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.

نویسندگان

Mohammad Javad Faraji

Electrical Engineering DepartmentHamedan University of TechnologyHamedan, Iran

Ramezan Ali Naghizadeh

Electrical Engineering DepartmentHamedan University of TechnologyHamedan, Iran