Litcius/Paper detail

Network-Aware Demand-Side Management Framework With A Community Energy Storage System Considering Voltage Constraints

Chathurika P. Mediwaththe, Lachlan Blackhall

2020IEEE Transactions on Power Systems47 citationsDOIOpen Access PDF

Abstract

This paper studies the feasibility of integrating a community energy storage (CES) system with rooftop photovoltaic (PV) power generation for demand-side management of a neighbourhood while maintaining the distribution network voltages within allowed limits. To this end, we develop a decentralized energy trading system between a CES provider and users with rooftop PV systems. By leveraging a linearized branch flow model for radial distribution networks, a voltage-constrained leader-follower Stackelberg game is developed wherein the CES provider maximizes revenue and the users minimize their personal energy costs by trading energy with the CES system and the grid. The Stackelberg game has a unique equilibrium at which the CES provider maximizes revenue and the users minimize energy costs at a unique Nash equilibrium. A case study, with realistic PV power generation and demand data, confirms that the energy trading system can reduce peak energy demand and prevent network voltage excursions, while delivering financial benefits to the users and the CES provider. Further, simulations highlight that, in comparison with a centralized system, the decentralized energy trading system provides greater economic benefits to the users with less energy storage capacity.

Topics & Concepts

Stackelberg competitionEnergy storageRevenueComputer scienceEnvironmental economicsGame theoryDistributed generationElectric power systemNash equilibriumEnergy management systemSmart gridEnergy managementPeak demandPhotovoltaic systemMicroeconomicsBusinessEconomicsRenewable energyElectricityEnergy (signal processing)Power (physics)Electrical engineeringFinanceEngineeringMathematicsPhysicsQuantum mechanicsStatisticsSmart Grid Energy ManagementOptimal Power Flow DistributionMicrogrid Control and Optimization