A framework for time-stamping battery charging and pricing structure to enable equitable and efficient dispatch for microgrids in demand-side management environment

Microgrids rely on diverse energy sources such as photovoltaics (PV), fossil fuels, and microturbines to power their operations. However, compensating these generators for their services poses significant challenges. This work examines the intricacies of compensation for various energy sources within microgrids and explores pricing mechanisms for battery energy storage. We investigate the feasibility of differentiating battery power based on the sources employed for charging, and the use of this information in pricing battery discharge power. Furthermore, we explore the possibility of “time stamping” the battery charging power. The timestamped charging data allows to distinguish discharged power according to its historical charging sources. This information is utilized in pricing battery power. The formulation supports equitable compensation for each energy source and allows microgrid operator (MGO) to establish fair payment structures. The problem is modeled as a bilevel interaction between the MGO and consumers in demand-side management environment. The prosumers schedule their devices by responding to the price signal sent by MGO. The price per slot depends on the total load per slot. By rearranging the device schedule, consumers change the price per unit per slot of energy. The MGO utilizes this information to decide the generation, charging–discharging profile of battery and compensation of various energy sources. A comprehensive analysis is performed to provide valuable insights into compensation and pricing strategies for the efficient and effective operation of a microgrid. Simulation results show that the proposed approach reduces the average cost by 18%, lowers the peak-to-average ratio (PAR) by 9.11%, and increases battery revenue from DG charged energy by 35.68% compared to flat-rate pricing schemes. • Novel time-stamping tracks battery energy source and charging time for fair pricing. • Source-differentiated revenue allocation increasing fairness. • Bilevel framework integrates source-differentiated pricing with prosumer game theory. • Prevents 13.415% revenue loss from undifferentiated battery discharge pricing. • Privacy-preserving Stackelberg–Nash algorithm for convergence.