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Demand‐Side Management (DSM) Strategic plan of International Energy Agency states that the first option in all energy policies to achieve sustainable, reliable, and economic systems is DSM activities such as demand response programs (DRP). Thereby, these programs must also be considered in energy management of microgrids (MGs) and their operation and resiliency optimization. Energy management in MGs is carried out with different objectives such as reducing operation costs and enhancing the resilience response. In the first approach, the microgrid operator attempts to minimize the energy cost supplied by available resources in normal conditions. On the other hand, the goal of improving microgrid resilience response is to reduce the energy outages and load interruptions in emergencies such as occurrence of floods, earthquakes, and hurricanes. Naturally, in the second approach, the generation share of the microgrid resources itself in supplying the required demand is more; because the microgrid and main network connection will be lost in this approach. Since these two approaches may lead to different strategies in microgrid energy management, a compromise must be reached between them. In this paper, DRP, storage devices, renewable resources, such as wind and photovoltaic (PV) units, are modelled to manage energy in the MGs equipped with Combined Cooling, Heat, and Power to minimize the operation costs and enhance the resilience response. Three case studies are considered. The first case deals with the management of energy and structure in MGs without considering resilience objective function and responsive loads. In the second case, the resilience objective function is considered in the problem, and in the third study, responsive loads were also taken into account. The results show that the total objective function is reduced by considering the resilience objective function in case two. Also, the use of responsive loads in the third case also reduces more the total costs of MGs.

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Microgrid (MG) operator tries to supply the electricity consumption with minimum cost. To this end, the operator should economically manage the output power of its resources. These resources may be electrical, heat, or Combined Cooling, Heat and Power (CCHP) generators. On the other hand, improvement of the MGs resilience response against Low-Probability High-Impact (LPHI) events have received considerable attention in recent years. So, this should be taken into account in the energy management of MGs. The MGs energy management is realized in this paper with the goals of improving resilience, reducing operation cost, reducing environmental pollution, and reducing real power losses. For this purpose, some tools such as energy storage devices, CCHP, and renewables (Wind Turbine (WT) and Photovoltaic (PV) units) are implemented. Also, Genetic Algorithm (GA) is adopted to achieve the optimal answer. By considering the resilience concept in MG operation and based on the results, we find that the amount of operating costs and environmental pollution have increased by an average of 6.31 and 2.8 percent, respectively. But, because of reducing the outage cost and power losses by an average of 13.91 and 0.5 percent, respectively, the total cost is reduced by an average of 5.93 percent.