Analytic Hierarchy Process (AHP)-Swarm intelligence based flexible demand response management of grid-connected microgrid

The integration of demand response programs (DRP) into the microgrid energy management system can enhance the load characteristics by enabling the active participation of consumers to achieve techno-economic benefits. From the microgrid operator's perspective, these DRP can optimize the revenue and accelerate return on investment. The previous research studies do not accurately represent modelling load responsiveness and price elasticities while implementing demand response programs. The accurate assessment of consumer behaviour to market price changes is paramount while modelling the price elasticities. With this viewpoint, a new microgrid energy management problem is proposed with the integration of flexible price elasticity based incentive-driven DRP in this research work. Further, the network flow constraints are considered to evaluate power losses and voltage deviation at each node of the modified IEEE-33 and IEEE-38 bus distribution networks. The comprehensive load model with the combination of linear and nonlinear conservative load responsive models is adopted and derived for each incentive-driven DRP by considering the nonlinear incentive and penalty model. Nine possible demand response scenarios were created, and techno-economic performance indices for each scenario were evaluated. Finally, the Fuzzy Analytic Hierarchy Program is adopted to choose the best alternative based on each techno-economic criterion. The recently reported swarm optimizer Sparrow Search Algorithm is devised for the first time in the microgrid literature to solve the above-proposed microgrid energy management problem. The obtained results are compared with existing metaheuristics to test the algorithm performance.