Abstract
Microgrids have emerged as a practical solution to improve the power system resilience against unpredicted failures and power outages. Microgrids offer substantial benefits for customers through the local supply of domestic demands as well as reducing curtailment during possible disruptions. Furthermore, the interdependency of natural gas and power networks is a key factor in energy systems’ resilience during critical hours. This paper suggests a probabilistic optimization of networked multi-carrier microgrids (NMCMG), addressing the uncertainties associated with thermal and electrical demands, renewable power generation, and the electricity market. The approach aims to minimize the NMCMG costs associated with the operation, maintenance, CO2e emission, startup and shutdown cost of units, incentive and penalty payments, as well as load curtailment during unpredicted failures. Moreover, two types of demand response programs (DRPs), including time-based and incentive-based DRPs, are addressed. The DRPs unlock the flexibility potentials of domestic demands to compensate for the power shortage during critical hours. The heat-power dual dependency characteristic of combined heat and power systems as a substantial technology in microgrids is considered in the model. The simulation results confirm that the suggested NMCMG not only integrates the flexibility potentials into the microgrids but also enhances the resilience of the energy systems.
Highlights
Improving the power system’s resilience against incidents and natural disasters has attracted much attention during the last decade
The multi-carrier microgrids (MCMG) are interconnected through the power and natural gas networks
This paper proposed a mathematical formulation for enhancing the resiliency of networked multi-carrier microgrids regarding severe uncertainties
Summary
Improving the power system’s resilience against incidents and natural disasters has attracted much attention during the last decade. The integration of distributed generations (DG) into the energy networks has created many challenges for power system operation In this way, the uncertainties of non-dispatchable DGs, demands, and the electricity market make the problem non-deterministic. The paper in [19] proposed a hybrid robust/stochastic framework for optimal scheduling of a multi-energy MG comprised of electric vehicle parking lots, power-to-gas facility, and price-responsive shiftable loads. Proposing a mathematical model of NMCMG addressing the interdependencies of gas and electricity networks; Optimizing the operational strategies of NMCMG in the presence of uncertainties associated with electrical and thermal demands, electricity market, and RES; Introducing varying H2P ratio of CHP units with respect to the loading level; Integrating the flexibility potentials of responsive thermal/electrical consumers into the main grid using IBDRP and TBDRP.
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