Coordination of Smart PV Inverters in DistributionSystems with Deep Reinforcement Learning
سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 70
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شناسه ملی سند علمی:
ICNRTEE02_056
تاریخ نمایه سازی: 4 مهر 1403
چکیده مقاله:
This research proposes a multi-tasking DeepReinforcement Learning (DRL) algorithm capable of minimizing powerlosses and mitigating voltage fluctuations in high photovoltaicpenetration (PV) distribution grids without curtailing their activeoutput power. The problem is formulated as a Markov Decision Process(MDP) with an optimized multi-purpose reward function. Two modelfreedata-driven DRL algorithms, Soft Actor-Critic (SAC) and TrustRegion Policy Optimization (TRPO), are trained. The proposedalgorithms are implemented on the IEEE ۳۷-bus test case distributionsystem, featuring a significant penetration of photovoltaic (PV) sources.Their efficacy is assessed using authentic real-world data. Thesealgorithms demonstrate a robust ability to proficiently handleuncertainties associated with PV generation while ensuring compliancewith standard operational constraints.
کلیدواژه ها:
نویسندگان
Mohammad Javad Faraji
Electrical Engineering DepartmentHamedan University of TechnologyHamedan, Iran
Ramezan Ali Naghizadeh
Electrical Engineering DepartmentHamedan University of TechnologyHamedan, Iran