{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "# Voltage Sag Analysis\n", "\n", "## Introduction\n", "\n", "Voltage sags, also known as voltage dips, are a common power quality issue that can affect electrical equipment performance. They are characterized by a short duration reduction in the RMS voltage, usually lasting from a few milliseconds to a few minutes. In this tutorial, we will explore detection techniques for voltage sags in synchrophasor data using the PredictiveGrid Platform.\n", "\n", "## Table of Contents\n", "\n", "1. [What are Voltage Sags?](#what-are-voltage-sags)\n", "2. [Causes of Voltage Sags](#causes-of-voltage-sags)\n", "4. [Measurement and Detection](#measurement-and-detection)\n", "% 7. [Conclusion](#conclusion)\n", "% 8. [References](#references)\n", "\n", "## What are Voltage Sags?\n", "\n", "From the IEEE Standard on Power Quality `1159-2019`\n", "\n", "> A sag is a decrease in rms voltage to between 0.1 pu and 0.9 pu for durations from 0.5 cycles to 1 min.\n", "\n", "These are a common type of power quality disturbance that can impact the operation of sensitive equipment.\n", "\n", "### Key Characteristics\n", "\n", "- **Duration:** 0.5 cycles to ~1 minute\n", "- **Magnitude:** 10% to 90% of nominal voltage 0.9<->0.1 pu\n", "- **Frequency:** Occurrence varies based on system conditions and external factors\n", "\n", "## Causes of Voltage Sags\n", "\n", "Voltage sags can be caused by various factors, including:\n", "\n", "1. **Faults on the power system:** Short circuits, lightning strikes, and equipment failures can lead to voltage sags.\n", "2. **Large motor startups:** The inrush current required to start large motors can cause a temporary drop in voltage.\n", "4. **Utility grid switching:** Switching operations in the utility grid can cause temporary voltage sags.\n", "\n", "## Measurement and Detection\n", "\n", "To effectively manage voltage sags, it is essential to measure and detect them accurately. Common methods include:\n", "\n", "- **Power quality monitors:** Devices that record voltage levels and capture events like sags and swells.\n", "- **Digital relays:** Protection devices that can detect and respond to voltage sags.\n", "- **RMS Voltage Measurements from PMUs:** Can view the RMS voltage timeseries from synchrophasors/other devices and identify for historial or real time detection\n", "\n", "\n", "## Case 1: Distribution PMUs with community solar (`Ni4ai dataset`)\n", "\n", "> The \u201cSunshine\u201d dataset comes from a distribution system in a sunny climate with significant solar PV generation. The data were collected with micro-PMUs during an early research deployment. There are gaps in the data which correspond to outages as the team was experimenting with different system configurations and wireless communications. When fully connected, each PMU reports data at 120 frames per second on twelve channels: three-phase voltage and current, giving root-mean-square magnitude and phase angle for each.\n", "\n", "> The six sensor locations correspond to three substation buses, one large PV array, and two university buildings. While all six are within the same city, there are three separate distribution circuits, equipped with two sensors each\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "### 1. Connect to the platform and access all voltage streams\n", "\n", "We need to connect to the data timeseries storage platform and then locate the datasets of interest. Note, these systems ran for approximately 18 months at 120Hz so we have a lot of data we can work with!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.077034Z", "start_time": "2024-07-18T17:20:49.990112Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:44.297440Z", "iopub.status.busy": "2025-12-08T22:48:44.297358Z", "iopub.status.idle": "2025-12-08T22:48:44.993569Z", "shell.execute_reply": "2025-12-08T22:48:44.993260Z", "shell.execute_reply.started": "2025-12-08T22:48:44.297430Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import pingthings as pt\n", "import pyarrow as pa\n", "import pyarrow.compute as pc\n", "import seaborn as sns\n", "from tqdm.notebook import tqdm\n", "\n", "sns.set_style(\"darkgrid\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.130119Z", "start_time": "2024-07-18T17:20:50.076579Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:44.994071Z", "iopub.status.busy": "2025-12-08T22:48:44.993929Z", "iopub.status.idle": "2025-12-08T22:48:45.287096Z", "shell.execute_reply": "2025-12-08T22:48:45.286522Z", "shell.execute_reply.started": "2025-12-08T22:48:44.994054Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "conn.info() = {'major_version': 5, 'minor_version': 48, 'build': '5.48.0', 'proxy': {'proxy_endpoints': []}}\n" ] } ], "source": [ "conn = pt.connect()\n", "print(f\"{conn.info() = }\")" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "### Filter for voltage mag streams on the A-phase\n", "\n", "Our data exists under the name prefix `sunhine/PMU[1-6]`" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.176797Z", "start_time": "2024-07-18T17:20:50.133033Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.287642Z", "iopub.status.busy": "2025-12-08T22:48:45.287543Z", "iopub.status.idle": "2025-12-08T22:48:45.337188Z", "shell.execute_reply": "2025-12-08T22:48:45.336856Z", "shell.execute_reply.started": "2025-12-08T22:48:45.287633Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "len(voltage_streams) = 18\n" ] } ], "source": [ "voltage_streams = conn.streams_in_collection(\n", " \"sunshine\", is_collection_prefix=True, tags={\"unit\": \"volts\"}\n", ")\n", "print(f\"{len(voltage_streams) = }\")" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "Lets get a quick description of some of the main attributes and metadata for these data streams (signals)\n", "\n", "For these data streams we just need to check their units, name, collection, and their unique identifier\n", "\n", "Each data stream can also have its own set of user-applied metadata called `annotations` which is a dictionary" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.187671Z", "start_time": "2024-07-18T17:20:50.165180Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.337624Z", "iopub.status.busy": "2025-12-08T22:48:45.337535Z", "iopub.status.idle": "2025-12-08T22:48:45.346527Z", "shell.execute_reply": "2025-12-08T22:48:45.346311Z", "shell.execute_reply.started": "2025-12-08T22:48:45.337614Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/html": [ "
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uuidcollectionnameunit
1035bdb8dc-bf18-4523-85ca-8ebe384bd9b5sunshine/PMU1L1MAGvolts
3d4cfa9a6-e11a-4370-9eda-16e80773ce8csunshine/PMU1L2MAGvolts
11b2936212-253e-488a-87f6-a9927042031fsunshine/PMU1L3MAGvolts
5e290a69d-1e52-4411-bccd-da7c3f39531csunshine/PMU2L1MAGvolts
16ef43c96-9429-48db-9d37-bffd981b4a24sunshine/PMU2L2MAGvolts
8b4920286-9aaa-4ca0-82ac-937e3ff7d8e8sunshine/PMU2L3MAGvolts
20295f80f-6776-4384-b563-4582f7256600sunshine/PMU3L1MAGvolts
1338d62795-6341-4069-96d3-fe74bffcac67sunshine/PMU3L2MAGvolts
1637539589-88aa-48b7-8cb4-1ea2f32c9e8dsunshine/PMU3L3MAGvolts
1208060a62-04c0-4597-8d2f-7df58e461ba2sunshine/PMU4L1MAGvolts
908aac678-a2f5-4a9c-9c18-c569cd414368sunshine/PMU4L2MAGvolts
155031918c-346f-4488-9755-b3917153e607sunshine/PMU4L3MAGvolts
4edb36769-f56f-47c5-bbda-a177c424cc4fsunshine/PMU5L1MAGvolts
14b4de2e84-7816-4dc7-9702-f1c210586e1csunshine/PMU5L2MAGvolts
6a60aa7aa-9ad1-425b-bb2e-74b42a2cd3e0sunshine/PMU5L3MAGvolts
0d3e9ed52-6db9-4b98-bfda-e1b509148e47sunshine/PMU6L1MAGvolts
7d60fc469-a6da-4c98-8763-fd833293d955sunshine/PMU6L2MAGvolts
174833b5e0-ef30-40ed-8db8-352e79d38c28sunshine/PMU6L3MAGvolts
\n", "
" ], "text/plain": [ " uuid collection name unit\n", "10 35bdb8dc-bf18-4523-85ca-8ebe384bd9b5 sunshine/PMU1 L1MAG volts\n", "3 d4cfa9a6-e11a-4370-9eda-16e80773ce8c sunshine/PMU1 L2MAG volts\n", "11 b2936212-253e-488a-87f6-a9927042031f sunshine/PMU1 L3MAG volts\n", "5 e290a69d-1e52-4411-bccd-da7c3f39531c sunshine/PMU2 L1MAG volts\n", "1 6ef43c96-9429-48db-9d37-bffd981b4a24 sunshine/PMU2 L2MAG volts\n", "8 b4920286-9aaa-4ca0-82ac-937e3ff7d8e8 sunshine/PMU2 L3MAG volts\n", "2 0295f80f-6776-4384-b563-4582f7256600 sunshine/PMU3 L1MAG volts\n", "13 38d62795-6341-4069-96d3-fe74bffcac67 sunshine/PMU3 L2MAG volts\n", "16 37539589-88aa-48b7-8cb4-1ea2f32c9e8d sunshine/PMU3 L3MAG volts\n", "12 08060a62-04c0-4597-8d2f-7df58e461ba2 sunshine/PMU4 L1MAG volts\n", "9 08aac678-a2f5-4a9c-9c18-c569cd414368 sunshine/PMU4 L2MAG volts\n", "15 5031918c-346f-4488-9755-b3917153e607 sunshine/PMU4 L3MAG volts\n", "4 edb36769-f56f-47c5-bbda-a177c424cc4f sunshine/PMU5 L1MAG volts\n", "14 b4de2e84-7816-4dc7-9702-f1c210586e1c sunshine/PMU5 L2MAG volts\n", "6 a60aa7aa-9ad1-425b-bb2e-74b42a2cd3e0 sunshine/PMU5 L3MAG volts\n", "0 d3e9ed52-6db9-4b98-bfda-e1b509148e47 sunshine/PMU6 L1MAG volts\n", "7 d60fc469-a6da-4c98-8763-fd833293d955 sunshine/PMU6 L2MAG volts\n", "17 4833b5e0-ef30-40ed-8db8-352e79d38c28 sunshine/PMU6 L3MAG volts" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "streams_summary = [\n", " {\n", " \"uuid\": str(s.uuid),\n", " \"collection\": s.collection,\n", " \"name\": s.name,\n", " \"unit\": s.tags()[\"unit\"],\n", " }\n", " for s in voltage_streams\n", "]\n", "streams_summary_df = pd.DataFrame.from_dict(streams_summary, dtype=\"string\").sort_values(\n", " by=[\"collection\", \"name\"]\n", ")\n", "streams_summary_df" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "We see that for each PMU (_e.g._ `sunshine/PMU1`), the voltage streams have a name `L{PHASE}MAG` where `1` is `A`, `2` is `B`..." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.189112Z", "start_time": "2024-07-18T17:20:50.187960Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.346921Z", "iopub.status.busy": "2025-12-08T22:48:45.346837Z", "iopub.status.idle": "2025-12-08T22:48:45.349728Z", "shell.execute_reply": "2025-12-08T22:48:45.349462Z", "shell.execute_reply.started": "2025-12-08T22:48:45.346911Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "matches = [ # find the correct stream\n", " stream\n", " for stream in voltage_streams\n", " if stream.collection == \"sunshine/PMU1\" and stream.name == \"L1MAG\"\n", "]\n", "assert len(matches) == 1 # make sure there's only one\n", "reference_stream = matches[0]\n", "reference_stream" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.196503Z", "start_time": "2024-07-18T17:20:50.195511Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.350805Z", "iopub.status.busy": "2025-12-08T22:48:45.350634Z", "iopub.status.idle": "2025-12-08T22:48:45.352721Z", "shell.execute_reply": "2025-12-08T22:48:45.352346Z", "shell.execute_reply.started": "2025-12-08T22:48:45.350793Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "len(a_phase_streams) = 5\n" ] } ], "source": [ "# all A-phase streams\n", "a_phase_streams = [s for s in voltage_streams if s.name == \"L1MAG\" and \"PMU3\" not in s.collection]\n", "print(f\"{len(a_phase_streams) = }\")" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "### Timeseries data stored in the platform\n", "\n", "In our database, the internal datastructure to store the timeseries is a tree that is indexed on time, the further down the tree you go, the more granular data you encounter.\n", "These data are also versioned, so you can pin a computation to a specific version for reproducible queries.\n", "\n", "At each level of the tree, we pre-compute and update statistical summary information of the timeseries as data is inserted. If you want to look at all 18 months of the timeseries data and its general trends, you can do so with very little computational and data access penalties.\n", "\n", "In addition, this also affords us the following benefits:\n", "\n", "1. We can backfill data at any point, out of order insertions is as fast as regular insertions\n", "2. a read request for data between `t1` and `t2` is guaranteed to be in sorted order, no additional post processing steps needed for out of order data\n", "3. Reading multiple streams in parallel and combining the results is a very scalable action since each stream is its own tree\n", "4. We can leverage tree search algorithms and our pre-computed statistical summaries to effictively walk the tree to find our events of interest\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.255916Z", "start_time": "2024-07-18T17:20:50.206579Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.353295Z", "iopub.status.busy": "2025-12-08T22:48:45.353047Z", "iopub.status.idle": "2025-12-08T22:48:45.357284Z", "shell.execute_reply": "2025-12-08T22:48:45.357023Z", "shell.execute_reply.started": "2025-12-08T22:48:45.353283Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "def find_sags(\n", " s: pt.timeseries.Stream,\n", " normalization_factor: float = 1.0,\n", " tree_width: int = 52,\n", " threshold_below_pu: float = 0.9,\n", " start: int = pt.timeseries.constants.MINIMUM_TIME,\n", " end: int = pt.timeseries.constants.MAXIMUM_TIME,\n", " stop_tree_width: int = 30,\n", " version: int = 0,\n", ") -> list[pa.Table] | None:\n", " \"\"\"Recursively walk the tree to find event sags that fit our per-unit threshold.\"\"\"\n", " results = []\n", "\n", " # print(f\"Searching between {pd.Timestamp(start)} and {pd.Timestamp(end)} at a width of {pt.timeseries.constants.PW[tree_width]}\")\n", " windows = s.windowed_values(\n", " start=start, end=end, width=pt.timeseries.constants.PW[tree_width], version=version\n", " )\n", "\n", " min_in_pu = pc.divide(windows[\"min\"], normalization_factor)\n", " mask_below_thresh = pc.less_equal(min_in_pu, threshold_below_pu)\n", " mask_min_is_less_than_max = pc.less(windows[\"min\"], windows[\"max\"])\n", " mask_all = pc.and_(mask_below_thresh, mask_min_is_less_than_max)\n", " times = pc.filter(windows[\"time\"], mask_all)\n", "\n", " for valid_time in times:\n", " wstart = valid_time.as_py().value\n", " wend = wstart + int(2**tree_width)\n", "\n", " # our stop condition\n", " if tree_width <= stop_tree_width:\n", " raw_points = s.raw_values(\n", " wstart - (2**stop_tree_width), wend + (2**stop_tree_width), version\n", " )\n", " tmp = pc.divide(raw_points[\"value\"], normalization_factor)\n", " tmp_tab = pa.table([raw_points[\"time\"], tmp], names=[\"time\", \"value\"])\n", " results.append(tmp_tab)\n", " else:\n", " sub_results = find_sags(\n", " s,\n", " normalization_factor,\n", " tree_width=tree_width - 1,\n", " threshold_below_pu=threshold_below_pu,\n", " start=wstart,\n", " end=wend,\n", " stop_tree_width=stop_tree_width,\n", " version=version,\n", " )\n", " if sub_results:\n", " results.extend(sub_results)\n", "\n", " return results" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.293609Z", "start_time": "2024-07-18T17:20:50.212117Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.357821Z", "iopub.status.busy": "2025-12-08T22:48:45.357652Z", "iopub.status.idle": "2025-12-08T22:48:45.387046Z", "shell.execute_reply": "2025-12-08T22:48:45.386749Z", "shell.execute_reply.started": "2025-12-08T22:48:45.357810Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pt.utils.ns_to_datetime(reference_stream.earliest().time) = datetime.datetime(2015, 10, 1, 16, 8, 24, 8333, tzinfo=datetime.timezone.utc)\n", "pt.utils.ns_to_datetime(reference_stream.latest().time) = datetime.datetime(2017, 4, 15, 1, 37, 11, 333333, tzinfo=datetime.timezone.utc)\n" ] } ], "source": [ "print(f\"{pt.utils.ns_to_datetime(reference_stream.earliest().time) = }\")\n", "print(f\"{pt.utils.ns_to_datetime(reference_stream.latest().time) = }\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When choosing a resolution, note that these scale as 2\\*\\*(point width) ns:\n", "\n", "| point width | window size |\n", "| --- | --- |\n", "| 52 | 1.71 months |\n", "| 49 | 6.52 days |\n", "| 36 | 1.15 minutes |\n", "| 30 | 1.07 seconds |\n", "\n", "A full table of point widths can be found [here](pingthings.timeseries.constants.PW)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "Lets walk through the year of 2017, but first lets plot the min, mean, and max of that using a pointwidth of 49" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.339926Z", "start_time": "2024-07-18T17:20:50.256189Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:45.388030Z", "iopub.status.busy": "2025-12-08T22:48:45.387671Z", "iopub.status.idle": "2025-12-08T22:48:46.141788Z", "shell.execute_reply": "2025-12-08T22:48:46.141245Z", "shell.execute_reply.started": "2025-12-08T22:48:45.388007Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/html": [ "
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timeminmeanmaxcountstddev
02015-12-28 06:42:59.920142336+00:006843.3491217168.2836917262.5214846755399436.483932
12016-01-03 19:05:29.873563648+00:006730.7304697146.2841807236.1855472357641630.368816
22016-02-11 21:20:29.594091520+00:007031.1293957154.5898447244.5439451456554533.561325
32016-02-18 09:42:59.547512832+00:00771.5824587151.5756847298.7724616755399532.155090
42016-02-24 22:05:29.500934144+00:006841.3559577156.9360357295.4189456755399436.042336
52016-03-02 10:27:59.454355456+00:006657.9794927154.2651377264.3393556755399436.071171
62016-03-08 22:50:29.407776768+00:006434.2832037156.9873057256.9838876755399537.595371
72016-03-15 11:12:59.361198080+00:004686.4409187150.5693367305.9785166755427737.196758
82016-03-21 23:35:29.314619392+00:006950.4028327154.3896487247.0180666755399537.552750
92016-03-28 11:57:59.268040704+00:006895.0644537162.2392587260.0961916755399435.820419
102016-04-04 00:20:29.221462016+00:007017.0283207161.4560557301.8852546755399435.994030
112016-04-10 12:42:59.174883328+00:006825.3710947152.1098637284.2006846692911834.552238
122016-04-17 01:05:29.128304640+00:007006.6586917154.4677737288.6728526755463338.513111
132016-04-23 13:27:59.081725952+00:006946.4614267162.5957037258.6215826755430530.351898
142016-04-30 01:50:29.035147264+00:006931.1533207164.8666997298.0112306728721636.523064
152016-05-06 14:12:58.988568576+00:006580.9541027164.0405277300.8623056741738339.368473
162016-05-13 02:35:28.941989888+00:006904.0771487153.4355477280.8383796743325034.433182
172016-05-19 14:57:58.895411200+00:006796.8339847160.8149417257.7065436748112332.911831
182016-05-26 03:20:28.848832512+00:006869.3134777161.8725597264.3911136746735534.305164
192016-06-01 15:42:58.802253824+00:007044.2680667150.8549807286.5512701243550438.305382
202016-06-14 16:27:58.709096448+00:006987.6093757187.9868167319.545898426583933.658150
212016-06-21 04:50:28.662517760+00:007016.4223637156.4658207281.1025396725832742.842468
222016-06-27 17:12:58.615939072+00:007019.6757817158.3715827325.3715826741863039.184334
232016-07-04 05:35:28.569360384+00:006964.9145517161.4755867293.4907236755425737.822296
242016-07-10 17:57:58.522781696+00:006939.0991217167.4165047282.6704106747203837.911224
252016-07-17 06:20:28.476203008+00:006710.9169927165.0175787294.7631846755399440.225117
262016-07-23 18:42:58.429624320+00:006905.5039067174.1479497290.3344736755424538.372890
272016-07-30 07:05:28.383045632+00:005558.5742197163.2094737294.1577156723071539.522358
282016-08-05 19:27:58.336466944+00:006865.9082037163.1518557277.5302736700943437.245747
292016-08-12 07:50:28.289888256+00:005780.0566417167.1323247307.2128916704171540.181225
302016-08-18 20:12:58.243309568+00:006915.6538097161.2631847284.0146486723599444.174938
312016-08-25 08:35:28.196730880+00:006905.4438487153.1772467277.5117196726191542.096008
322016-08-31 20:57:58.150152192+00:006720.5141607165.1445317279.9887706705599439.953091
332016-09-07 09:20:28.103573504+00:006635.2832037163.2919927290.2006846737315439.882545
342016-09-13 21:42:58.056994816+00:006899.2744147161.3471687290.3359386729227540.514523
352016-09-20 10:05:28.010416128+00:006392.5209967157.8022467318.2285166726672339.112907
362016-09-26 22:27:57.963837440+00:007022.3159187165.6640627300.7250986724045141.436214
372016-10-03 10:50:27.917258752+00:006944.9741217160.4365237290.1015626755399440.870972
382016-10-09 23:12:57.870680064+00:005955.3212897151.0429697268.4375006755399441.210709
392016-10-16 11:35:27.824101376+00:006901.3242197157.2871097276.0219735361410233.036419
402016-10-22 23:57:57.777522688+00:005097.3129887148.0917977255.7197276612504435.632080
412016-10-29 12:20:27.730944+00:006889.3930667162.9628917266.5205086755399532.416542
422016-11-05 00:42:57.684365312+00:007027.0673837156.4062507283.4536136755411640.484756
432016-11-11 13:05:27.637786624+00:006561.6850597160.2475597270.7373056755399434.567955
442016-11-18 01:27:57.591207936+00:007022.3168957155.9619147247.2690436755399535.379372
452016-11-24 13:50:27.544629248+00:006753.3442387153.8657237258.3769536755399429.264280
462016-12-01 02:12:57.498050560+00:006591.2348637164.7768557281.7475596755399534.874657
472016-12-07 14:35:27.451471872+00:006891.4184577160.8164067265.0493166755399432.994476
482016-12-14 02:57:57.404893184+00:007022.7192387156.7114267261.2080086755399434.202499
492016-12-20 15:20:27.358314496+00:006501.1142587162.7568367282.7773446755399537.336090
\n", "
" ], "text/plain": [ " time min mean max \\\n", "0 2015-12-28 06:42:59.920142336+00:00 6843.349121 7168.283691 7262.521484 \n", "1 2016-01-03 19:05:29.873563648+00:00 6730.730469 7146.284180 7236.185547 \n", "2 2016-02-11 21:20:29.594091520+00:00 7031.129395 7154.589844 7244.543945 \n", "3 2016-02-18 09:42:59.547512832+00:00 771.582458 7151.575684 7298.772461 \n", "4 2016-02-24 22:05:29.500934144+00:00 6841.355957 7156.936035 7295.418945 \n", "5 2016-03-02 10:27:59.454355456+00:00 6657.979492 7154.265137 7264.339355 \n", "6 2016-03-08 22:50:29.407776768+00:00 6434.283203 7156.987305 7256.983887 \n", "7 2016-03-15 11:12:59.361198080+00:00 4686.440918 7150.569336 7305.978516 \n", "8 2016-03-21 23:35:29.314619392+00:00 6950.402832 7154.389648 7247.018066 \n", "9 2016-03-28 11:57:59.268040704+00:00 6895.064453 7162.239258 7260.096191 \n", "10 2016-04-04 00:20:29.221462016+00:00 7017.028320 7161.456055 7301.885254 \n", "11 2016-04-10 12:42:59.174883328+00:00 6825.371094 7152.109863 7284.200684 \n", "12 2016-04-17 01:05:29.128304640+00:00 7006.658691 7154.467773 7288.672852 \n", "13 2016-04-23 13:27:59.081725952+00:00 6946.461426 7162.595703 7258.621582 \n", "14 2016-04-30 01:50:29.035147264+00:00 6931.153320 7164.866699 7298.011230 \n", "15 2016-05-06 14:12:58.988568576+00:00 6580.954102 7164.040527 7300.862305 \n", "16 2016-05-13 02:35:28.941989888+00:00 6904.077148 7153.435547 7280.838379 \n", "17 2016-05-19 14:57:58.895411200+00:00 6796.833984 7160.814941 7257.706543 \n", "18 2016-05-26 03:20:28.848832512+00:00 6869.313477 7161.872559 7264.391113 \n", "19 2016-06-01 15:42:58.802253824+00:00 7044.268066 7150.854980 7286.551270 \n", "20 2016-06-14 16:27:58.709096448+00:00 6987.609375 7187.986816 7319.545898 \n", "21 2016-06-21 04:50:28.662517760+00:00 7016.422363 7156.465820 7281.102539 \n", "22 2016-06-27 17:12:58.615939072+00:00 7019.675781 7158.371582 7325.371582 \n", "23 2016-07-04 05:35:28.569360384+00:00 6964.914551 7161.475586 7293.490723 \n", "24 2016-07-10 17:57:58.522781696+00:00 6939.099121 7167.416504 7282.670410 \n", "25 2016-07-17 06:20:28.476203008+00:00 6710.916992 7165.017578 7294.763184 \n", "26 2016-07-23 18:42:58.429624320+00:00 6905.503906 7174.147949 7290.334473 \n", "27 2016-07-30 07:05:28.383045632+00:00 5558.574219 7163.209473 7294.157715 \n", "28 2016-08-05 19:27:58.336466944+00:00 6865.908203 7163.151855 7277.530273 \n", "29 2016-08-12 07:50:28.289888256+00:00 5780.056641 7167.132324 7307.212891 \n", "30 2016-08-18 20:12:58.243309568+00:00 6915.653809 7161.263184 7284.014648 \n", "31 2016-08-25 08:35:28.196730880+00:00 6905.443848 7153.177246 7277.511719 \n", "32 2016-08-31 20:57:58.150152192+00:00 6720.514160 7165.144531 7279.988770 \n", "33 2016-09-07 09:20:28.103573504+00:00 6635.283203 7163.291992 7290.200684 \n", "34 2016-09-13 21:42:58.056994816+00:00 6899.274414 7161.347168 7290.335938 \n", "35 2016-09-20 10:05:28.010416128+00:00 6392.520996 7157.802246 7318.228516 \n", "36 2016-09-26 22:27:57.963837440+00:00 7022.315918 7165.664062 7300.725098 \n", "37 2016-10-03 10:50:27.917258752+00:00 6944.974121 7160.436523 7290.101562 \n", "38 2016-10-09 23:12:57.870680064+00:00 5955.321289 7151.042969 7268.437500 \n", "39 2016-10-16 11:35:27.824101376+00:00 6901.324219 7157.287109 7276.021973 \n", "40 2016-10-22 23:57:57.777522688+00:00 5097.312988 7148.091797 7255.719727 \n", "41 2016-10-29 12:20:27.730944+00:00 6889.393066 7162.962891 7266.520508 \n", "42 2016-11-05 00:42:57.684365312+00:00 7027.067383 7156.406250 7283.453613 \n", "43 2016-11-11 13:05:27.637786624+00:00 6561.685059 7160.247559 7270.737305 \n", "44 2016-11-18 01:27:57.591207936+00:00 7022.316895 7155.961914 7247.269043 \n", "45 2016-11-24 13:50:27.544629248+00:00 6753.344238 7153.865723 7258.376953 \n", "46 2016-12-01 02:12:57.498050560+00:00 6591.234863 7164.776855 7281.747559 \n", "47 2016-12-07 14:35:27.451471872+00:00 6891.418457 7160.816406 7265.049316 \n", "48 2016-12-14 02:57:57.404893184+00:00 7022.719238 7156.711426 7261.208008 \n", "49 2016-12-20 15:20:27.358314496+00:00 6501.114258 7162.756836 7282.777344 \n", "\n", " count stddev \n", "0 67553994 36.483932 \n", "1 23576416 30.368816 \n", "2 14565545 33.561325 \n", "3 67553995 32.155090 \n", "4 67553994 36.042336 \n", "5 67553994 36.071171 \n", "6 67553995 37.595371 \n", "7 67554277 37.196758 \n", "8 67553995 37.552750 \n", "9 67553994 35.820419 \n", "10 67553994 35.994030 \n", "11 66929118 34.552238 \n", "12 67554633 38.513111 \n", "13 67554305 30.351898 \n", "14 67287216 36.523064 \n", "15 67417383 39.368473 \n", "16 67433250 34.433182 \n", "17 67481123 32.911831 \n", "18 67467355 34.305164 \n", "19 12435504 38.305382 \n", "20 4265839 33.658150 \n", "21 67258327 42.842468 \n", "22 67418630 39.184334 \n", "23 67554257 37.822296 \n", "24 67472038 37.911224 \n", "25 67553994 40.225117 \n", "26 67554245 38.372890 \n", "27 67230715 39.522358 \n", "28 67009434 37.245747 \n", "29 67041715 40.181225 \n", "30 67235994 44.174938 \n", "31 67261915 42.096008 \n", "32 67055994 39.953091 \n", "33 67373154 39.882545 \n", "34 67292275 40.514523 \n", "35 67266723 39.112907 \n", "36 67240451 41.436214 \n", "37 67553994 40.870972 \n", "38 67553994 41.210709 \n", "39 53614102 33.036419 \n", "40 66125044 35.632080 \n", "41 67553995 32.416542 \n", "42 67554116 40.484756 \n", "43 67553994 34.567955 \n", "44 67553995 35.379372 \n", "45 67553994 29.264280 \n", "46 67553995 34.874657 \n", "47 67553994 32.994476 \n", "48 67553994 34.202499 \n", "49 67553995 37.336090 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "start = pt.utils.to_nanoseconds(\"2016-01-01\")\n", "end = pt.utils.to_nanoseconds(\"2017-01-01\")\n", "tree_width = 49\n", "data = reference_stream.windowed_values(\n", " start, end, pt.timeseries.constants.PW[tree_width]\n", ").to_pandas()\n", "display(data)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "Each of these summary points we read are based on approximately 67,553,994 raw measurements!" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:50.340169Z", "start_time": "2024-07-18T17:20:50.298428Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:46.142733Z", "iopub.status.busy": "2025-12-08T22:48:46.142519Z", "iopub.status.idle": "2025-12-08T22:48:46.149003Z", "shell.execute_reply": "2025-12-08T22:48:46.148742Z", "shell.execute_reply.started": "2025-12-08T22:48:46.142712Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/html": [ "
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timeminmeanmaxcountstddev
32016-02-18 09:42:59.547512832+00:00771.5824587151.5756847298.7724616755399532.155090
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" ], "text/plain": [ " time min mean max \\\n", "3 2016-02-18 09:42:59.547512832+00:00 771.582458 7151.575684 7298.772461 \n", "6 2016-03-08 22:50:29.407776768+00:00 6434.283203 7156.987305 7256.983887 \n", "7 2016-03-15 11:12:59.361198080+00:00 4686.440918 7150.569336 7305.978516 \n", "27 2016-07-30 07:05:28.383045632+00:00 5558.574219 7163.209473 7294.157715 \n", "29 2016-08-12 07:50:28.289888256+00:00 5780.056641 7167.132324 7307.212891 \n", "35 2016-09-20 10:05:28.010416128+00:00 6392.520996 7157.802246 7318.228516 \n", "38 2016-10-09 23:12:57.870680064+00:00 5955.321289 7151.042969 7268.437500 \n", "40 2016-10-22 23:57:57.777522688+00:00 5097.312988 7148.091797 7255.719727 \n", "\n", " count stddev \n", "3 67553995 32.155090 \n", "6 67553995 37.595371 \n", "7 67554277 37.196758 \n", "27 67230715 39.522358 \n", "29 67041715 40.181225 \n", "35 67266723 39.112907 \n", "38 67553994 41.210709 \n", "40 66125044 35.632080 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[data[\"min\"] / data[\"mean\"].mean() < 0.9]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lets walk through the year of data! And use a stopping window size of 1.07 seconds" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:52.195943Z", "start_time": "2024-07-18T17:20:50.302448Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:46.149419Z", "iopub.status.busy": "2025-12-08T22:48:46.149337Z", "iopub.status.idle": "2025-12-08T22:48:55.018620Z", "shell.execute_reply": "2025-12-08T22:48:55.018236Z", "shell.execute_reply.started": "2025-12-08T22:48:46.149410Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "norm_factor = data[\"mean\"].mean()\n", "sags = find_sags(\n", " s=reference_stream,\n", " start=start,\n", " end=end,\n", " normalization_factor=norm_factor,\n", " stop_tree_width=30,\n", " tree_width=52,\n", " version=0,\n", " threshold_below_pu=0.90,\n", ")" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:52.212131Z", "start_time": "2024-07-18T17:20:52.199559Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:55.019061Z", "iopub.status.busy": "2025-12-08T22:48:55.018973Z", "iopub.status.idle": "2025-12-08T22:48:55.021580Z", "shell.execute_reply": "2025-12-08T22:48:55.021251Z", "shell.execute_reply.started": "2025-12-08T22:48:55.019051Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 1 sag! between 2016-02-18 09:54:12.791666+00:00 and 2016-02-18 09:54:15.999999+00:00\n", "Found 2 sag! between 2016-02-18 09:54:13.858333+00:00 and 2016-02-18 09:54:17.074999+00:00\n", "Found 3 sag! between 2016-03-11 23:37:22.816666+00:00 and 2016-03-11 23:37:26.033333+00:00\n", "Found 4 sag! between 2016-03-15 22:16:57.333333+00:00 and 2016-03-15 22:17:00.549999+00:00\n", "Found 5 sag! between 2016-03-15 23:26:22.374999+00:00 and 2016-03-15 23:26:25.591666+00:00\n", "Found 6 sag! between 2016-08-02 23:05:02.624999+00:00 and 2016-08-02 23:05:05.841666+00:00\n", "Found 7 sag! between 2016-08-02 23:05:03.699999+00:00 and 2016-08-02 23:05:06.916666+00:00\n", "Found 8 sag! between 2016-08-16 18:45:06.758333+00:00 and 2016-08-16 18:45:09.966666+00:00\n", "Found 9 sag! between 2016-09-26 13:11:10.641666+00:00 and 2016-09-26 13:11:13.849999+00:00\n", "Found 10 sag! between 2016-10-14 11:03:59.699999+00:00 and 2016-10-14 11:04:02.908333+00:00\n", "Found 11 sag! between 2016-10-24 04:58:10.583333+00:00 and 2016-10-24 04:58:13.799999+00:00\n", "Found 12 sag! between 2016-10-24 13:31:51.266666+00:00 and 2016-10-24 13:31:54.483333+00:00\n", "Found 13 sag! between 2016-10-24 13:49:17.091666+00:00 and 2016-10-24 13:49:20.308333+00:00\n", "Found 14 sag! between 2016-10-24 14:05:23.458333+00:00 and 2016-10-24 14:05:26.674999+00:00\n", "Found 15 sag! between 2016-10-24 19:13:00.008333+00:00 and 2016-10-24 19:13:03.224999+00:00\n", "Found 16 sag! between 2016-10-24 22:45:59.683333+00:00 and 2016-10-24 22:46:02.899999+00:00\n" ] } ], "source": [ "counter = 0\n", "for result in sags:\n", " counter += 1\n", " print(f\"Found {counter} sag! between {result['time'][0]} and {result['time'][-1]}\")" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:52.540369Z", "start_time": "2024-07-18T17:20:52.211765Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:55.022018Z", "iopub.status.busy": "2025-12-08T22:48:55.021932Z", "iopub.status.idle": "2025-12-08T22:48:55.104458Z", "shell.execute_reply": "2025-12-08T22:48:55.104242Z", "shell.execute_reply.started": "2025-12-08T22:48:55.022005Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "result.to_pandas().set_index(\"time\").plot()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:20:52.549111Z", "start_time": "2024-07-18T17:20:52.539784Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:55.104932Z", "iopub.status.busy": "2025-12-08T22:48:55.104814Z", "iopub.status.idle": "2025-12-08T22:48:55.107973Z", "shell.execute_reply": "2025-12-08T22:48:55.107742Z", "shell.execute_reply.started": "2025-12-08T22:48:55.104921Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "text/plain": [ "np.float32(0.89475393)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result.to_pandas()[\"value\"].min()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "Lets do this for all A phase voltage streams!" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:21:02.292905Z", "start_time": "2024-07-18T17:20:52.547752Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:48:55.108411Z", "iopub.status.busy": "2025-12-08T22:48:55.108319Z", "iopub.status.idle": "2025-12-08T22:49:43.569830Z", "shell.execute_reply": "2025-12-08T22:49:43.569362Z", "shell.execute_reply.started": "2025-12-08T22:48:55.108402Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "08264c898c1a4000beb2b6ff022e058c", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/5 [00:00" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "For sunshine/PMU5 A phase voltage mag, 50 sags found!\n" ] }, { "data": { "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "For sunshine/PMU2 A phase voltage mag, 2 sags found!\n" ] }, { "data": { "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "For sunshine/PMU1 A phase voltage mag, 16 sags found!\n" ] }, { "data": { "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "For sunshine/PMU4 A phase voltage mag, 24 sags found!\n" ] }, { "data": { "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", 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zWC+372IL+rP7uN2zPcyXrq9R4bIeu37XvgVt+NPfQ7PUBEmKd0pRifs49BjMbA/zHNwf6Ho5PSVBWqclmtde/x/1vjYOh5nZoKFC2ye0gVB/BzrcoL87PUz9/1ofT49TKwB5RaVmjY8ffyo0M0asJkX9/8Eaf9djs34XFVmviXt66ontepz6uultTtbLEQqH57HM79Dz/6gVgLw/e5770aJSM/tEj1d7RfRLew30992xRap5TUZ1aym9z2oidvrHjmyZtuqrSlOR9bgn9TtLfjxSKNv350tWo0QZ3CHTHF/Fios+Xw2CwOmCSk0YvPDPb2XRv3/0LsAUiH4g6IeAfjj70rUClBUMrPBiAkaFN3Tf+9E3UO1Qr26RIW3w0zcp80FifaDoh4gnUZSfpIu94geMflAXVze4DthM+zk03Fgf3Na/D+3pMBUaz+Jn+uFsrQ6rzKJtWonwBMLapsezcGxPMw3WDlqJuuKVz8x04HObNTCvkS5IpzOHJvc/Sy44I82W4wDChUqNjXZmH6020Ci92go0+ganIUHL5/rXXE343s/JhGuRKuvDwZd+eOhf+RqazOJMnuqUw1PRcH93/2ytsqlO7O/eouVt64PFu2JmQqypuCR4qiFW06FO99QPJn2D1n3N9ERXmSTEuis0ep3+xazPWysVeshaUdD70Qina0Lok7EqM1ZQs6oIWkHQ43N/uY/Xd7hDg6fuo4+p4c5qitTtWkHSha60QqSVCvO78jwvq6qREh9r/uo/4pkuaf0/o8em1RV9XvocLNZjW6+dX8WgQgXBWWG7PlZmA/cKpjpzRe9bj0MX09LX1KrsWKuh6nPS2QwHC4pMtahFw0RvpcRV5n7e2kehh5SeEu+ZIeOeJqr0vrXyqNdrcGiYECtZjRNNFSCjQYL3GDVIWK+772Jg+vtV5rUtda/uqq+vdTv9negxmOs8r1vTBvHeBcCsKav6/4pvZbEivX+9fVJcTKXhLe//ixUqYCW+l83P7tfL+jehr2lKgtNcp8eh1Vnrd6OVkHnrvzP9Kk9/tFOeGd5J7PD/bdprAk27piny2q+6m2PRKp3+O6H/BdGMRuEweOaqTmbcWf9qVFa1Jc7TH6BvtvpGrx+0TRskmP30DVXfZPR21oeovsfqm7w3CHi+x+gghyc06DCHfmjrG6iu+miGh8wHnzs5WGHC5Vl0So8l1jN84B4ScfgFC2v/mAq312vMMFKZSKnnA02fk36I6DCPGXqhORBhFhvjHr6pqVO9jXvITQIMK7ofO9y6ZjWSc5ulyoQlm01Drh30fWXJph/Nzzf2OsM7DK3BGoh2/F8eBhostG+hyhfZ6Qg4Bc6qStREqsSaYHQqrHONAIgcrR4pO4a51KuffmequWemJcmAthm2PCZQVxBqAKAWWQuRBWqIDqePd2aboa6vD7krQvf8z9lRM4sLOFWEGgCoRdbwT00qNTrUu/qrg7LvpyI5/4zG0qVlw0r7aP/V/rwi08e1eNNeee3T77zXDTvPPZsJqG8INQBQm2+y2lXvaVI+VR/vzJGHV/3X/Nxgo1Pev+Uiv7Mif59bKLe8tbnSySCvP7+VjOjawjRoA/URqykBQB2r1Kz99rD3Z50h+Ynnss7U2rYvTx549z8m0PguiDfhkjPN+jOtGifRxI96i0oNANQiXSDSd1bkyaZUa3D5dE+u+VlPS/DVwQL5y5cHpXOLVHnigx3e63QW5YKxPc008kMFRXJ+68b8HlHvEWoAwIbhJ6VLMcTr/PFq7MktNGsL6bIJDw5qKzcs2CTrdh2WO5cdk92HC832/udkyA0XtvbOumxj4xmagagafvrXv/4lt956q/Tp00fat28vf/3rX096mw0bNsiIESOkc+fOcumll8qiRYsq7bN69WoZOnSodOrUyXz/8MMPK+2zYMECGTBggLkfvb+NGzfW9PABwFa+pyvRU6eczAZPJaZbViM5r3mq9DmriRm60kCj1ZlFY3vKE78815wZG0CIoebYsWMmzDz88MOntP/3338vEyZMkJ49e8ry5ctNIHriiSdMiLFs2rRJ7rnnHrnyyivlnXfeMd/vvvtu2bx5s3efVatWyfTp0+W2224z96P3N378eNm7d29NnwIARCTUaKXmZHYcOmq+63CT+t2Q9tKmSZJZPHPaL9rJmVRlgPANP/Xr1898narFixdLixYtZOrUqeby2WefLVu3bpXXXntNBg8ebLa9/vrrcskll8gtt9zi3UerO7r9mWeeMdvmz58vI0eOlFGjRpnLen9r1qwxVZ977723pk8DAGzhu1bMqTQLf3+k0Hy3woueQuLN63tK9tEiyWqUVItHCpz+ar2n5osvvpDevXv7bevbt68sW7ZMSkpKJC4uzuxz4403VtpHQ40qLi6W7du3m4qPL71frfLUFKv7A7CLOQ2DdXb4cvf5s6rzXa4VanQWk3ubnltMZzUB9ZXDUUdCTXZ2tmRk+C/VnZ6eLqWlpZKbmyuZmZlmH91WcZ9Dhw6Zn3U/l8tVaR+9X2ufmkhPd5d1AcCuVYVLy1yS2jBZMtKrbuo9WlTqXXum29lNpTGnOgHq3uyniic+1CmLFbcH2qfitlPZ51Tk5OSbMysDgB08Z0qQgzn5klx+4kzsFVknvdRVgkuPFUn2sSJ+QYC4KzWnUpCo9VATqJpy+PBhiY2NlcaNG3v30WpNxX2sCk9aWpo4nc5K++Tk5FSqAp0KDTSEGgD2rlXjkhJXebXvPXsOu4eezmiczHsUUBdXFO7WrZusW7fOb5s2+OrUbe2nsfZZu3ZtpX26d+9ufo6Pj5eOHTtW2kfv19oHAOr6WjWuk8x+0tMfqDPSOM0BYEuoOXr0qHz55ZfmS/3www/mZ2tq9axZs2TKlCne/ceMGWOu0+nY33zzjSxdutQ0Cd90003efcaOHWsCy9y5c80++n39+vVyww03ePcZN26cua1+6T5PPvmk7Nu3z9w/AJwO07pPtk7Nd56ZT63TaAoGglHj4adt27aZEGLRsKKGDx8uM2bMMENNGjYsrVu3NiFF99PF87QxWKdjW9O5VY8ePczU7WeffVaef/55c5vZs2dL165dvfvognzaMDxnzhw5ePCgtGvXztxvVlZWUE8cAGw//9NJKjU5R91NwpkN3CsFA6gZR7nVtVuPZGfTKAzAPtf830bZlXNMXhrVRc4/o+pzNN24YJNs358vT1/ZUfqd4z/bE6jvjcIZGSdvFOYs3QBg25m6qx9+yjteYr7r6RAA1ByhBgDs6qk5yfBT3vFS8z2VUAMEhVADALUs1kzprv40CWXl5ZJf5A41VGqA4BBqAKCWxXmmdFcXao4WucS6OjXRvdwFgJoh1ABAHeip+cnTT5MYGyMJsbw1A8HgXw4A2LT4XnVTuq2hp4b00wBBI9QAgE09NSXVDD/lFVqhhqEnIFiEGgCwq6emmkqNNfxEpQYIHqEGAOpATw3DT0DoCDUAYFOocVU3/ORZo4ZKDRA8Qg0A2NVTU93wEz01QMgINQBg1+ynaoef6KkBQkWoAQDbemoYfgJqE6EGAOw6TUK1s5+Y0g2EilADADYNP1W3Tk2+FWoSOEM3ECxCDQDUsjhr+MlVdU9NUanLfE+M420ZCBb/egDAtkbhqis11nRvpycAAag5Qg0A2NVTU02osa6zmooB1ByhBgBqmRVUSqoZfrJCDZUaIHiEGgCw6dxP1a0obF1nVXUA1Bz/egCgDqxTQ6UGCB2hBgBqGT01gD0INQBg1zo11fTUMPsJCB2hBgAiPPxUXl7O7CcgDAg1AFDLYp3VnybBN+sw+wkIHqEGACJcqfHdzjo1QPAINQBg05TuqnpqfKd6E2qA4BFqACDilZoTYYdQAwSPUAMAEZ7S7VupoacGCB6hBgDqSE+NjlI5HJz7CQgWoQYAbOqpKT1JTw1VGiA0hBoAiPDw04kzdPOWDIQiqH9BCxYskAEDBkjnzp1lxIgRsnHjxpPuP2TIEOnSpYsMHjxYli9f7nf99ddfL+3bt6/0NWHCBO8+L7zwQqXre/fuHczhA0DdHH7y7AcgOLE1vcGqVatk+vTp8sgjj0iPHj1k8eLFMn78eFm5cqW0bNmy0v4LFy6UWbNmyeOPP25C0JYtW2TatGnSsGFDE4yswFJSUuK9zZEjR+TKK6+Uyy67zO++2rZtK/Pnz/dedjqdNT18AIjYaRKqWnzvRKWGUAPYGmo0VIwcOVJGjRplLk+dOlXWrFkjixYtknvvvbfS/itWrJDRo0fL0KFDzeXWrVvLF198Ia+88oo31DRu3NjvNhqQEhMTK4UaDTFNmzat6SEDQERZYaXEZ+q2L3pqgAiEmuLiYtm+fbvfsJDSYaBNmzZVeZuEhAS/bRpYtm7daqozcXFxlW6zbNkyGTZsmCQnJ/tt37Nnj/Tp00fi4+Ola9euMnnyZBOSaorJBQDsFBd74jQJgd5/rFCj4Yf3J6CyU/13UaNQk5ubKy6XS9LT0/22Z2RkyKFDhwLeRkPI0qVLZeDAgdKxY0fZtm2bCS0aaPT+MjMz/fbX4amvv/5annjiCb/t2o/z1FNPSZs2bSQnJ0deeuklGTNmjLz33nuSlpZWk6ch6empNdofAELhTCo23zW6pDVpUKl3psHRUvM9Ps4pGRm8PwG2DT+piuso6Blmq1pbYeLEiSbw6BCU7qeBaPjw4TJv3ryAPTEagNq1a2dCjK9+/fr5Xe7WrZsMGjTINB2PGzeuRsefk5Mv5YGHtgEg7AqK3KFF7T+YJwmeyo33PelwgfnukHLJzs7nNwBUoBHjVAoSNQo1WhHRIJKdne23XSsnWq0JRIeatLH4scceM/tpT8ySJUskJSWlUoWlsLDQ9NNMmjTppMeiQ1Mafnbv3i01pYGGUAPALk6fP/p0CCreWdXiew7emwC7pnRrL4sOIa1du9Zv+7p166R79+7V3lZ7Z5o3b25Ckc6g6t+/v8RUWJPh/fffNz04V1xxxUmPRff75ptvaBwGUOfF+ISasgB/Ufn21ACwcfhJh3qmTJkinTp1MkFGqy779u0z/S1Kp28fOHBAZs6caS7v2rXL9MloY29eXp6ZPbVjxw6ZMWNGpfu2em8C9choP40GoRYtWsjhw4dNT01BQYEZygKAusw3qwQKNaxTA0Qo1OjUbG3wnTNnjhw8eNAMAc2dO1eysrLM9do/oyHHUlZWZoKMhpvY2Fjp1auXmf7dqlUrv/vV6z///HN57bXXAj7u/v37zWwnXcNGQ4/21Lz11lvexwWAuirGJ9UEWn/vRKWGFYWBUDjKtXu3ntFGvPr3rAFEir7NXvjMJ+bn1bddJE2S4/2u/9vXh+SBd7+U7lkNZe6YbhE6SqDu0hHcU5kZyJ8FAFDLdHaoVayprlLjdPKWDISCf0EAYANr2YuyAKnGe5oEVt4DQkKoAQAbeE7/VG2jsHWOKADBIdQAgJ2VmgDDT77r1AAIHqEGAGxwoqemmnVqqNQAISHUAICNC/AFmnlJpQYID0INANgYalxUaoBaQ6gBABuHnwJWalxl5js9NUBoCDUAEOlKjWcbPTVAaAg1AGDjqRICLeKuZ+5WVGqA0BBqAMDO2U/ukaYqKjW8JQOh4F8QANg4/FQmVGqA2kKoAQBbKzVV99Q4fc7mDaDmCDUAYGelJuDsJxqFgXAg1ABApFcUtnpqOE0CEBJCDQBE+txPVGqAsCDUAIANrOnaAc/SbfXUUKkBQkKoAQAbWHklYKjxrCjM4ntAaAg1AGADa2ZToOEnT6ahUgOEiFADADawJmsHrNR4VuSjUgOEhlADABGv1NBTA4QDoQYA7Jz9FCDVlHq2UakBQkOoAQAbOL2NwtVUalhRGAgJoQYAbF2npppKTQxvyUAo+BcEADZWasoDrShMpQYIC0INANhYqfEsHhz4NAkMPwEhIdQAgA1iqqnUWKdJoKcGCA2hBgAifJZuKjVAeBBqAMDWUFN1pYbhJyA0hBoAsIE1sSlQqKFSA4QHoQYA7KzUeM7zFOiElvTUAKEh1ABApIefvOvUWGeIAmBbqFmwYIEMGDBAOnfuLCNGjJCNGzeedP8hQ4ZIly5dZPDgwbJ8+XK/699++21p3759pa+ioqKQHhcA6gorr1QXaqjUAKGJrekNVq1aJdOnT5dHHnlEevToIYsXL5bx48fLypUrpWXLlpX2X7hwocyaNUsef/xxE0a2bNki06ZNk4YNG5qAYmnQoIH85S9/8bttQkJC0I8LAKfN7CdWFAYiU6mZP3++jBw5UkaNGiVnn322TJ06VZo3by6LFi0KuP+KFStk9OjRMnToUGndurUMGzZMrr76annllVcqLUzVtGlTv69QHhcA6hIqNUAdq9QUFxfL9u3bZcKECX7be/fuLZs2baryNr4VF5WYmChbt26VkpISiYuLM9uOHTsm/fv3F5fLJeeee67cddddct555wX9uNXx/MEEALaJ8aSa8gDvQValJs7p4P0JCOFzu0ahJjc314SO9PR0v+0ZGRly6NChgLfp06ePLF26VAYOHCgdO3aUbdu2ybJly0yg0fvLzMyUs846ywwtaR9NQUGBvPHGG3LttdfKO++8I23atAnqcauTnp5a49sAQCiSEt1/wCUmxUtGRmrAKd1NMxpIRqMkXmjArp4a33OYWHTZ74rbLBMnTjTBQ4egdD8NJsOHD5d58+aJ0+k0+3Tr1s18WbRnRvd58803Tf9NMI9bnZycfAnQqwcAtaa4uNR8Lygokuzs/ICL7+UdOSZxJe79AJygH/WnUpCoUahJS0szQSQ7O9tve05OjqmaBKJDTVqFeeyxx8x+2iuzZMkSSUlJMfcXSExMjGkq3r17d9CPWx0NNIQaAJGa0u37/qNDT+U++/DeBNjUKBwfH2+GkNauXeu3fd26ddK9e/dqb6u9M9rYq+FEZzJp/4yGl0C0AvPll196m4VDeVwAqAtiKvTPWHyneDtp+APsHX4aN26cTJkyRTp16mQChVZd9u3bJ2PGjDHX6/TtAwcOyMyZM83lXbt2mWncXbt2lby8PDOLaceOHTJjxgzvfb744ovmeu2fsXpqvvrqKzN9+1QfFwBOl0ZhX74Zp4q/8wDUVqjRqdnauDtnzhw5ePCgtGvXTubOnStZWVnmeu2f0bBhKSsrM0FGw01sbKz06tXLTMNu1aqVdx8NOw8//LC5bWpqqpn1pP00uljfqT4uAJwOU7qrq9RYQ1QAguMo17Geekab9OrfswYQSTP+ukOWbd4nEy4+U8ZfcqZ3e0FRqfR/cZ35ec1dfSQhlnINUJHm/YqzBgPhXw8A2MCqwljTty2+Fzn1ExAaQg0A2MAKLBWL474hh+EnIDSEGgCwtVLjv9035FCpAUJDqAEAG0NN5UqN+7teG8xiogBOINQAgK2zn/y3WyHHmvINIHiEGgCwgVWFObF+sP8UbzINEDpCDQDYwOl5t62wTI33Mk3CQOgINQBgY6WmrIrF96jUAKEj1ACADZyOyisIuy973oxpEgZCRqgBADsrNZWGn9wbnJRqgJARagDABtYZuCtXatyXmfsEhI5QAwA2cJxk+IlKDRA6Qg0A2Fqp8d9uNQ6z8B4QOkINAES0UuPpqWH8CQgZoQYAbGANL1W1Tg2VGiB0hBoAqAPr1FCpAUJHqAEAG99sq1xRmCndQMgINQBgAyu0VDz3k1W5YfE9IHSEGgCw9SzdFU5oyWkSgLAh1ACADaxKTIXJT97LNAoDoSPUAICdlZoKqca6bK1jAyB4hBoAiGilxlp8j18DECpCDQDYGGoqV2rc36nUAKEj1ACADWJi/CszFusyU7qB0BFqAMAGMZ7zcFuVGYurzHM9w09AyAg1AGDnOjVVnPuJdWqA0BFqAMAGViWm4orC3uEnKjVAyAg1ABDBcz9Zw1FUaoDQEWoAwAbWCSup1AC1h1ADAHZWaqpYfI9KDRA6Qg0A2MBZRaixLhJqgNARagDABo4qhp+sE1xa69gACF5Q/4wWLFggAwYMkM6dO8uIESNk48aNJ91/yJAh0qVLFxk8eLAsX77c7/q33npLfvWrX8kFF1xgvm688UbZsmWL3z4vvPCCtG/f3u+rd+/ewRw+ANSZSg1TuoHwia3pDVatWiXTp0+XRx55RHr06CGLFy+W8ePHy8qVK6Vly5aV9l+4cKHMmjVLHn/8cROCNKxMmzZNGjZsaIKR+uyzz2TYsGHm/uLj42XevHly0003mfts1qyZ977atm0r8+fP9152Op3BP3MAiEilpmKocX9n+AmIQKjRUDFy5EgZNWqUuTx16lRZs2aNLFq0SO69995K+69YsUJGjx4tQ4cONZdbt24tX3zxhbzyyiveUKOhx5cGoNWrV8v69evlqquu8gsxTZs2rfmzBIAIc3oWoqk4/HSiUhOJowLqcagpLi6W7du3y4QJE/y26zDQpk2bqrxNQkKC37bExETZunWrlJSUSFxcXKXbFBYWSmlpqTRq1Mhv+549e6RPnz6mmtO1a1eZPHmyCUk1xdlwAURu8b1yv/cg30Zh3puAwE7130aNQk1ubq64XC5JT0/3256RkSGHDh0KeBsNIUuXLpWBAwdKx44dZdu2bbJs2TITaPT+MjMzK91GKzc67HTJJZd4t2k/zlNPPSVt2rSRnJwceemll2TMmDHy3nvvSVpaWk2ehqSnp9ZofwAIVZOCEvM9JiZGMjJOvAclJce7vyfF+W0HYMPwk+96C77LfFfcZpk4caIJPDoEpftpIBo+fLjpmwnUE6PDUtpL88Ybb/hVePr16+e3X7du3WTQoEGm6XjcuHE1Ov6cnHzvX0cAYIe8vELzvaTUJdnZ+d7t+QVF7u3FpX7bAZygEeNUChI1CjVaEdEgkp2d7bddKydarQlEh5q0sfixxx4z+2lPzJIlSyQlJaVSheXVV1+Vl19+2fTtdOjQodpjSU5Olnbt2snu3bulpjTQEGoA2Mn6s09Pk+D7/uOd0u1w8L4E2DmlW3tZdAhp7dq1ftvXrVsn3bt3r/a22jvTvHlzE4p0BlX//v1NGdailZs5c+aY7zpL6mS0V+ebb76hcRjAacGa3VRVo7B1GgUANg4/6VDPlClTpFOnTibIaNVl3759pr/F6oc5cOCAzJw501zetWuXmcatjb15eXmmCrNjxw6ZMWOG35DTc889Z26blZXl7c/RaoxWdJT202gQatGihRw+fNj01BQUFJihLAA4nRqFfVkhp6ohfAC1GGp0arY2+GpV5eDBg2YIaO7cuSaMKA0kGnIsZWVlJshouImNjZVevXqZ6d+tWrXy7qOXtXF40qRJfo91xx13yJ133ml+3r9/v5ntdOTIETNspT01umif9bgAcHpXagg1QKgc5dq9W89oM179e9YAImnnoaNy7RufS5PkOFl928Xe7a9+ukf+uHaPXNW5uUz9RbuIHiNQV2nmP5XZgZxtBABsYLUQVqrUlPkvzgcgeIQaALBBjGf+U8WeGpfnMpEGCB2hBgBsEBMTONRYHQBUaoDQEWoAwM7ZT57hJouLE1oCYUOoAYAInqXbqtQw+QkIHaEGAGxgTdmuOPHSZTUKk2qAkBFqAMAG1uJ61mkRLOWemMPie0DoCDUAYAPrNAgVlwazQo6Td2MgZPwzAgA7KzWVVhT2vx5A8Ag1AGAD354Z32oNJ7QEwodQAwA28C3E+FZrrFBjnRsKQPAINQBgA9/F9fwrNZ43Y0INEDJCDQDYXanxmQFV5vmZUz8BoSPUAIDdPTU+260FhqnUAKEj1ACADXxnNwWs1FCqAUJGqAEAG/hmlvKAjcL8GoBQEWoAwAa+w0u+53+iURgIH0INANjAtxLjH2qY0g2EC6EGAGzqqbFyje/pn05Uavg1AKEi1ACATazg4lepoVEYCBtCDQDYxJrh5F+p8Qw/8VsAQsa/IwCwuVk4YKMw409AyAg1ABDB4ScXU7qBsCHUAIDdlRprGWGf80CxojAQOkINAERw+Mk6Y7fvaRQABIdQAwC2Dz9VrtSQaYDQEWoAwObzPwWa0u2kURgIGaEGAGxi5Rbfcz9Zw0++J7wEEBxCDQDY3FNjzXjyHX5ykmmAkBFqAMD2Sk3lRmEqNUDoCDUAYHulRgJUaijVAKEi1ACA3adJ8Jn+5PKe+4lfAxCqoP4ZLViwQAYMGCCdO3eWESNGyMaNG0+6/5AhQ6RLly4yePBgWb58eaV9Vq9eLUOHDpVOnTqZ7x9++GHIjwsAdUms99xPPj01nu8x3nN4A7At1KxatUqmT58ut912mwknPXv2lPHjx8vevXsD7r9w4UKZNWuW3HnnnbJy5UqZNGmS/O53v5OPPvrIu8+mTZvknnvukSuvvFLeeecd8/3uu++WzZs3B/24AFBXe2pKqdQAdSPUzJ8/X0aOHCmjRo2Ss88+W6ZOnSrNmzeXRYsWBdx/xYoVMnr0aFN9ad26tQwbNkyuvvpqeeWVV7z7vP7663LJJZfILbfcYu5Tv1900UVme7CPCwB1jbUWjf8JLTlNAhAusTXZubi4WLZv3y4TJkzw2967d29TbanqNgkJCX7bEhMTZevWrVJSUiJxcXHyxRdfyI033ui3T9++fb2hJpjHrQ79eAAiwWoG1iBjvQ9ZRRsNPLw3AYGd6r+NGoWa3Nxccblckp6e7rc9IyNDDh06FPA2ffr0kaVLl8rAgQOlY8eOsm3bNlm2bJkJNHp/mZmZkp2dXek+9bJ1n8E8bnXS01NrfBsACFVCvPstNyU1STIy3O9DDk/1Jq1xsncbgODUKNRYKq6noFMSq1pjYeLEiSZ46BCU7qfBZPjw4TJv3jxxOp01us+aPG51cnLy/Vb0BAA7lHtOz5175JhkZ+ebn0tL3dvy8wq92wD404/6UylI1CjUpKWlmSCilRVfOTk5pmoSiA41aYPvY489ZvZr2rSpLFmyRFJSUsz9Kb1txfs8fPiw9z6DedzqaKAh1ACI1Do1pa5y73uQNaVbr+F9CbCxUTg+Pt4MIa1du9Zv+7p166R79+7V3lZ7Z7SxV8OJzmTq37+/xHgWZujWrVul+1yzZo33PkN5XAA4LRqFOaElYP/w07hx42TKlClmPRkNFFp12bdvn4wZM8Zcr9O3Dxw4IDNnzjSXd+3aJVu2bJGuXbtKXl6emcW0Y8cOmTFjhvc+x44dK7/+9a9l7ty5cumll8rf/vY3Wb9+vZkOfqqPCwB1nXV+J6s6o6wfrSoOABtDjU7N1sbdOXPmyMGDB6Vdu3YmjGRlZZnrtX9Gw4alrKzMBBkNN7GxsdKrVy8zDbtVq1befXr06CHPPPOMPPvss/L888+bqd+zZ882QehUHxcATpdKjSvglO6IHRYQNRzlvmdWqye0Ga/+PWsAkTZp2VZZvztXHrmsnfyyY3OzbdCc9XKksEQW39BTzs5IifQhAnWSFjJPZXYgZxsBALsrNX7DTyy+B4QLoQYAbD73k+9Zuhl+AsKHUAMANrGagf0qNe5lamgUBsKAUAMAdk/pDjT8xLsxEDL+GQGATawZToFmP1nnhQIQPEINANjdU+NTqbH6a4I55QsAf4QaAIjg7CdrVQ1rYT4AwSPUAIDdjcKeIKOBxso3VGqA0BFqAMD2RmH3Zd81QOmpAUJHqAEAm1jBpdRTqfGdBUVLDRA6Qg0ARGhKt+8ifNZ1AIJHqAGACDUK+556j7N0A6Ej1ABAhBqFfderoVADhI5QAwA2ifW8456o1Pi8GdNUA4SMUAMAETr3k+96NVRqgNARagDA7kZhT5bxq9SQaoCQEWoAIEKNwr49Ncx9AkJHqAGASK1TY52h28GKwkA4EGoAIELr1FjDUDQJA+FBqAEAm8RUGH7yrdQACB2hBgBsHn6ywsyJUEOqAcKBUAMANnF63nFLrUqN58SWhBogPAg1AGBzpabS8BPvxEBY8E8JACK0Tg2NwkB4EWoAIMLr1DD8BIQHoQYA7B5+Kvc/Szezn4DwINQAQKSmdNMoDIQVoQYAbO+pcYeaUk+qiaVUA4QFoQYAIjT7yZraHetknRogHAg1ABChdWqs3hor7AAIDaEGACI0pbvU5Qk1DD8BYUGoAQCbWFO3K07ppqcGCI/YYG60YMECefXVV+XQoUPStm1b+e1vfyvnn39+lfuvWLFC5s2bJ3v27JHU1FTp27evTJkyRdLS0sz1119/vWzYsKHS7fr16ydz5841P7/wwgvy4osv+l2fkZEha9euDeYpAIDtrPBihRkr3FCpASIUalatWiXTp0+XRx55RHr06CGLFy+W8ePHy8qVK6Vly5aV9t+4caPcf//98uCDD0r//v3lwIED8uijj8q0adPkD3/4gzewlJSUeG9z5MgRufLKK+Wyyy7zuy8NUPPnz/dedjqdNT18AKgzlRpr+IlKDRCh4ScNFSNHjpRRo0bJ2WefLVOnTpXmzZvLokWLAu6/efNmycrKkrFjx0rr1q1NRWf06NGybds27z6NGzeWpk2ber+0+pKYmFgp1GiI8d2vSZMmwTxnAKhTKwoTaoAIVGqKi4tl+/btMmHCBL/tvXv3lk2bNgW8Tffu3WX27Nny8ccfy89//nPJycmR1atXm6GlqixbtkyGDRsmycnJftt1+KpPnz4SHx8vXbt2lcmTJ5ugVFNMNAAQCbE+69To+5B39lOMg/clIAyf2zUKNbm5ueJyuSQ9Pb1Sb4v21wSiQ1RPP/203H333SYUlZaWyoABA+Shhx4KuP+WLVvk66+/lieeeMJve5cuXeSpp56SNm3amGD00ksvyZgxY+S9997z9uacqvT01BrtDwDhkF7kXmyvXBySkZEqySk/mctJiXHmMoAINAo7KkQmPX9JxW2WnTt3yuOPPy633367qbJo+Jk5c6bpyXnyyScr7b906VJp166dCTG+KlZ2unXrJoMGDZLly5fLuHHjanT8OTn54vkDCQBsk593zHwvcZVJdna+5B4pNJfLSt2XAQSmEeNUChI1CjVaEdG+luzsbL/tWjnRak0gL7/8sqnW3HzzzeZyhw4dJCkpSa677jpTvcnMzPTuW1hYaBqOJ02adNJj0aEpDT+7d++WmtJAQ6gBYDeHnOip0fcgaxE+HX7iPQmwuVFYe1k6duxYaRr1unXrTO9MIMePH5eYGP+HsWYtWWeotbz//vtmiOqKK6446bHoft98841pGAaA07JRmCndQGRnP+lQjw4R6ZeGCh1C2rdvn+lvUbNmzTJr0Fh0GveHH34oCxculO+//14+//xzMxylw0vNmjXzu2+9z4EDBwbskdF+Gl3LRu9DZ1RpNaegoECGDx8e3DMHgAg2Cvud+4kVhYHI9NQMHTrUNAzPmTNHDh48aIaAdIE8nbattGdGQ45lxIgRcvToUbNgnwYTXXzvoosukvvuu8/vfnft2mUCz2uvvRbwcffv329mO+kaNhp6tKfmrbfe8j4uAJwu69R4z/1EpQYIK0d5xTGgekAb8urfswYQaQfyi+SXcz+TOKdD1t3dV97Y8L288MkuGdaxmTx6WftIHx5QZ+nfA6cyQ5BzPwGATZyeSaLeFYUZfgLCilADABE4S7cWya1wQ08NEB6EGgCwie+JK/W0T6XWisIscw6EBaEGAGxuFFZapbFOaMlZuoHwINQAgE18h5l0WjfDT0B4EWoAIEKVGt8TWgIIHaEGACLRU2OGn9wnuCTUAOFBqAEAm/gWZLRKY1VqmP0EhAehBgBs4nA4/NaqYUVhILwINQAQoZNasvgeEF6EGgCIQLOwGX7i3E9AWBFqACASqwqXnThdAj01QHgQagAgwsNPzH4CwoNQAwA2sk6JoKdIoKcGCC9CDQBEZPiJnhog3Ag1ABCBtWpoFAbCj1ADADaK9anUnBh+4q0YCAf+JQGAjWI8oUYDDVO6gfAi1ABABBqFfU+TYG0DEBpCDQBEaJ2aUpdn+Mk6dwKAkBBqACBC69R4T2hJpQYIC0INAERo+InF94DwItQAQAQahX3P0s1pEoDwINQAQAQqNWVUaoCwI9QAgI2cnndd30oN534CwoNQAwA2sgKM9tNw7icgvAg1ABCR4Sd3tcZss86dACAkhBoAiHCjMKEGCA9CDQDYyJrppIGmVFfgY/YTEDaEGgCwUUKs+233eGkZU7qBMCPUAICNkuKc5vux4lKGn4AwI9QAgI1S4j2hpsQlnlM/sfgeEMlQs2DBAhkwYIB07txZRowYIRs3bqx2/xUrVsgVV1whXbt2lT59+siDDz4oubm53uvffvttad++faWvoqKikB4XAOpqpSbveKl3G43CQIRCzapVq2T69Oly2223yfLly6Vnz54yfvx42bt3b8D9NXjcf//9cvXVV8t7770nzz77rGzdulWmTZvmt1+DBg1kzZo1fl8JCQlBPy4A1EXJnkpNPqEGCLvYmt5g/vz5MnLkSBk1apS5PHXqVBNAFi1aJPfee2+l/Tdv3ixZWVkyduxYc7l169YyevRomTdvnt9+DodDmjZtGrbHDVa5Ll1eWhK2+4OI0xkrMTGMdAK+w0/5RScqNbH8+wDsDzXFxcWyfft2mTBhgt/23r17y6ZNmwLepnv37jJ79mz5+OOP5ec//7nk5OTI6tWrpV+/fn77HTt2TPr37y8ul0vOPfdcueuuu+S8884L+nGr41n7qhINM9nZ+6W83D3NEuGTlNRAGjVqYsIrUJ8lBwo1TkeV70sA5JT/fdQo1GgfjIaO9PR0v+0ZGRly6NChgLfp0aOHPP3003L33XebcFJaWmr6Yh566CHvPmeddZYZWtI+moKCAnnjjTfk2muvlXfeeUfatGkT1ONWJz09NWCFZs+ePeJ0OiUtrRkfvmFTbnqj8vOPSElJvLRs2TJ8dw2chpqnF5jvR0tO/PHUrGkq7zlAJIafVMW/tjUQVPUX+M6dO+Xxxx+X22+/3TQJawiZOXOmPPLII/Lkk0+afbp162a+fIPQ8OHD5c033/TrvanJ41YnJydfyj2zDiwuV6nk5xdIo0YZ4nTG1/g+UbWkpHhxucolJ+ewxMamMBSFes1VVGy+Hzla7G0SzslxBx0AgelHfaCCREihJi0tzVQysrOz/bbrkJJWTQJ5+eWXTUi5+eabzeUOHTpIUlKSXHfddaZ6k5mZWek22n+hM5x2794d9ONWRwNN5VBT5u3/QPjFx7ubvrVSFxdHaET9lRjrmf3kGX7SFYYrvh8BCE6Nujfj4+OlY8eOsnbtWr/t69atM70zgRw/frzSX+YaUKxKSyC6/csvv/Q2DgfzuMGi56N28LoCbinx7j+cvOd9opkGCJsalyXGjRsnU6ZMkU6dOplAsWTJEtm3b5+MGTPGXD9r1iw5cOCAGWJS2vyr/TMLFy6Uvn37ysGDB82wU5cuXaRZs2ZmnxdffNGsYaP9M1ZPzVdffWWGqE71cQHgdGoU9m0SBhChUDN06FDTuDtnzhwTUNq1aydz584107aV9sxo2LDoInlHjx41C+c99dRTkpqaKhdddJHcd9993n3y8vLk4YcfNrfV63XWk/bTaPA51cdFcK6++nK55ppr5ZprfsVLCNgg2bP4noVKDRA+jvKqxoCiWHZ25UbhkpJiycnZJ+npLepVz4ddoaa+vr5ARcWlZdL7uTXeyxkp8fL+rRfxQgHV0FHajIyTNwqzIhoA2CjO6fA7LYI2CgMID0LNaWz58mVy1VVDpKzMf7HA+++/Rx5//BH58ccf5IEHJsvll/9CBg3qKzffPFb+9a/Pqry/ffv2Sp8+58uOHf/1bsvPzzfb/v3vE+fZ2rXrW/nNbyaZ+9T7/v3vH5IjR47U0rMEoq9p3lpVWHHeJyB8CDXV0JG5whKXrV81GQ0cMGCg/PTTEb/Aof1JGzZ8Kr/4xRCzSvNFF/WWZ5+dI6+9tkAuvPAiuf/+ybJ///6g/4fRafV33jlB2rZtL/Pm/UlmzXpeDh8+LA8//EDQ9wnU574aQg0QPizKUgUNFzcv3ixb9uaJnbq2bCivjOl6SlOgGzZsJL16XSwffvgXOf/8C822v//9r9KwYUPp2fMCM3W+bdt23v0nTJgo//znP2Tt2o9l5MjRQR3f8uVLpV27DnLLLbd7tz344MMyYsQw+e67PXLGGWcGdb9AfZLkU6lh+AkIH0JNNU6Hke5Bg4bI//t/T8i99z5g1vPRgHPppb8wgaawsFDmz58r69atkezsQ+ZUE3rKggMHgq/U/Pe/X5rKkA49VaTDXYQa4OQYfgJqB6GmClop0YrJ8VJ7T26ZGBtTo4Xq+vTpK089VS7r16+RDh3Ok82bN8kdd9xjrvvDH56TDRvWy+233y2tWrWWhIQEmTbtfikpOXEiPV8Oh3s00ncITFcA9lVWVi69e/eV226bVOn26ek1X90ZqO/DT1RqgPAh1FRDw0VShTUl6pqEhETp16+/fPDB+/LDD99L69ZnSIcO55rrtmzZJEOHXm6uV9pjs3//XhHpGfC+0tIam+85OSdOR7Fz54mmYdWuXXv5+OOPpHnzFhIby/8+QKgL8BFqgPChUTgK/OIXl8n69Wtl5coVpkHYkpXV2gQQnc20Y8fX8rvfTTWVluoCUseOneXNN183M5y++OLfMnfuS377jBx5jWlGfvTRqfKf/2wzQ07amPzkk78zw1sAahZqaBQGwodQEwV69LhAUlMbmkbdQYMu826fNGmy2X7rrTeZad4XXnixqbRUR5t+dcjp5puvl+eee1omTLjN7/qMjKby0kuvmmnkkyffKWPHjjb7NWjQgLNvA6eI2U9A7WBFYQ9WvK1dvL7ACX9cu1te/fQ78/Ol7TJkxuXn8fIAYVhRmKYIALDZiC4tpKCoVNKS4+SKTs15/YEwIdQAgM0yUxPkNwPO4XUHwoyeGgAAEBUINQAAICoQagAAQFQg1FRQkxNK4tTxugIAahuhxnohYtwvhcsV+BQCCE1xcZH57nTSmw4AqB18wnjExDglLi5RCgqOmJNBWudBQugVGg00BQW5kpTEAn0AgNpDqPE5z1OjRk0kJ2e/HD58oBZf8vpJA03Dhk0ifRgAgChGqPF9MWLjJDOzlZSWlkTuNxKFdMjJGt4DAKC2EGoCVGzi4uJr7QUHAAC1gz+fAQBAVCDUAACAqBBbX8/2CQAAoutz21HOqmgAACAKMPwEAACiAqEGAABEBUINAACICoQaAAAQFQg1AAAgKhBqANRpn332mbRv317y8vIifSgA6jimdAOoU66//nrp0KGDTJ061VwuLi6Wn376STIyMsxpTACgKvVy8T0Ap4/4+Hhp2rRppA8DwGmA4ScAdcYDDzwgGzZskDfeeMMMOenX22+/7Tf8pJfPP/98+fvf/y6DBw+Wrl27yqRJk+TYsWPy5z//WQYMGCAXXHCB/P73vxeXy+W9b634zJw5U/r27SvdunWTUaNGmaEtANGDSg2AOkOHnHbv3i1t27Y1QUXt3Lmz0n7Hjx+XP/3pTzJ79mw5evSo3HHHHXLnnXdKamqqzJ07V77//ntzuWfPnjJ06FBzmwcffFB+/PFHc5vMzEz58MMP5eabb5Z3331X2rRpY/tzBRB+hBoAdYaGkri4OElMTPQOOX377beV9ispKZFHH31UzjjjDHNZKzYrVqyQtWvXSkpKipxzzjnSq1cv+fTTT02o+e6772TlypXy8ccfS7Nmzcxt/vd//1c++eQTU/mZPHmyzc8UQG0g1AA47SQlJXkDjdIm4qysLBNofLcdPnzY/Lx9+3bR09xddtllfvejQ1KNGze28cgB1CZCDYDTTmys/1uXzooKtK2srMz8rIHG6XTKsmXLzHdfycnJNhwxADsQagDUKTr8ZIWRcDn33HNN07BWbrTJGEB0YvYTgDpFh5E2b94sP/zwgwkh4Qg4P/vZz+Tyyy+XKVOmyAcffGAaibds2WKairXPBkB0INQAqFNuuukmM0Q0bNgwufjii2Xfvn1hud/p06fLVVddJTNmzJAhQ4bIxIkTTbBp3rx5WO4fQOSxojAAAIgKVGoAAEBUINQAAICoQKgBAABRgVADAACiAqEGAABEBUINAACICoQaAAAQFQg1AAAgKhBqAABAVCDUAACAqECoAQAAUYFQAwAAJBr8/9D6GX+ipcPwAAAAAElFTkSuQmCC", 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", 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", 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" ], "text/plain": [ " sunshine/PMU6 sunshine/PMU5 sunshine/PMU2 sunshine/PMU1 \\\n", "sunshine/PMU6 1.000000 0.996615 0.998574 0.988252 \n", "sunshine/PMU5 0.996615 1.000000 0.998159 0.968694 \n", "sunshine/PMU2 0.998574 0.998159 1.000000 0.990526 \n", "sunshine/PMU1 0.988252 0.968694 0.990526 1.000000 \n", "sunshine/PMU4 0.998495 0.977561 0.999887 0.976392 \n", "\n", " sunshine/PMU4 \n", "sunshine/PMU6 0.998495 \n", "sunshine/PMU5 0.977561 \n", "sunshine/PMU2 0.999887 \n", "sunshine/PMU1 0.976392 \n", "sunshine/PMU4 1.000000 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "merged_df = merge_tables(result_dict)\n", "corr_df = perform_correlation_analysis(merged_df)\n", "corr_df" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:21:04.403004Z", "start_time": "2024-07-18T17:21:04.080340Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:49:44.037437Z", 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "merged_df.set_index(\"time\").plot()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "source": [ "## Day of the week plot\n", "\n", "Since this is a distribution system being monitored, do these voltage sags occur most often on certain days of the week?" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:21:07.393238Z", "start_time": "2024-07-18T17:21:07.392117Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:49:45.090423Z", "iopub.status.busy": "2025-12-08T22:49:45.090302Z", "iopub.status.idle": "2025-12-08T22:49:45.092684Z", "shell.execute_reply": "2025-12-08T22:49:45.092360Z", "shell.execute_reply.started": "2025-12-08T22:49:45.090408Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "# iterate through each event (the list of tables), extract the day of the week 0->6 (monday->sunday) the event exists in\n", "# take the average and assign it to the floor of that value, create a histogram\n", "def extract_weekday_and_min_pu_value(tab: pa.Table) -> tuple[int, float]:\n", " weekday_vals = int(pc.mean(pc.day_of_week(tab[\"time\"])).as_py())\n", " min_val_pu = pc.min(tab[\"value\"]).as_py()\n", " return weekday_vals, min_val_pu" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T17:21:07.473010Z", "start_time": "2024-07-18T17:21:07.393934Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:49:45.093150Z", "iopub.status.busy": "2025-12-08T22:49:45.093053Z", "iopub.status.idle": "2025-12-08T22:49:45.103040Z", "shell.execute_reply": "2025-12-08T22:49:45.102595Z", "shell.execute_reply.started": "2025-12-08T22:49:45.093140Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "cd5580da2ada46a4821461af339a2d13", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/5 [00:00" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create the plot\n", "plt.figure(figsize=(16, 9))\n", "sns.set(style=\"whitegrid\")\n", "\n", "# Create a scatter plot\n", "scatter_plot = sns.boxplot(\n", " x=\"weekday\",\n", " y=\"value\",\n", " hue=\"collection\",\n", " data=weekday_df,\n", ")\n", "\n", "# Add vertical lines to delineate weekdays\n", "for i in range(1, 7):\n", " plt.axvline(x=i - 0.5, color=\"grey\", linestyle=\"--\", linewidth=3)\n", "\n", "# Enhance the plot\n", "plt.title(\n", " \"Distribution of Voltage Sag Events by Day of Week and Minimum Per-unit Voltage Magnitude\\nFrom 2016-01-01 to 2017-01-01\"\n", ")\n", "plt.ylabel(\"Minimum Voltage Magnitude Encountered ($V_m$)[pu]\")\n", "plt.xlabel(\"Day of the Week\")\n", "plt.legend(title=\"Sensor\", bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n", "\n", "# Show the plot\n", "plt.tight_layout()\n", "plt.savefig(\"vsag_distribution_sunshine_data_2016_2017.png\", dpi=200)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2024-07-18T18:55:30.151309Z", "start_time": "2024-07-18T18:55:29.661175Z" }, "collapsed": false, "execution": { "iopub.execute_input": "2025-12-08T22:49:45.613924Z", "iopub.status.busy": "2025-12-08T22:49:45.613787Z", "iopub.status.idle": "2025-12-08T22:49:45.712702Z", "shell.execute_reply": "2025-12-08T22:49:45.712333Z", "shell.execute_reply.started": "2025-12-08T22:49:45.613910Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create the plot\n", "plt.figure(figsize=(12, 8))\n", "sns.set(style=\"whitegrid\")\n", "\n", "# Create a scatter plot\n", "scatter_plot = sns.scatterplot(x=\"weekday\", y=\"value\", hue=\"collection\", data=weekday_df, s=100)\n", "\n", "# Add vertical lines to delineate weekdays\n", "for i in range(1, 7):\n", " plt.axvline(x=i - 0.5, color=\"grey\", linestyle=\"--\", linewidth=3)\n", "\n", "# Enhance the plot\n", "plt.title(\n", " \"Scatter Plot of Voltage Sag Events by Day of Week and Minimum Per-unit Voltage Magnitude\"\n", ")\n", "plt.ylabel(\"Minimum Voltage Magnitude Encountered ($V_m$)[pu]\")\n", "plt.xlabel(\"Day of the Week\")\n", "plt.legend(title=\"Sensor\", bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n", "\n", "# Show the plot\n", "plt.tight_layout()\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 4 }