Rolling horizon optimization based real-time energy management of a residential neighborhood considering PV and ESS usage fairness.

• A Mixed-Integer Linear Programming (MILP) framework based energy management system model. • A rolling horizon approach to tackle with PV production uncertainties. • Ensuring a fairness among the residential end-users for PV and ESS usage. • Development of PV and ESS usage metrics for fairness evaluation. The incorporation of decentralized energy solutions, including solar photovoltaic (PV) installations and energy storage systems (ESSs), into residential communities has received substantial interest in recent times. This is driven by the objective of enhancing the self-reliance of residential zones while decreasing their reliance on centralized power grids. Effective management of these systems can yield advantages such as load equalization, cost reduction, and diminished emissions. The process of optimizing energy management in residential communities entails addressing multiple factors, including uncertainty, equity, and efficiency. This study introduces an innovative methodology for real-time energy management in a residential community, taking into account both the equitable utilization of solar PV and ESS and the minimization of costs. The suggested technique employs rolling horizon optimization and mixed-integer linear programming (MILP) to tackle uncertainties in PV production and guarantee a fair allocation of shared resources. The outcomes of this novel approach showcase its capability to sustain cost-effectiveness while fostering equitable energy consumption. [ABSTRACT FROM AUTHOR]