Tarifación Dinámica de Redes Inteligentes de Distribución Usando Optimización Multiobjetivo

Abstract

Energy storage systems (ESS) and Demand Response (DR) technologies can provide economic benefi ts to Distribution Network Operator (DNO) and residential clients. We consider a scenario of a Distribution Smart Gridwhere prosumers can schedule their fl exible demand and storeenergy supplied from the distribution grid and from ownPV panelswith the aid of Home Energy Management Systems (HEMS) that maximize its benefi ts in response to a 24 hour dynamic pricing. DNO can benefi t from prosumers’ energy resources, if prosumers are incentivized to schedule their consumptionand ESSto alleviate the distribution network in times ofhigh congestionsor when the wholesale electricity market price is high. We propose to optimize a 24 hour day-ahead dynamic pricing in order to maximize the daily social benefi t of DNO and prosumers (i.e. minimize DNO operation costs and maximize prosumers’ utility). We tackle the proposed problem by solving the prosumers’ and DNO optimization problems in a distributed manner using both mathematical and heuristic optimization techniques.