# Energy Load and Power Forecasting

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/energy-load-and-power-forecasting/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the methods and techniques for forecasting electricity prices and load demand, with an emphasis on short-term forecasting using neural networks, ARIMA models, and probabilistic approaches. The cluster also covers topics related to wind power generation, deep learning applications, and renewable energy forecasting. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | t11052 |
| Works | 116 |

## Topic papers all

Showing 15 of 116.

- [Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques](https://scholariq.org/papers/predicting-stock-and-stock-price-index-movement-using-trend-deterministic-data/)
- [Short-term photovoltaic solar power forecasting using a hybrid Wavelet-PSO-SVM model based on SCADA and Meteorological information](https://scholariq.org/papers/short-term-photovoltaic-solar-power-forecasting-using-a-hybrid-wavelet-pso-svm/)
- [A Distributionally Robust Optimization Model for Unit Commitment Considering Uncertain Wind Power Generation](https://scholariq.org/papers/a-distributionally-robust-optimization-model-for-unit-commitment-considering/)
- [Physical energy and data-driven models in building energy prediction: A review](https://scholariq.org/papers/physical-energy-and-data-driven-models-in-building-energy-prediction-a-review/)
- [Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks](https://scholariq.org/papers/hourly-forecasting-of-solar-irradiance-based-on-ceemdan-and-multi-strategy-cnn/)
- [Fundamentals and business model for resource aggregator of demand response in electricity markets](https://scholariq.org/papers/fundamentals-and-business-model-for-resource-aggregator-of-demand-response-in/)
- [An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources](https://scholariq.org/papers/an-optimized-home-energy-management-system-with-integrated-renewable-energy-and/)
- [Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network](https://scholariq.org/papers/deep-learning-approach-for-short-term-stock-trends-prediction-based-on-two/)
- [Forecast Methods for Time Series Data: A Survey](https://scholariq.org/papers/forecast-methods-for-time-series-data-a-survey/)
- [Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM](https://scholariq.org/papers/time-series-forecasting-for-hourly-photovoltaic-power-using-conditional/)
- [Prediction of home energy consumption based on gradient boosting regression tree](https://scholariq.org/papers/prediction-of-home-energy-consumption-based-on-gradient-boosting-regression-tree/)
- [Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms](https://scholariq.org/papers/multi-step-ahead-forecasting-of-heat-load-in-district-heating-systems-using/)
- [An ANN-based Approach for Forecasting the Power Output of Photovoltaic System](https://scholariq.org/papers/an-ann-based-approach-for-forecasting-the-power-output-of-photovoltaic-system/)
- [Hybrid deep neural model for hourly solar irradiance forecasting](https://scholariq.org/papers/hybrid-deep-neural-model-for-hourly-solar-irradiance-forecasting/)
- [Machine Learning Based Photovoltaics (PV) Power Prediction Using Different Environmental Parameters of Qatar](https://scholariq.org/papers/machine-learning-based-photovoltaics-pv-power-prediction-using-different/)

## Topic primary papers

Showing 15 of 36.

- [Short-term photovoltaic solar power forecasting using a hybrid Wavelet-PSO-SVM model based on SCADA and Meteorological information](https://scholariq.org/papers/short-term-photovoltaic-solar-power-forecasting-using-a-hybrid-wavelet-pso-svm/)
- [Physical energy and data-driven models in building energy prediction: A review](https://scholariq.org/papers/physical-energy-and-data-driven-models-in-building-energy-prediction-a-review/)
- [Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks](https://scholariq.org/papers/hourly-forecasting-of-solar-irradiance-based-on-ceemdan-and-multi-strategy-cnn/)
- [Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM](https://scholariq.org/papers/time-series-forecasting-for-hourly-photovoltaic-power-using-conditional/)
- [Prediction of home energy consumption based on gradient boosting regression tree](https://scholariq.org/papers/prediction-of-home-energy-consumption-based-on-gradient-boosting-regression-tree/)
- [Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms](https://scholariq.org/papers/multi-step-ahead-forecasting-of-heat-load-in-district-heating-systems-using/)
- [Non-parametric hybrid models for wind speed forecasting](https://scholariq.org/papers/non-parametric-hybrid-models-for-wind-speed-forecasting/)
- [Support Vector Regression Model Based on Empirical Mode Decomposition and Auto Regression for Electric Load Forecasting](https://scholariq.org/papers/support-vector-regression-model-based-on-empirical-mode-decomposition-and-auto/)
- [A novel method based on time series ensemble model for hourly photovoltaic power prediction](https://scholariq.org/papers/a-novel-method-based-on-time-series-ensemble-model-for-hourly-photovoltaic-power/)
- [Parallel genetic algorithms for optimizing the SARIMA model for better forecasting of the NCDC weather data](https://scholariq.org/papers/parallel-genetic-algorithms-for-optimizing-the-sarima-model-for-better/)
- [Short-Term Electricity-Load Forecasting by deep learning: A comprehensive survey](https://scholariq.org/papers/short-term-electricity-load-forecasting-by-deep-learning-a-comprehensive-survey/)
- [Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM](https://scholariq.org/papers/improving-the-efficiency-of-multistep-short-term-electricity-load-forecasting/)
- [Numerical solving of the generalized Black-Scholes differential equation using Laguerre neural network](https://scholariq.org/papers/numerical-solving-of-the-generalized-black-scholes-differential-equation-using/)
- [Artificial humming bird with data science enabled stability prediction model for smart grids](https://scholariq.org/papers/artificial-humming-bird-with-data-science-enabled-stability-prediction-model-for/)
- [Machine learning methods for GEFCom2017 probabilistic load forecasting](https://scholariq.org/papers/machine-learning-methods-for-gefcom2017-probabilistic-load-forecasting/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.