OPTIMAL SCHEDULING ALGORITHM OF RENEWABLE ENERGY POWER GENERATION CONSIDERING SECURITY RISK COST

Fu Xiaoyan; Zheng Le

doi:10.19912/j.0254-0096.tynxb.2025-0487

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (7) : 792-801. DOI: 10.19912/j.0254-0096.tynxb.2025-0487

OPTIMAL SCHEDULING ALGORITHM OF RENEWABLE ENERGY POWER GENERATION CONSIDERING SECURITY RISK COST

Fu Xiaoyan¹, Zheng Le²

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Abstract

In response to the system scheduling optimization problem caused by the intermittent and fluctuating output of renewable energy generation, an optimal scheduling algorithm of renewable energy power generation considering security and stability risk cost is proposed. Firstly, a multi-objective optimal scheduling model of renewable energy generation is established with the power generation cost, the stability cost, and the proportion of renewable energy consumption as optimization objectives. Secondly, based on the principles of deep reinforcement learning, an optimization solution framework for the scheduling model of renewable energy power generation system is proposed. Combined with the Markov Decision Process （MDP）, the multi-objective optimization scheduling problem of renewable energy generation is transformed and described to establish a solution process for the model based on deep reinforcement learning. Then, an open-source platform for scheduling of renewable energy with deep reinforcement learning （SEDRL） is established using open-source software packages such as PandaPower, OpenAI Gym, and Stable-Baselines. According to the actual power grid parameters, the system optimization scheduling algorithm program is established, and different deep reinforcement learning algorithms are used for verification. Finally, a test example is established based on the IEEE 118-bus system for verification. The results show that the open-source platform has good scalability and is suitable for the generation of renewable energy generation scheduling strategies in different scenarios.

Key words

renewable energy / optimal scheduling / multi-objective optimization / deep reinforcement learning / security risk

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Fu Xiaoyan, Zheng Le. OPTIMAL SCHEDULING ALGORITHM OF RENEWABLE ENERGY POWER GENERATION CONSIDERING SECURITY RISK COST[J]. Acta Energiae Solaris Sinica. 2026, 47(7): 792-801 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0487

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