13 +1402,13 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "c87c4179", "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] diff --git a/state-estimation-assignment/State Estimation Assignment.ipynb b/state-estimation-assignment/State Estimation Assignment.ipynb index b460302..c9de039 100644 --- a/state-estimation-assignment/State Estimation Assignment.ipynb +++ b/state-estimation-assignment/State Estimation Assignment.ipynb @@ -250,11 +250,15 @@ "model = PowerGridModel(input_data)\n", "\n", "# Run the (iterative linear) state estimation\n", - "se_output_data = model.calculate_state_estimation(\n", - " symmetric=True, \n", - " error_tolerance=1e-8, \n", - " max_iterations=20, \n", - " calculation_method=CalculationMethod.iterative_linear)" + "try:\n", + " se_output_data = model.calculate_state_estimation(\n", + " symmetric=True,\n", + " error_tolerance=1e-8,\n", + " max_iterations=20,\n", + " calculation_method=CalculationMethod.iterative_linear)\n", + "except Exception as e:\n", + " print(e)\n", + " \n" ] }, { From 5b8a30fe1cb91d755991d3dc8ec2618882437f28 Mon Sep 17 00:00:00 2001 From: Sander-Timmerman Date: Fri, 4 Apr 2025 11:45:44 +0200 Subject: [PATCH 5/6] python version Signed-off-by: Sander-Timmerman --- ...Estimation Assignment with Solutions.ipynb | 127 +++++++++--------- 1 file changed, 65 insertions(+), 62 deletions(-) diff --git a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb index d2202dd..9bfc586 100644 --- a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb +++ b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "2bc7de1e", "metadata": {}, "outputs": [], @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "760a38b1", "metadata": {}, "outputs": [], @@ -151,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "02130221", "metadata": {}, "outputs": [ @@ -502,7 +502,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "2baee3cd", "metadata": {}, "outputs": [], @@ -526,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "71b39571", "metadata": {}, "outputs": [ @@ -628,7 +628,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "88034903", "metadata": {}, "outputs": [ @@ -688,7 +688,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "c9a7953f", "metadata": {}, "outputs": [], @@ -734,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "a8d298d5", "metadata": { "scrolled": true @@ -788,7 +788,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "c7cb7bb7", "metadata": {}, "outputs": [ @@ -1026,7 +1026,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "7db83085", "metadata": {}, "outputs": [ @@ -1093,7 +1093,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "e8e2e740", "metadata": {}, "outputs": [ @@ -1155,7 +1155,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "2d716bad", "metadata": {}, "outputs": [ @@ -1188,33 +1188,33 @@ " \n", " \n", " 2022-01-01 00:00:00\n", - " 10505.071297\n", - " 9556.358042\n", - " 8979.453846\n", + " 10515.903626\n", + " 9519.269996\n", + " 9285.942457\n", " \n", " \n", " 2022-01-01 00:15:00\n", - " 10472.366122\n", - " 9590.359109\n", - " 9158.149264\n", + " 10571.251382\n", + " 9504.850773\n", + " 9086.425137\n", " \n", " \n", " 2022-01-01 00:30:00\n", - " 10430.783413\n", - " 9571.307686\n", - " 9361.661032\n", + " 10480.791787\n", + " 9635.056812\n", + " 9096.222447\n", " \n", " \n", " 2022-01-01 00:45:00\n", - " 10496.095778\n", - " 9721.916002\n", - " 9087.858887\n", + " 10507.228812\n", + " 9552.950661\n", + " 9230.305044\n", " \n", " \n", " 2022-01-01 01:00:00\n", - " 10456.970477\n", - " 9732.933301\n", - " 9149.232895\n", + " 10501.045884\n", + " 9655.662750\n", + " 9292.624845\n", " \n", " \n", " ...\n", @@ -1224,33 +1224,33 @@ " \n", " \n", " 2022-01-01 22:45:00\n", - " 10463.871386\n", - " 9591.701667\n", - " 9181.804136\n", + " 10634.333469\n", + " 9503.854463\n", + " 9186.518621\n", " \n", " \n", " 2022-01-01 23:00:00\n", - " 10557.345322\n", - " 9493.200006\n", - " 9206.088224\n", + " 10652.795359\n", + " 9563.450849\n", + " 9221.243219\n", " \n", " \n", " 2022-01-01 23:15:00\n", - " 10411.855598\n", - " 9370.505307\n", - " 9217.738430\n", + " 10456.577120\n", + " 9555.280069\n", + " 9376.888530\n", " \n", " \n", " 2022-01-01 23:30:00\n", - " 10463.747896\n", - " 9622.379641\n", - " 9064.659914\n", + " 10396.306880\n", + " 9405.658892\n", + " 9145.239732\n", " \n", " \n", " 2022-01-01 23:45:00\n", - " 10407.162675\n", - " 9487.929498\n", - " 9247.524005\n", + " 10571.715516\n", + " 9516.401493\n", + " 9213.450714\n", " \n", " \n", "\n", @@ -1259,17 +1259,17 @@ ], "text/plain": [ " 9 10 11\n", - "2022-01-01 00:00:00 10505.071297 9556.358042 8979.453846\n", - "2022-01-01 00:15:00 10472.366122 9590.359109 9158.149264\n", - "2022-01-01 00:30:00 10430.783413 9571.307686 9361.661032\n", - "2022-01-01 00:45:00 10496.095778 9721.916002 9087.858887\n", - "2022-01-01 01:00:00 10456.970477 9732.933301 9149.232895\n", + "2022-01-01 00:00:00 10515.903626 9519.269996 9285.942457\n", + "2022-01-01 00:15:00 10571.251382 9504.850773 9086.425137\n", + "2022-01-01 00:30:00 10480.791787 9635.056812 9096.222447\n", + "2022-01-01 00:45:00 10507.228812 9552.950661 9230.305044\n", + "2022-01-01 01:00:00 10501.045884 9655.662750 9292.624845\n", "... ... ... ...\n", - "2022-01-01 22:45:00 10463.871386 9591.701667 9181.804136\n", - "2022-01-01 23:00:00 10557.345322 9493.200006 9206.088224\n", - "2022-01-01 23:15:00 10411.855598 9370.505307 9217.738430\n", - "2022-01-01 23:30:00 10463.747896 9622.379641 9064.659914\n", - "2022-01-01 23:45:00 10407.162675 9487.929498 9247.524005\n", + "2022-01-01 22:45:00 10634.333469 9503.854463 9186.518621\n", + "2022-01-01 23:00:00 10652.795359 9563.450849 9221.243219\n", + "2022-01-01 23:15:00 10456.577120 9555.280069 9376.888530\n", + "2022-01-01 23:30:00 10396.306880 9405.658892 9145.239732\n", + "2022-01-01 23:45:00 10571.715516 9516.401493 9213.450714\n", "\n", "[96 rows x 3 columns]" ] @@ -1304,7 +1304,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "dfdcb8fe", "metadata": {}, "outputs": [], @@ -1324,7 +1324,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "582a7323", "metadata": {}, "outputs": [], @@ -1340,7 +1340,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "e74fcd19", "metadata": {}, "outputs": [], @@ -1363,7 +1363,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "d7226899", "metadata": {}, "outputs": [ @@ -1371,9 +1371,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "max power load: [20380848.76970243 10070427.34573025]\n", - "min power load: [19640596.79998607 9936984.59368392]\n", - "ratio: [1.03768989 1.0134289 ]\n" + "max power load: [20434193.11194256 10049332.4056693 ]\n", + "min power load: [19743595.69002406 9930151.59743081]\n", + "ratio: [1.0349783 1.01200191]\n" ] } ], @@ -1402,13 +1402,15 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "c87c4179", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1441,6 +1443,7 @@ } ], "metadata": { + "celltoolbar": "Geen", "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", From 539dd60742089b294654783dab29375c0a519376 Mon Sep 17 00:00:00 2001 From: Sander-Timmerman Date: Fri, 4 Apr 2025 12:27:57 +0200 Subject: [PATCH 6/6] run with latest version Signed-off-by: Sander-Timmerman --- ...Estimation Assignment with Solutions.ipynb | 128 +++++++++--------- .../State Estimation Assignment.ipynb | 6 +- 2 files changed, 67 insertions(+), 67 deletions(-) diff --git a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb index 9bfc586..5962dcf 100644 --- a/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb +++ b/state-estimation-assignment/State Estimation Assignment with Solutions.ipynb @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "2bc7de1e", "metadata": {}, "outputs": [], @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "760a38b1", "metadata": {}, "outputs": [], @@ -151,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "02130221", "metadata": {}, "outputs": [ @@ -502,7 +502,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "2baee3cd", "metadata": {}, "outputs": [], @@ -526,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "71b39571", "metadata": {}, "outputs": [ @@ -628,7 +628,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "88034903", "metadata": {}, "outputs": [ @@ -688,7 +688,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "c9a7953f", "metadata": {}, "outputs": [], @@ -734,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "a8d298d5", "metadata": { "scrolled": true @@ -788,7 +788,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "c7cb7bb7", "metadata": {}, "outputs": [ @@ -1026,7 +1026,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "7db83085", "metadata": {}, "outputs": [ @@ -1093,7 +1093,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "e8e2e740", "metadata": {}, "outputs": [ @@ -1155,7 +1155,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "2d716bad", "metadata": {}, "outputs": [ @@ -1188,33 +1188,33 @@ " \n", " \n", " 2022-01-01 00:00:00\n", - " 10515.903626\n", - " 9519.269996\n", - " 9285.942457\n", + " 10606.480633\n", + " 9449.649580\n", + " 9205.568138\n", " \n", " \n", " 2022-01-01 00:15:00\n", - " 10571.251382\n", - " 9504.850773\n", - " 9086.425137\n", + " 10483.366999\n", + " 9727.240644\n", + " 9212.518569\n", " \n", " \n", " 2022-01-01 00:30:00\n", - " 10480.791787\n", - " 9635.056812\n", - " 9096.222447\n", + " 10609.764556\n", + " 9550.070802\n", + " 9362.149158\n", " \n", " \n", " 2022-01-01 00:45:00\n", - " 10507.228812\n", - " 9552.950661\n", - " 9230.305044\n", + " 10574.014241\n", + " 9397.886258\n", + " 9298.033408\n", " \n", " \n", " 2022-01-01 01:00:00\n", - " 10501.045884\n", - " 9655.662750\n", - " 9292.624845\n", + " 10590.212035\n", + " 9590.004470\n", + " 9347.904429\n", " \n", " \n", " ...\n", @@ -1224,33 +1224,33 @@ " \n", " \n", " 2022-01-01 22:45:00\n", - " 10634.333469\n", - " 9503.854463\n", - " 9186.518621\n", + " 10542.595608\n", + " 9512.758258\n", + " 9173.215749\n", " \n", " \n", " 2022-01-01 23:00:00\n", - " 10652.795359\n", - " 9563.450849\n", - " 9221.243219\n", + " 10400.272830\n", + " 9406.056582\n", + " 9233.211454\n", " \n", " \n", " 2022-01-01 23:15:00\n", - " 10456.577120\n", - " 9555.280069\n", - " 9376.888530\n", + " 10582.826242\n", + " 9706.276834\n", + " 9300.629733\n", " \n", " \n", " 2022-01-01 23:30:00\n", - " 10396.306880\n", - " 9405.658892\n", - " 9145.239732\n", + " 10294.027953\n", + " 9580.638345\n", + " 9047.154720\n", " \n", " \n", " 2022-01-01 23:45:00\n", - " 10571.715516\n", - " 9516.401493\n", - " 9213.450714\n", + " 10497.678725\n", + " 9590.450163\n", + " 9187.435950\n", " \n", " \n", "\n", @@ -1259,17 +1259,17 @@ ], "text/plain": [ " 9 10 11\n", - "2022-01-01 00:00:00 10515.903626 9519.269996 9285.942457\n", - "2022-01-01 00:15:00 10571.251382 9504.850773 9086.425137\n", - "2022-01-01 00:30:00 10480.791787 9635.056812 9096.222447\n", - "2022-01-01 00:45:00 10507.228812 9552.950661 9230.305044\n", - "2022-01-01 01:00:00 10501.045884 9655.662750 9292.624845\n", + "2022-01-01 00:00:00 10606.480633 9449.649580 9205.568138\n", + "2022-01-01 00:15:00 10483.366999 9727.240644 9212.518569\n", + "2022-01-01 00:30:00 10609.764556 9550.070802 9362.149158\n", + "2022-01-01 00:45:00 10574.014241 9397.886258 9298.033408\n", + "2022-01-01 01:00:00 10590.212035 9590.004470 9347.904429\n", "... ... ... ...\n", - "2022-01-01 22:45:00 10634.333469 9503.854463 9186.518621\n", - "2022-01-01 23:00:00 10652.795359 9563.450849 9221.243219\n", - "2022-01-01 23:15:00 10456.577120 9555.280069 9376.888530\n", - "2022-01-01 23:30:00 10396.306880 9405.658892 9145.239732\n", - "2022-01-01 23:45:00 10571.715516 9516.401493 9213.450714\n", + "2022-01-01 22:45:00 10542.595608 9512.758258 9173.215749\n", + "2022-01-01 23:00:00 10400.272830 9406.056582 9233.211454\n", + "2022-01-01 23:15:00 10582.826242 9706.276834 9300.629733\n", + "2022-01-01 23:30:00 10294.027953 9580.638345 9047.154720\n", + "2022-01-01 23:45:00 10497.678725 9590.450163 9187.435950\n", "\n", "[96 rows x 3 columns]" ] @@ -1304,7 +1304,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "dfdcb8fe", "metadata": {}, "outputs": [], @@ -1324,7 +1324,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "582a7323", "metadata": {}, "outputs": [], @@ -1340,7 +1340,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "e74fcd19", "metadata": {}, "outputs": [], @@ -1363,7 +1363,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "d7226899", "metadata": {}, "outputs": [ @@ -1371,9 +1371,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "max power load: [20434193.11194256 10049332.4056693 ]\n", - "min power load: [19743595.69002406 9930151.59743081]\n", - "ratio: [1.0349783 1.01200191]\n" + "max power load: [20318956.68763128 10078884.93969939]\n", + "min power load: [19640245.64115419 9945815.88385369]\n", + "ratio: [1.03455716 1.0133794 ]\n" ] } ], @@ -1402,7 +1402,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "c87c4179", "metadata": { "scrolled": true @@ -1410,7 +1410,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1445,9 +1445,9 @@ "metadata": { "celltoolbar": "Geen", "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.13 (Standalone)", "language": "python", - "name": "python3" + "name": "python3.13" }, "language_info": { "codemirror_mode": { @@ -1459,7 +1459,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.5" + "version": "3.13.2" } }, "nbformat": 4, diff --git a/state-estimation-assignment/State Estimation Assignment.ipynb b/state-estimation-assignment/State Estimation Assignment.ipynb index c9de039..1e98386 100644 --- a/state-estimation-assignment/State Estimation Assignment.ipynb +++ b/state-estimation-assignment/State Estimation Assignment.ipynb @@ -614,9 +614,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3.13 (Standalone)", "language": "python", - "name": "python3" + "name": "python3.13" }, "language_info": { "codemirror_mode": { @@ -628,7 +628,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.5" + "version": "3.13.2" } }, "nbformat": 4,