Scenario based Stochastic Multi-Objective Scheduling of Hybrid Heat and Power Resources of a Micro-grid Considering Demand Response Program

Abstract

In this paper a stochastic model proposes for optimal microgrid energy management with the aim of minimizing costs and emissions. In this model, uncertainties related to load demand, wind speed and solar irradiation are modeled with a scenario-based stochastic modeling. By using this, the uncertain nature of the proposed problem is converted into some deterministic problems. A Hybrid Microgrid System (HMS) that includes power resources such as wind turbines (WT), photovoltaic panels (PV), energy storage system (ESS), fuel cell (FC), power only unit (PO) and two types of CHP units and heat resources such as heat storage (HS) is set up and programmed in both grid-connected and islanded modes to generate electricity and heat simultaneously. To achieve this goal, network loads will participate in the demand response program (DRP). Since these two goals are not the same, the multi objective particle swarm optimization (MOPSO) algorithm is used to yield the best expected Pareto optimal front. Also, fuzzy-based decision making mechanism is applied to extract the best compromise considering the set of solutions of Pareto optimal front. Due to the high volume of the simulation output, the implemented results are shown only for the 13^th scenario as most probable scenario that has a higher probability. Finally, the total cost ($/day) and total emission (kg/day) for three case studies under each scenario and related expected values are represented.