Multi energy load and renewable energy scenario dataset

Citation Author(s):
Qinglin
Meng
Submitted by:
QingLin Meng
Last updated:
Fri, 12/27/2024 - 03:01
DOI:
10.21227/vq8s-1x22
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Abstract 

This dataset is sourced from an integrated energy system in a region of northern China, encompassing a wide range of energy data including wind power, photovoltaic power, electricity load, thermal load, and cooling load. The dataset features a time resolution of one hour, with a 24-hour timescale for each selected day. A total of five typical days have been chosen, representing different seasonal and weather conditions, to capture the variations in energy production and consumption patterns. The dataset includes detailed information on wind and photovoltaic generation, fluctuations in electricity load, and the demand variations for both thermal and cooling loads. This dataset is designed to provide essential support for optimizing the scheduling of integrated energy systems, forecasting renewable energy generation, managing load demand, and enabling intelligent energy dispatching. Additionally, it serves as a valuable resource for energy policy development and long-term energy planning, offering insights into the interactions between renewable energy sources and demand-side management in real-world scenarios.

Instructions: 

The dataset selects 5 typical days, covering energy production and consumption characteristics under different seasonal and weather conditions. It includes data on wind power and photovoltaic generation, electricity load, thermal load, and cooling load demand variations. The dataset aims to support the optimization and scheduling of integrated energy systems, renewable energy generation forecasting, load management, and intelligent energy dispatching, while also providing foundational data for energy policy and planning.