AI RESEARCH
Feature-driven reinforcement learning for photovoltaic in continuous intraday trading
arXiv CS.LG
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ArXi:2510.16021v3 Announce Type: replace Sequential intraday electricity trading allows photovoltaic (PV) operators to reduce imbalance settlement costs as forecasts improve throughout the day. Yet deployable trading policies must jointly handle forecast uncertainty, intraday prices, liquidity, and the asymmetric economics of PV imbalance exposure. This paper proposes a feature-driven reinforcement learning (FDRL) framework for intraday PV trading in the Nordic market.