Dynamic Pricing for Smart Distribution Networks Efficient and Economic Operation

PALACIOS, JUAN PABLO; SAMPER, MAURICIO ; VARGAS, ALBERTO

Viña del Mar

Congreso; CLAGTEE 2013 (X Latin-American Congress on Electric Power Generation, Transmission and Distribution); 2013

Pontificia Universidad Católica de Valparaiso

Smart Grids have permitted the implementation of Demand Response (DR) programs and have also improved the control of Distributed Energy Resources (DER). In this paper we obtain a model of DR of a group of customers, based on DR pilot projects data and using Artificial Neural Networks (ANN). We neglect the low voltage electrical network assuming that clients and DER (e.g. Photovoltaic Generators) are directly connected to distribution transformers. With the knowledge of the clients´ DR model we will define an optimal distribution pricing (e.g. TOU pricing) to minimize the costs related to distribution network congestion: Energy Not Supplied Costs for network congestion, Energy for Voltage Quality Penalty Costs, Technical Losses Costs. On the other hand in this work we will assume that Photovoltaic Generation units do not have Energy Storage Systems (ESS), and PV generation will be considered as a negative demand in households. In a later work we will consider that energy from PV ESSs can be dispatched in such a way that clients receive more economic benefits because of electricity price differentials through the day.