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Risk-Based Reserve Scheduling for Active Distribution Networks Based on an Improved Proximal Policy Optimization Algorithm

Authors :
Xiaoyu Li
Xueshan Han
Ming Yang
Source :
IEEE Access, Vol 11, Pp 15211-15228 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

Achieving the coordinated optimization of tie-line reserve and energy storage on two timescales is a key issue in reserve scheduling for active distribution networks. To effectively manage the uncertainty related to renewable energy, we propose risk-based reserve scheduling for active distribution networks based on an improved proximal policy optimization algorithm. The reserve scheduling for active distribution networks is constructed as a two-scale multistage stochastic programming model, in which intraday real-time operation is constructed as a multi-stage stochastic programming model. With the help of more accurate and realistic intraday operation scenario simulation, the energy storage can be fully utilized to improve the system’s ability to climb and peak, reduce the reserve pressure of the main network, and achieve the purpose of improving the flexibility of system operation. An improved proximal policy optimization algorithm is proposed to solve optimization problems in a model-free manner while effectively handling conditional value-at-risk constraints. The effectiveness of the proposed risk-based reserve scheduling for active distribution networks based on an improved proximal policy optimization algorithm is verified by a modified IEEE33 case.

Details

Language :
English
ISSN :
21693536
Volume :
11
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.1a73db55afe7436398fed44ceb07a77a
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2022.3230670