Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage
Yunshou Mao1,2, Zhihong Cai3, Xianan Jiao4
1School of Electronic Information and Electrical Engineering, Huizhou University, Huizhou, 516007, Guangdong, P.R. China.
Scientific Reports
|March 13, 2025
Summary
This study optimizes comprehensive energy systems by integrating generalized energy storage, including electric vehicles (EVs) and hydrogen storage, across multiple timescales. This multi-timescale approach significantly reduces operational costs and improves system reliability.
Area of Science:
- Energy Systems Engineering
- Optimization Theory
- Renewable Energy Integration
Background:
- Existing research often overlooks coordinated multi-timescale optimization of diverse energy storage resources in comprehensive energy systems.
- Single-sided resource focus and two-timescale optimization limit the holistic management of energy systems.
Purpose of the Study:
- To develop and validate a multi-timescale optimization strategy for comprehensive energy systems.
- To integrate flexible demand-side resources as generalized energy storage, including electric vehicles (EVs), hydrogen storage, and air conditioning (AC) clusters.
- To minimize the operational costs of comprehensive energy systems across day-ahead, intraday, and real-time stages.
Main Methods:
- An optimization scheduling model for mobile energy storage, hydrogen storage, and virtual energy storage of AC clusters was established, considering physical and temporal constraints.
- The day-ahead stage utilized the C&CG method to handle uncertainties in wind and photovoltaic power generation.
- Intraday and real-time stages employed hydrogen storage, gas turbines, and AC virtual energy storage for mitigating renewable energy fluctuations and rapid response.
Main Results:
- The proposed multi-timescale optimization model effectively reduces operational costs in comprehensive energy systems.
- Integration of generalized energy storage, including EVs and AC clusters, enhances system reliability.
- Case studies confirmed the significant economic and reliability benefits of the developed optimization strategy.
Conclusions:
- Coordinated multi-timescale optimization of generalized energy storage is crucial for efficient and reliable comprehensive energy systems.
- Flexible demand-side resources can be effectively utilized as generalized energy storage to improve system performance.
- The study provides a robust framework for optimizing energy system operations under renewable energy variability.
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