Customized Prices Design for Agent-based Local Energy Market with PV and Energy Storage

Distributed energy resources, especially residential photovoltaics (PV), have been playing increasingly important roles in modern smart grids over past years. Residential netload is closely tied with customers' activities and weather, such as load consumption and solar generation, which could potentially be leveraged to improve demand response by designing customized price incentives. This paper seeks to design customized prices for a local energy market (LEM) that consists of agent, PV, energy storage (ES), prosumers, and consumers. The LEM agent who owns a community-scale ES system is responsible for operating the market and facilitating the energy sharing within the community. A hierarchical energy trading infrastructure is considered, where the agent acts as the mediator between the utility grid and customers. A two-stage decision-making framework, including look-ahead ES scheduling and real-time customized prices design, is developed for agent's profit maximization. The customer's consumption behavior is modeled as a utility maximization problem. Numerical results of case studies with 10 residential customers show the effectiveness of the customized prices design.