Abstract
Prosumer Energy Management System (PEMS) is the system used for intelligent energy management for a house-hold with on-site photovoltaic (PV) system using the input data from various sources: smart meter, PV management system, a distribution transformer, dispatching unit of a home, real-time pricing from utility provider data center. An efficient PEMS should be able to provide demand response (DR) management in response to the prices, on-site energy generation, and electricity load to contribute to the improvement of overall electricity grid reliability and reduce the costs of a prosumer. This paper presents the Smart PEMS based on two components: seasonal decomposition long short-term memory (SD-LSTM) based forecasting system for predicting electricity prices and PV system energy generation combined with Q-Learning based home appliances scheduler.