Optimal energy flow control strategy for a residential energy local network combined with demand-side management and real-time pricing

Abstract

Due to the increasing importance of demand-side resources in the energy internet, this paper proposes an optimal energy flow control strategy for a residential energy local network (RELN), which consists of a small number of households, based on the idea of demand-side management. In particular, a type of optimal and dynamic RELN energy consumption scheduling framework is formulated to minimize the daily total operation cost, while fully considering the output forecast error of renewable energy sources (RESs), the consumption preference of users and the status of the energy storage system. In this framework, we provide a unified appliance model to group various types of appliances, which are connected to the network, into a physical model with the same attributes, and a comprehensive real-time pricing mechanism between the RELN and power distribution company (PDC) is developed based on the generalized total load to guide the electricity consumption behavior of the end-users and to also balance the total residential load. On this basis, a mixed integer programming (MIP) model for dynamic energy management optimization of the RELN is optimized at each decision period and integrated into a model predictive control method to reduce the negative impacts of forecast errors of RESs, thereby realizing an optimal and automatic energy flow control for the RELN. Finally, the effectiveness of the proposed RELN energy flow management framework is verified using several case studies.