Demand response for residential appliances using multi-agent reinforcement learning with price and solar power uncertainty
The electricity market exhibits significant uncertainty arising from rapid fluctuations in prices, variations in load demand, and the intermittent nature of renewable energy resources. Effectively managing residential energy under these dynamic conditions is a challenging task. Demand Response (DR) offers a practical solution by enabling the flexible scheduling of energy consumption in response to
