Probabilistic Power Flow Optimization of Source Network Load Storage in AC/DC Systems Based on SOC Characteristics

• Published in: Electric power systems research 2024-03, Vol.228, p.110032, Article 110032
• Main Authors: Shu, Hongchun, Dai, Yue, Liao, Mengli, Tang, Yutao
• Format: Article
• Language: English
• Subjects: energy storage systems; probabilistic power flow; source network load storage; state of charge
• ISSN: 0378-7796
• DOI: 10.1016/j.epsr.2023.110032

•Establish a source-load dual-side uncertainty model and consider the correction of customer responsiveness under time-of-use price for the load side•Consider the SOC characteristics of the energy storage system and perform nodal equivalence•Establish the power flow calculation model of source grid load storage AC/DC system•Introduce penalty function to establish a multi-objective optimization model for probabilistic optimal power flow and improve the power flow distribution at time t The randomness and fluctuation of wind turbines and photovoltaics affect the optimal operation of the power system. This paper aims to mitigate wind and solar fluctuations by integrating energy storage systems (ESS). One crucial metric for assessing the performance of energy storage systems is state of charge (SOC). Therefore, this paper proposes a power flow optimization method based on SOC characteristics. Firstly, we consider the uncertainties on both the generation and load sides of the power system and establish a source load model. Subsequently, an analysis of the SOC characteristics of the ESS is conducted, and associated constraints are provided. Then, a power flow model for the AC-DC system with voltage source converter (VSC) is developed based on the source load storage configuration. The optimization model is formulated as a multi-objective problem, utilizing penalty functions to minimize the overall economic cost, system losses, and line voltage deviations. Finally, the proposed method is validated through simulation analysis using an enhanced IEEE 30-node system as a case study. The simulation results confirm the correctness and effectiveness of the presented approach.