This paper introduces a day-ahead energy management algorithm for the coordination of smart homes with renewable energy sources and energy storage systems in neighborhood areas. The aim of this study is to establish a day-ahead decentralized coordination method with appliance scheduling and energy sharing (among smart homes) to minimize the electricity bills of consumers under dynamic pricing. The energy sharing algorithm focuses on increasing the utilization of renewable sources by controlling storage units. A multi-agent system is used to model entities (smart homes, aggregator and utility) as agents and the optimization problem is solved in a decentralized manner by home agents with a genetic algorithm. The performance of the coordination algorithm is evaluated annually with and without considering forecasting errors.