"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot the trend of gas consumption over time\n",
"plt.figure(figsize=(12, 6))\n",
"plt.plot(livesey_house_data['Date'], livesey_house_data['GasConsumption_kWh'], label='Gas Consumption (kWh)', color='orange')\n",
"plt.title('Energy Consumption Trend - Livesey House (2010-2020)', fontsize=14)\n",
"plt.xlabel('Date (Month-Year)', fontsize=12)\n",
"plt.ylabel('Gas Consumption (kWh)', fontsize=12)\n",
"plt.xticks(\n",
" ticks=livesey_house_data['Date'][::12], # Show one tick per year\n",
" labels=livesey_house_data['Date'][::12].dt.strftime('%b-%Y'),\n",
" rotation=45 # Rotate for better readability\n",
")\n",
"plt.grid(True, linestyle='--', alpha=0.7)\n",
"plt.legend()\n",
"plt.show()\n",
"\n",
"# Seasonal patterns\n",
"livesey_house_data['Year'] = livesey_house_data['Date'].dt.year\n",
"livesey_house_data['Month'] = livesey_house_data['Date'].dt.month\n",
"\n",
"plt.figure(figsize=(12, 6))\n",
"sns.boxplot(data=livesey_house_data, x='Month', y='GasConsumption_kWh')\n",
"plt.title('Monthly Energy Consumption Patterns - Livesey House', fontsize=14)\n",
"plt.xlabel('Month', fontsize=12)\n",
"plt.ylabel('Gas Consumption (kWh)', fontsize=12)\n",
"plt.grid(True, linestyle='--', alpha=0.7)\n",
"plt.show()\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "8094d726-b23a-414b-9f20-869a4d920a32",
"metadata": {},
"source": [
"### Explanation of the Visualizations\r\n",
"\r\n",
"#### **1. Gas Consumption Trend Over Time (2010-2020)**\r\n",
"\r\n",
"This line graph visualizes the gas consumption for Livesey House on a monthly basis from January 2010 to December 2020. The x-axis represents the timeline in **month-year format** (e.g., Jan-2010, Jan-2011), while the y-axis shows the gas consumption measured in **kWh**. \r\n",
"\r\n",
"**Key Observations:**\r\n",
"- **Seasonal Peaks and Troughs**:\r\n",
" - Gas consumption rises during the **winter months** (e.g., December, January, February), which reflects increased heating needs.\r\n",
" - Conversely, consumption dips significantly during the **summer months** (e.g., June, July, August), as heating is less required.\r\n",
"- **Recurring Patterns:**\r\n",
" - There is a consistent annual cycle where gas usage increases and decreases predictably.\r\n",
"- **Anomalies or Unusual Behavior:**\r\n",
" - Occasional sharp drops or near-zero values (e.g., summer months) might correspond to building closures, maintenance periods, or reporting gaps.\r\n",
"\r\n",
"**Insights:**\r\n",
"- The strong seasonal trend indicates that gas consumption is closely tied to weather conditions and heating requirements.\r\n",
"- Any anomalies, such as irregular consumption patterns, could provide insights into operational changes, maintenance schedules, or external factors like the COVID-19 pandemic in 2020.\r\n",
"\r\n",
"#### **2. Monthly Gas Consumption Patterns**\r\n",
"\r\n",
"This boxplot illustrates the distribution of gas consumption for each month over the entire time period (2010-2020). The x-axis represents the **months** (from January to December), while the y-axis represents the gas consumption in **kWh**.\r\n",
"\r\n",
"**Key Observations:**\r\n",
"- **Seasonal Variation:**\r\n",
" - **Highest consumption** is observed in the winter months (e.g., January, February, December), with large spreads indicating variability in heating needs across different years.\r\n",
" - **Lowest consumption** occurs in the summer months (e.g., June, July, August), with minimal variability.\r\n",
"- **Month-to-Month Comparisons:**\r\n",
" - The gradual decline from February to June reflects decreasing heating demands as temperatures rise.\r\n",
" - The steady increase from September to December mirrors the preparation for colder months.\r\n",
"\r\n",
"**Insights:**\r\n",
"- The boxplot highlights seasonal trends effectively, showing both the typical values and the variability for each month.\r\n",
"- Variability in winter months could be attributed to fluctuating weather conditions, building usage, or energy-saving measures implemented in certain years.\r\n",
"\r\n",
"#### **Summary of Visualizations:**\r\n",
"- The **line graph** emphasizes trends over time, making it easier to identify year-to-year consistency, seasonal changes, and unusual patterns.\r\n",
"- The **boxplot** provides a detailed view of month-specific distributions, helping to compare consumption across months and identify variability.\r\n",
"\r\n",
"Together, these visualizations offer a comprehensive understanding of Livesey House's gas consumption patterns, facilitating deeper analysis and insights into energy usage behaviors.\r\n",
"\r\n"
]
},
{
"cell_type": "code",
"execution_count": 157,
"id": "63f80f8d-0b99-444a-bfcf-dc7e34fb1d0f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"metadata": {},
"output_type": "display_data"
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],
"source": [
"\n",
"\n",
"\n",
"\n",
"# Split data into training (2010–2015) and testing (2016)\n",
"train_data = livesey_house_data[livesey_house_data['Year'] <= 2015]\n",
"test_data = livesey_house_data[livesey_house_data['Year'] == 2016]\n",
"\n",
"# Define features (Year, Month, Temperature) and target (Gas Consumption)\n",
"X_train = train_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_train = train_data['GasConsumption_kWh']\n",
"X_test = test_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_test = test_data['GasConsumption_kWh']\n",
"\n",
"# Train the Random Forest model\n",
"rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
"rf_model.fit(X_train, y_train)\n",
"\n",
"# Make predictions on the test set\n",
"y_pred_rf = rf_model.predict(X_test)\n",
"\n",
"# Evaluate the model\n",
"mae_rf = mean_absolute_error(y_test, y_pred_rf)\n",
"rmse_rf = np.sqrt(mean_squared_error(y_test, y_pred_rf))\n",
"r2_rf = r2_score(y_test, y_pred_rf)\n",
"\n",
"# Display evaluation metrics\n",
"print(f\"Random Forest Results (2016):\")\n",
"print(f\"Mean Absolute Error (MAE): {mae_rf:.2f} kWh\")\n",
"print(f\"Root Mean Squared Error (RMSE): {rmse_rf:.2f} kWh\")\n",
"print(f\"R² Score: {r2_rf:.3f}\")\n",
"\n",
"# Display predicted and actual values\n",
"predicted_vs_actual_rf = test_data.copy()\n",
"predicted_vs_actual_rf['Predicted_kWh'] = y_pred_rf\n",
"print(predicted_vs_actual_rf[['Date', 'GasConsumption_kWh', 'Predicted_kWh']])\n",
"\n",
"# Visualize predicted vs actual values for 2016\n",
"plt.figure(figsize=(10, 6))\n",
"plt.plot(test_data['Date'], y_test, label='Actual Consumption', marker='o')\n",
"plt.plot(test_data['Date'], y_pred_rf, label='Predicted Consumption', marker='x')\n",
"plt.xlabel('Date')\n",
"plt.ylabel('Gas Consumption (kWh)')\n",
"plt.title('Actual vs Predicted Gas Consumption (2016) Livesey House')\n",
"plt.legend()\n",
"plt.grid(True)\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"id": "b897355c-7026-4f49-b340-2349b310c55a",
"metadata": {},
"source": [
"## Random Forest Model Analysis for Livesey House (2016)\n",
"\n",
"### Model Performance Metrics\n",
"The Random Forest model achieved the following performance metrics when predicting gas consumption for Livesey House in 2016:\n",
"\n",
"- **Mean Absolute Error (MAE):** **4,716.15 kWh**\n",
" - On average, the model's predictions deviate from the actual gas consumption by approximately 4,716.15 kWh.\n",
"- **Root Mean Squared Error (RMSE):** **6,325.34 kWh**\n",
" - The RMSE penalizes larger errors more heavily, providing a measure of overall accuracy.\n",
"- **R² Score:** **0.907**\n",
" - The model explains 90.7% of the variance in gas consumption, indicating strong predictive performance.\n",
"\n",
"### Predicted vs. Actual Gas Consumption (2016)\n",
"The table below compares the actual and predicted gas consumption for Livesey House in 2016:\n",
"\n",
"| **Date** | **Actual Consumption (kWh)** | **Predicted Consumption (kWh)** |\n",
"|----------------|------------------------------|----------------------------------|\n",
"| 2016-01-31 | 44,521.23 | 53,301.16 |\n",
"| 2016-02-29 | 49,879.95 | 56,888.60 |\n",
"| 2016-03-31 | 53,280.31 | 52,675.38 |\n",
"| 2016-04-30 | 44,500.30 | 51,522.67 |\n",
"| 2016-05-31 | 22,460.13 | 11,954.99 |\n",
"| 2016-06-30 | 2,327.30 | 696.93 |\n",
"| 2016-07-31 | 0.00 | 167.96 |\n",
"| 2016-08-31 | 0.00 | 216.16 |\n",
"| 2016-09-30 | 0.00 | 412.14 |\n",
"| 2016-10-31 | 20,254.29 | 29,968.97 |\n",
"| 2016-11-30 | 45,611.88 | 46,342.33 |\n",
"| 2016-12-31 | 37,202.96 | 47,004.04 |\n",
"\n",
"### Key Insights\n",
"1. **High Predictive Accuracy:**\n",
" - The Random Forest model demonstrates strong performance with an R² score of 0.907, meaning it explains the majority of variance in the data.\n",
"\n",
"2. **Seasonal Trends:**\n",
" - The model accurately captures higher consumption during the colder months (e.g., January, February, and December).\n",
" - Predictions for summer months (e.g., July, August, and September) align well with the near-zero actual consumption.\n",
"\n",
"3. **Residual Errors:**\n",
" - Larger prediction errors are observed for transitional months such as May and October, suggesting potential improvements by adding additional seasonal or operational features.\n",
"\n",
"### Visualization\n",
"The following line plot compares the actual and predicted gas consumption for Livesey House in 2016:\n",
"\n",
"- **Blue Line:** Actual consumption.\n",
"- **Orange Line:** Predicted consumption.\n",
"\n",
"### Conclusion\n",
"The Random Forest model provides reliable predictions for Livesey House in 2016, accurately reflecting seasonal variations and achieving strong performance metrics. Further refinements could focus on improving predictions during transitional months to reduce residual errors further.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 125,
"id": "26deab5c-c9d2-4946-b46a-e2a4dca47172",
"metadata": {},
"outputs": [
{
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" Gas Consumption (kWh)\n",
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},
"execution_count": 125,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Filter the data for the Kirkham building\n",
"kirkham_data = gas_data[gas_data['Site'] == 'Kirkham']\n",
"\n",
"# Transpose the data to have months as a time-series format\n",
"kirkham_data_clean = kirkham_data.drop(columns=['Site', 'Units']).transpose()\n",
"kirkham_data_clean.columns = ['Gas Consumption (kWh)']\n",
"\n",
"# Convert the index to datetime, assuming the columns represent monthly data\n",
"kirkham_data_clean.index = pd.date_range(start='2010-01', periods=len(kirkham_data_clean), freq='ME')\n",
"\n",
"# Display the cleaned data to ensure correctness\n",
"kirkham_data_clean.head()\n"
]
},
{
"cell_type": "code",
"execution_count": 123,
"id": "348e01ab-f1f2-493d-95e2-20aed5b6655d",
"metadata": {},
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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"# Plot the gas consumption for the Kirkham building\n",
"plt.figure(figsize=(12, 6))\n",
"plt.plot(kirkham_data_clean.index, kirkham_data_clean['Gas Consumption (kWh)'], \n",
" marker='o', linestyle='-', label='Gas Consumption (kWh)')\n",
"plt.title('Gas Consumption Over Time - Kirkham Building', fontsize=14)\n",
"plt.xlabel('Date', fontsize=12)\n",
"plt.ylabel('Gas Consumption (kWh)', fontsize=12)\n",
"plt.grid(True)\n",
"plt.legend()\n",
"plt.tight_layout()\n",
"plt.show()\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "50e79149-3812-41ba-85ec-7981e39dc5a6",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "d78df728-82a9-40ac-8139-80c41ad9d929",
"metadata": {},
"outputs": [],
"source": [
"# Filter data for Livesey House\n",
"livesey_house_data = gas_data[gas_data['Site'] == 'Livesey House']\n",
"\n",
"# Drop unnecessary columns and reset index\n",
"livesey_house_data = livesey_house_data.drop(columns=['Site', 'Units']).reset_index(drop=True)\n",
"\n",
"# Transpose the data for proper structure\n",
"livesey_house_data = livesey_house_data.T\n",
"livesey_house_data.columns = ['GasConsumption_kWh']\n",
"\n",
"# Generate a Date column based on the time period\n",
"livesey_house_data['Date'] = pd.date_range(start='2010-01-01', periods=len(livesey_house_data), freq='ME')\n",
"\n",
"# Reset index\n",
"livesey_house_data = livesey_house_data.reset_index(drop=True)\n",
"\n",
"# Display the cleaned data\n",
"livesey_house_data.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "40f8612b-0c82-4e5a-ba0c-a717da51e7e0",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "fdf73420-7f2a-4744-9dc7-b8410b6ca5f9",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "742867be-28cc-41bf-bacc-ad19a57f6ada",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "9b7122a2-17ed-43ec-95ef-64cf98a24a66",
"metadata": {},
"source": [
"### Decomposition of Gas Consumption Time Series - Kirkham Building\n",
"\n",
"The decomposition of the time series reveals the following:\n",
"\n",
"1. **Original Time Series**: \n",
" - Displays monthly gas consumption trends from 2010 onwards. \n",
" - Seasonal peaks occur in winter months, with lower consumption in summer. \n",
" - An overall declining trend is observed over the years.\n",
"\n",
"2. **Trend Component**: \n",
" - Highlights a steady reduction in gas usage over time, potentially due to energy efficiency measures or changes in building operations.\n",
"\n",
"3. **Seasonal Component**: \n",
" - Shows recurring annual patterns with higher consumption during colder months, reflecting heating needs. \n",
"\n",
"4. **Residual Component**: \n",
" - Captures irregular fluctuations not explained by trend or seasonality. \n",
" - Spikes in residuals may indicate anomalies, such as unusual building activity or system inefficiencies.\n",
"\n",
"**Key Insight**: \n",
"The Kirkham building exhibits clear seasonal heating patterns and a long-term reduction in gas consumption, with some residual anomalies worth further investigation.\n"
]
},
{
"cell_type": "code",
"execution_count": 121,
"id": "402ef999-2209-4231-bd0d-722c0dc3240f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mean Absolute Error (MAE): 6577.29 kWh\n",
"Root Mean Squared Error (RMSE): 7644.53 kWh\n",
"R² Score: 0.869\n",
" Date GasConsumption_kWh Predicted_kWh\n",
"108 2019-01-31 61903.38 53886.591378\n",
"109 2019-02-28 44119.76 43779.534052\n",
"110 2019-03-31 44909.12 38786.508723\n",
"111 2019-04-30 33723.26 33793.483394\n",
"112 2019-05-31 16595.75 23686.426067\n",
"113 2019-06-30 0.00 8465.336743\n",
"114 2019-07-31 0.00 -6755.752581\n",
"115 2019-08-31 0.00 -1520.713915\n",
"116 2019-09-30 158.28 8828.356750\n",
"117 2019-10-31 16185.32 29405.491410\n",
"118 2019-11-30 38989.17 49982.626070\n",
"119 2019-12-31 42442.18 50103.632738\n"
]
}
],
"source": [
"# Importing necessary libraries\n",
"import pandas as pd\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
"import numpy as np\n",
"\n",
"# Load gas consumption data from the provided file\n",
"uclan_data_path = r'C:\\Users\\sheyi\\OneDrive\\Documents\\BuildingsProject\\UCLanPrestonBldDATA.xlsx'\n",
"uclan_gas_data = pd.ExcelFile(uclan_data_path).parse('GasData(kWh)')\n",
"\n",
"# Extract Livesey House gas consumption data\n",
"livesey_house_data = uclan_gas_data[uclan_gas_data['Site'] == 'Livesey House']\n",
"livesey_house_data = livesey_house_data.drop(columns=['Site', 'Units']).T\n",
"livesey_house_data.columns = ['GasConsumption_kWh']\n",
"\n",
"# Create a Date column\n",
"livesey_house_data['Date'] = pd.date_range(start='2010-01', periods=len(livesey_house_data), freq='ME')\n",
"\n",
"# Load temperature data from the provided file\n",
"temperature_data_path = r'C:\\Users\\sheyi\\OneDrive\\Documents\\BuildingsProject\\Preston monthly avarage temperature data from 2010 to 2023.xlsx'\n",
"temperature_data = pd.ExcelFile(temperature_data_path).parse('Temperature')\n",
"\n",
"# Clean and prepare temperature data\n",
"temperature_data['Date'] = pd.to_datetime(\n",
" temperature_data['Year'].astype(str) + '-' + temperature_data['Month'], format='%Y-%B'\n",
")\n",
"temperature_data['Date'] = temperature_data['Date'] + pd.offsets.MonthEnd(0)\n",
"temperature_data = temperature_data[['Date', 'Preston Temperature in C']]\n",
"\n",
"# Merge gas consumption data with temperature data\n",
"livesey_house_data = pd.merge(livesey_house_data, temperature_data, on='Date', how='inner')\n",
"\n",
"# Add 'Year' and 'Month' columns for feature engineering\n",
"livesey_house_data['Year'] = livesey_house_data['Date'].dt.year\n",
"livesey_house_data['Month'] = livesey_house_data['Date'].dt.month\n",
"\n",
"# Split data into training (2010-2018) and testing (2019)\n",
"train_data = livesey_house_data[livesey_house_data['Year'] < 2019]\n",
"test_data = livesey_house_data[livesey_house_data['Year'] == 2019]\n",
"\n",
"# Define features (Year, Month, Temperature) and target (Gas Consumption)\n",
"X_train = train_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_train = train_data['GasConsumption_kWh']\n",
"X_test = test_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_test = test_data['GasConsumption_kWh']\n",
"\n",
"# Train the regression model\n",
"model_with_temp = LinearRegression()\n",
"model_with_temp.fit(X_train, y_train)\n",
"\n",
"# Make predictions on the test set\n",
"y_pred_with_temp = model_with_temp.predict(X_test)\n",
"\n",
"# Evaluate the model\n",
"mae_with_temp = mean_absolute_error(y_test, y_pred_with_temp)\n",
"rmse_with_temp = np.sqrt(mean_squared_error(y_test, y_pred_with_temp))\n",
"r2_with_temp = r2_score(y_test, y_pred_with_temp)\n",
"\n",
"# Display evaluation metrics\n",
"print(f\"Mean Absolute Error (MAE): {mae_with_temp:.2f} kWh\")\n",
"print(f\"Root Mean Squared Error (RMSE): {rmse_with_temp:.2f} kWh\")\n",
"print(f\"R² Score: {r2_with_temp:.3f}\")\n",
"\n",
"# Display predicted and actual values\n",
"predicted_vs_actual = test_data.copy()\n",
"predicted_vs_actual['Predicted_kWh'] = y_pred_with_temp\n",
"print(predicted_vs_actual[['Date', 'GasConsumption_kWh', 'Predicted_kWh']])\n"
]
},
{
"cell_type": "markdown",
"id": "56f1aa91-3485-4cd3-adc9-94bb2a25e545",
"metadata": {},
"source": [
"## Linear Regression Model Analysis\r\n",
"\r\n",
"### Model Performance Metrics\r\n",
"The Linear Regression model achieved the following performance metrics:\r\n",
"\r\n",
"- **Mean Absolute Error (MAE)**: **6,577.29 kWh**\r\n",
" - On average, the predictions deviate from the actual gas consumption by approximately 6,577.29 kWh.\r\n",
"- **Root Mean Squared Error (RMSE)**: **7,644.53 kWh**\r\n",
" - The RMSE penalizes larger errors more heavily, indicating areas where predictions deviate significantly from actual values.\r\n",
"- **R² Score**: **0.869**\r\n",
" - The model explains 86.9% of the variance in gas consumption, which is strong but not as high as the Random Forest model.\r\n",
"\r\n",
"### Predicted vs. Actual Gas Consumption (2019)\r\n",
"The table below compares the predicted and actual gas consumption for Livesey House in 2019:\r\n",
"\r\n",
"| **Date** | **Actual Consumption (kWh)** | **Predicted Consumption (kWh)** |\r\n",
"|----------------|------------------------------|----------------------------------|\r\n",
"| 2019-01-31 | 61,903.38 | 53,886.59 |\r\n",
"| 2019-02-28 | 44,119.76 | 43,779.53 |\r\n",
"| 2019-03-31 | 44,909.12 | 38,786.51 |\r\n",
"| 2019-04-30 | 33,723.26 | 33,793.48 |\r\n",
"| 2019-05-31 | 16,595.75 | 23,686.43 |\r\n",
"| 2019-06-30 | 0.00 | 8,465.34 |\r\n",
"| 2019-07-31 | 0.00 | -6,755.75 |\r\n",
"| 2019-08-31 | 0.00 | -1,520.71 |\r\n",
"| 2019-09-30 | 158.28 | 8,828.36 |\r\n",
"| 2019-10-31 | 16,185.32 | 29,405.49 |\r\n",
"| 2019-11-30 | 38,989.17 | 49,982.63 |\r\n",
"| 2019-12-31 | 42,442.18 | 50,103.63 |\r\n",
"\r\n",
"### Key Insights\r\n",
"1. **Accuracy**:\r\n",
" - While the Linear Regression model performs reasonably well, it falls short compared to the Random Forest model, as evidenced by higher error metrics and a lower R² score.\r\n",
"\r\n",
"2. **Limitations**:\r\n",
" - Negative predictions for low-consumption months (e.g., July and August) highlight the model's inability to handle the non-linear nature of gas consumption patterns effectively.\r\n",
" - Predictions during summer months overestimate actual consumption.\r\n",
"\r\n",
"3. **Seasonality Reflected**:\r\n",
" - Despite limitations, the model captures general seasonal trends, predicting higher consumption in winter months and lower in summer.\r\n",
"\r\n",
"### Recommendations\r\n",
"- **Switch to Non-Linear Models**:\r\n",
" - Models like Random Forest or Gradient Boosting are better suited for capturing non-linear relationships and seasonality.\r\n",
"- **Feature Engineering**:\r\n",
" - Incorporate additional features, such as seasonal indicators or operational data, to improve accuracy.\r\n",
"- **Residual Analysis**:\r\n",
" - Analyze residuals to identify systematic biases in the model and address them.\r\n",
"\r\n",
"The Linear Regression model provides a baseline for prediction but has significant limitations compared to the Random Forest model.\r\n"
]
},
{
"cell_type": "code",
"execution_count": 119,
"id": "66986b55-213e-42a2-82cc-669d525b1db7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Random Forest Results:\n",
"Mean Absolute Error (MAE): 2741.32 kWh\n",
"Root Mean Squared Error (RMSE): 4173.44 kWh\n",
"R² Score: 0.961\n",
" Date GasConsumption_kWh Predicted_kWh\n",
"108 2019-01-31 61903.38 58353.318150\n",
"109 2019-02-28 44119.76 52634.586344\n",
"110 2019-03-31 44909.12 45036.396622\n",
"111 2019-04-30 33723.26 33520.605626\n",
"112 2019-05-31 16595.75 17811.027373\n",
"113 2019-06-30 0.00 442.187000\n",
"114 2019-07-31 0.00 90.670930\n",
"115 2019-08-31 0.00 777.962900\n",
"116 2019-09-30 158.28 214.554079\n",
"117 2019-10-31 16185.32 22761.127639\n",
"118 2019-11-30 38989.17 47305.258450\n",
"119 2019-12-31 42442.18 45468.982200\n"
]
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Importing necessary libraries\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
"import numpy as np\n",
"\n",
"# Load gas consumption data from the provided file\n",
"uclan_data_path = uclan_data_path = r'C:\\Users\\sheyi\\OneDrive\\Documents\\BuildingsProject\\UCLanPrestonBldDATA.xlsx'\n",
"uclan_gas_data = pd.ExcelFile(uclan_data_path).parse('GasData(kWh)')\n",
"\n",
"# Extract Livesey House gas consumption data\n",
"livesey_house_data = uclan_gas_data[uclan_gas_data['Site'] == 'Livesey House']\n",
"livesey_house_data = livesey_house_data.drop(columns=['Site', 'Units']).T\n",
"livesey_house_data.columns = ['GasConsumption_kWh']\n",
"\n",
"# Create a Date column\n",
"livesey_house_data['Date'] = pd.date_range(start='2010-01', periods=len(livesey_house_data), freq='ME')\n",
"\n",
"# Load temperature data from the provided file\n",
"temperature_data_path = r'C:\\Users\\sheyi\\OneDrive\\Documents\\BuildingsProject\\Preston monthly avarage temperature data from 2010 to 2023.xlsx'\n",
"temperature_data = pd.ExcelFile(temperature_data_path).parse('Temperature')\n",
"\n",
"# Clean and prepare temperature data\n",
"temperature_data['Date'] = pd.to_datetime(\n",
" temperature_data['Year'].astype(str) + '-' + temperature_data['Month'], format='%Y-%B'\n",
")\n",
"temperature_data['Date'] = temperature_data['Date'] + pd.offsets.MonthEnd(0)\n",
"temperature_data = temperature_data[['Date', 'Preston Temperature in C']]\n",
"\n",
"# Merge gas consumption data with temperature data\n",
"livesey_house_data = pd.merge(livesey_house_data, temperature_data, on='Date', how='inner')\n",
"\n",
"# Add 'Year' and 'Month' columns for feature engineering\n",
"livesey_house_data['Year'] = livesey_house_data['Date'].dt.year\n",
"livesey_house_data['Month'] = livesey_house_data['Date'].dt.month\n",
"\n",
"# Split data into training (2010-2018) and testing (2019)\n",
"train_data = livesey_house_data[livesey_house_data['Year'] < 2019]\n",
"test_data = livesey_house_data[livesey_house_data['Year'] == 2019]\n",
"\n",
"# Define features (Year, Month, Temperature) and target (Gas Consumption)\n",
"X_train = train_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_train = train_data['GasConsumption_kWh']\n",
"X_test = test_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_test = test_data['GasConsumption_kWh']\n",
"\n",
"# Train the Random Forest model\n",
"rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
"rf_model.fit(X_train, y_train)\n",
"\n",
"# Make predictions on the test set\n",
"y_pred_rf = rf_model.predict(X_test)\n",
"\n",
"# Evaluate the model\n",
"mae_rf = mean_absolute_error(y_test, y_pred_rf)\n",
"rmse_rf = np.sqrt(mean_squared_error(y_test, y_pred_rf))\n",
"r2_rf = r2_score(y_test, y_pred_rf)\n",
"\n",
"# Display evaluation metrics\n",
"print(f\"Random Forest Results:\")\n",
"print(f\"Mean Absolute Error (MAE): {mae_rf:.2f} kWh\")\n",
"print(f\"Root Mean Squared Error (RMSE): {rmse_rf:.2f} kWh\")\n",
"print(f\"R² Score: {r2_rf:.3f}\")\n",
"\n",
"# Display predicted and actual values\n",
"predicted_vs_actual_rf = test_data.copy()\n",
"predicted_vs_actual_rf['Predicted_kWh'] = y_pred_rf\n",
"print(predicted_vs_actual_rf[['Date', 'GasConsumption_kWh', 'Predicted_kWh']])\n",
"\n",
"\n",
"\n",
"# Visualize predicted vs actual values\n",
"plt.figure(figsize=(10, 6))\n",
"plt.plot(test_data['Date'], y_test, label='Actual Consumption', marker='o')\n",
"plt.plot(test_data['Date'], y_pred_rf, label='Predicted Consumption', marker='x')\n",
"plt.xlabel('Date')\n",
"plt.ylabel('Gas Consumption (kWh)')\n",
"plt.title('Actual vs Predicted Gas Consumption (2019)')\n",
"plt.legend()\n",
"plt.grid(True)\n",
"plt.show()\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "db2440c6-73a6-4edc-b0fa-17e0134c88bb",
"metadata": {},
"source": [
"## Random Forest Model Analysis\n",
"\n",
"### Model Performance Metrics\n",
"The Random Forest model achieved the following performance metrics:\n",
"\n",
"- **Mean Absolute Error (MAE)**: **2,741.32 kWh**\n",
" - This indicates that, on average, the model's predictions deviate from the actual gas consumption by approximately 2,741.32 kWh.\n",
"- **Root Mean Squared Error (RMSE)**: **4,173.44 kWh**\n",
" - The RMSE penalizes larger errors more heavily than the MAE, reflecting overall model accuracy.\n",
"- **R² Score**: **0.961**\n",
" - The model explains 96.1% of the variance in gas consumption, indicating excellent predictive performance.\n",
"\n",
"### Predicted vs. Actual Gas Consumption (2019)\n",
"The table below compares the predicted and actual gas consumption for Livesey House in 2019:\n",
"\n",
"| **Date** | **Actual Consumption (kWh)** | **Predicted Consumption (kWh)** |\n",
"|----------------|------------------------------|----------------------------------|\n",
"| 2019-01-31 | 61,903.38 | 58,353.32 |\n",
"| 2019-02-28 | 44,119.76 | 52,634.59 |\n",
"| 2019-03-31 | 44,909.12 | 45,036.40 |\n",
"| 2019-04-30 | 33,723.26 | 33,520.61 |\n",
"| 2019-05-31 | 16,595.75 | 17,811.03 |\n",
"| 2019-06-30 | 0.00 | 442.19 |\n",
"| 2019-07-31 | 0.00 | 90.67 |\n",
"| 2019-08-31 | 0.00 | 777.96 |\n",
"| 2019-09-30 | 158.28 | 214.55 |\n",
"| 2019-10-31 | 16,185.32 | 22,761.13 |\n",
"| 2019-11-30 | 38,989.17 | 47,305.26 |\n",
"| 2019-12-31 | 42,442.18 | 45,468.98 |\n",
"\n",
"### Key Insights\n",
"1. **High Accuracy**:\n",
" - The Random Forest model demonstrates exceptional performance, with a low MAE and RMSE, and an excellent R² score of 0.961.\n",
" - Negative predictions, which occurred in linear regression, are avoided.\n",
"\n",
"2. **Seasonality Reflected**:\n",
" - Predictions closely follow the seasonal trends, with higher values in winter months and near-zero predictions during summer months when heating is minimal.\n",
"\n",
"3. **Room for Improvement**:\n",
" - Predictions for low-consumption months (e.g., summer) could still be refined further to reduce over-prediction.\n",
"\n",
"\n",
"\n",
"## Predicted vs. Actual Gas Consumption Plot\r\n",
"\r\n",
"### Purpose of the Plot\r\n",
"The scatter plot visualizes the relationship between the **predicted** and **actual gas consumption** values for Livesey House in 2019, providing a way to assess the model's performance visuallact overall performance.\r\n",
"\r\n",
"### Interpretation\r\n",
"- The Random Forest model effectively captures the seasonal trends and variability in gas consumption.\r\n",
"- The clustering of points near the red line confirms high accuracy, as reflected in the performance metrics (MAE, RMSE, and R²).\r\n",
"\r\n",
"### Conclusion\r\n",
"The scatter plot reinforces the reliability of the Random Forest model for predicting gas consumption, while highlighting potential areas (e.g., low-consumption mobust and reliable performance.\n",
"\n",
"The Random Forest model provides a robust solution for predicting energy consumption, handling complex, non-linear data effectively while maintaining high accuracy.\n"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "04980c61-31ac-4d38-9e56-371347133a0d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Feature Importance:\n",
" Feature Importance\n",
"2 Preston Temperature in C 0.909685\n",
"1 Month 0.052893\n",
"0 Year 0.037421\n"
]
}
],
"source": [
"# Feature Importance\n",
"feature_importances = rf_model.feature_importances_\n",
"features = ['Year', 'Month', 'Preston Temperature in C']\n",
"importance_df = pd.DataFrame({\n",
" 'Feature': features,\n",
" 'Importance': feature_importances\n",
"}).sort_values(by='Importance', ascending=False)\n",
"\n",
"# Print feature importance\n",
"print(\"Feature Importance:\")\n",
"print(importance_df)"
]
},
{
"cell_type": "markdown",
"id": "1dddef33-119b-4ba5-a14f-1b7faa5d337f",
"metadata": {},
"source": [
"## Feature Importance Analysis for Random Forest Model\n",
"\n",
"### Purpose of Feature Importance\n",
"Feature importance analysis helps to understand which variables have the most significant impact on the predictions made by the Random Forest model. By ranking the importance of features, we can:\n",
"\n",
"- Identify key drivers of gas consumption.\n",
"- Simplify the model by removing less important features.\n",
"- Gain insights into the relationships between predictors and the target variable.\n",
"\n",
"### Feature Importance Results\n",
"Based on the Random Forest model trained on the dataset, the relative importance of features is as follows:\n",
"\n",
"| **Feature** | **Importance** |\n",
"|-------------------------------|----------------|\n",
"| Preston Temperature in C | 90.97% |\n",
"| Month | 5.29% |\n",
"| Year | 3.74% |\n",
"\n",
"_Note: Replace the example percentages with actual values from your results._\n",
"\n",
"### Observations\n",
"1. **Temperature Dominance**:\n",
" - `Preston Temperature in C` is the most critical predictor of gas consumption, reflecting its strong influence on heating requirements.\n",
"\n",
"2. **Seasonal Effects**:\n",
" - `Month` is moderately important, indicating the role of seasonal changes in energy consumption patterns.\n",
"\n",
"3. **Yearly Trends**:\n",
" - `Year` has the least importance, suggesting minimal variation in gas consumption across years in the dataset.\n",
"\n",
"### Visualization\n",
"The following bar chart illustrates the relative importance of features:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "c1685e93-f58b-45a0-8fce-1702652fccdd",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Visualize feature importance\n",
"plt.figure(figsize=(8, 6))\n",
"plt.barh(importance_df['Feature'], importance_df['Importance'], color='skyblue')\n",
"plt.xlabel('Importance')\n",
"plt.ylabel('Feature')\n",
"plt.title('Feature Importance for Random Forest')\n",
"plt.gca().invert_yaxis() # Invert y-axis to show the most important feature at the top\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "017afc18-bec4-4061-8ebf-4fa3c51f0ad0",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "239484dd-f070-4109-8378-7c6c3182cedd",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 137,
"id": "13b52d5d-79aa-417b-ae03-68b0547f763e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Random Forest Results:\n",
"Mean Absolute Error (MAE): 2929.20 kWh\n",
"Root Mean Squared Error (RMSE): 4177.25 kWh\n",
"R² Score: 0.970\n",
" Date GasConsumption_kWh Predicted_kWh\n",
"108 2019-01-31 70209.26 70045.830800\n",
"109 2019-02-28 48932.41 51321.963242\n",
"110 2019-03-31 50120.50 45202.751927\n",
"111 2019-04-30 30997.93 35607.786485\n",
"112 2019-05-31 14734.54 17583.606142\n",
"113 2019-06-30 1954.84 2385.623500\n",
"114 2019-07-31 2083.12 1755.522018\n",
"115 2019-08-31 1830.87 1767.239700\n",
"116 2019-09-30 2170.73 3548.858361\n",
"117 2019-10-31 28585.00 38059.038133\n",
"118 2019-11-30 51351.87 58913.670786\n",
"119 2019-12-31 57026.72 58011.499800\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Importing necessary libraries\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
"import numpy as np\n",
"\n",
"# Load gas consumption data from the provided file\n",
"uclan_data_path = uclan_data_path = r'C:\\Users\\sheyi\\OneDrive\\Documents\\BuildingsProject\\UCLanPrestonBldDATA.xlsx'\n",
"uclan_gas_data = pd.ExcelFile(uclan_data_path).parse('GasData(kWh)')\n",
"\n",
"# Extract Livesey House gas consumption data\n",
"Kirkham_data = uclan_gas_data[uclan_gas_data['Site'] == 'Kirkham']\n",
"Kirkham_data = Kirkham_data.drop(columns=['Site', 'Units']).T\n",
"Kirkham_data.columns = ['GasConsumption_kWh']\n",
"\n",
"# Create a Date column\n",
"Kirkham_data['Date'] = pd.date_range(start='2010-01', periods=len(Kirkham_data), freq='ME')\n",
"\n",
"# Load temperature data from the provided file\n",
"temperature_data_path = r'C:\\Users\\sheyi\\OneDrive\\Documents\\BuildingsProject\\Preston monthly avarage temperature data from 2010 to 2023.xlsx'\n",
"temperature_data = pd.ExcelFile(temperature_data_path).parse('Temperature')\n",
"\n",
"# Clean and prepare temperature data\n",
"temperature_data['Date'] = pd.to_datetime(\n",
" temperature_data['Year'].astype(str) + '-' + temperature_data['Month'], format='%Y-%B'\n",
")\n",
"temperature_data['Date'] = temperature_data['Date'] + pd.offsets.MonthEnd(0)\n",
"temperature_data = temperature_data[['Date', 'Preston Temperature in C']]\n",
"\n",
"# Merge gas consumption data with temperature data\n",
"Kirkham_data = pd.merge(Kirkham_data, temperature_data, on='Date', how='inner')\n",
"\n",
"# Add 'Year' and 'Month' columns for feature engineering\n",
"Kirkham_data['Year'] = Kirkham_data['Date'].dt.year\n",
"Kirkham_data['Month'] = Kirkham_data['Date'].dt.month\n",
"\n",
"# Split data into training (2010-2018) and testing (2019)\n",
"train_data = Kirkham_data[Kirkham_data['Year'] < 2019]\n",
"test_data = Kirkham_data[Kirkham_data['Year'] == 2019]\n",
"\n",
"# Define features (Year, Month, Temperature) and target (Gas Consumption)\n",
"X_train = train_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_train = train_data['GasConsumption_kWh']\n",
"X_test = test_data[['Year', 'Month', 'Preston Temperature in C']]\n",
"y_test = test_data['GasConsumption_kWh']\n",
"\n",
"# Train the Random Forest model\n",
"rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
"rf_model.fit(X_train, y_train)\n",
"\n",
"# Make predictions on the test set\n",
"y_pred_rf = rf_model.predict(X_test)\n",
"\n",
"# Evaluate the model\n",
"mae_rf = mean_absolute_error(y_test, y_pred_rf)\n",
"rmse_rf = np.sqrt(mean_squared_error(y_test, y_pred_rf))\n",
"r2_rf = r2_score(y_test, y_pred_rf)\n",
"\n",
"# Display evaluation metrics\n",
"print(f\"Random Forest Results:\")\n",
"print(f\"Mean Absolute Error (MAE): {mae_rf:.2f} kWh\")\n",
"print(f\"Root Mean Squared Error (RMSE): {rmse_rf:.2f} kWh\")\n",
"print(f\"R² Score: {r2_rf:.3f}\")\n",
"\n",
"# Display predicted and actual values\n",
"predicted_vs_actual_rf = test_data.copy()\n",
"predicted_vs_actual_rf['Predicted_kWh'] = y_pred_rf\n",
"print(predicted_vs_actual_rf[['Date', 'GasConsumption_kWh', 'Predicted_kWh']])\n",
"\n",
"\n",
"\n",
"# Visualize predicted vs actual values\n",
"plt.figure(figsize=(10, 6))\n",
"plt.plot(test_data['Date'], y_test, label='Actual Consumption', marker='o')\n",
"plt.plot(test_data['Date'], y_pred_rf, label='Predicted Consumption', marker='x')\n",
"plt.xlabel('Date')\n",
"plt.ylabel('Gas Consumption (kWh)')\n",
"plt.title('Actual vs Predicted Gas Consumption Kirkh (2019)')\n",
"plt.legend()\n",
"plt.grid(True)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "4e74f25f-9cc7-4c08-9a76-6cd68e768b35",
"metadata": {},
"source": [
"## space ##"
]
},
{
"cell_type": "code",
"execution_count": 169,
"id": "8936e6a4-1f27-4fcd-ae95-e7b16c9417fb",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Seasonal patterns\n",
"Kirkham_data['Year'] = Kirkham_data['Date'].dt.year\n",
"Kirkham_data['Month'] = Kirkham_data['Date'].dt.month\n",
"\n",
"plt.figure(figsize=(12, 6))\n",
"sns.boxplot(data=Kirkham_data, x='Month', y='GasConsumption_kWh')\n",
"plt.title('Monthly Energy Consumption Patterns - Kirkham Building', fontsize=14)\n",
"plt.xlabel('Month', fontsize=12)\n",
"plt.ylabel('Gas Consumption (kWh)', fontsize=12)\n",
"plt.grid(True, linestyle='--', alpha=0.7)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "ca9c6756-1095-42e4-96a1-02ee8713de47",
"metadata": {},
"source": [
"## space ##"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a700db2a-f735-4a8b-bf25-12ef112e5537",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "f3625673-1d61-44c1-98ee-21df7dfd68f5",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.12.4"
}
},
"nbformat": 4,
"nbformat_minor": 5
}