Scenario-based investment planning of isolated multi-energy microgrids considering electricity, heating and cooling demand

Multi-energy microgrids provide a flexible solution for the utilization of the distributed energy resources in order to meet the electrical, heating and cooling energy demands in the off-grid communities. However, the planning of the multi-energy microgrids is a non-trivial problem due to the complex energy flows between the sources and the loads pertaining to the electrical, heating and cooling energy, along with the intermittency of the renewable distributed generation. This work proposes a scenario-based stochastic multi-energy microgrid investment planning model that aims to minimize the investment and operation costs as well as the Carbon dioxide emissions by determining the optimal distributed energy resource mix, siting and sizing in the isolated microgrids. The proposed planning model employs the power flow and heat transfer equations to explicitly model the energy flows between electrical, heating and cooling energy sources and loads. Moreover, an uncertainty matrix is employed to tackle the operational uncertainties associated with the wind and photovoltaic generation, and the electrical, heating and cooling loads. The uncertainty matrix is modeled using the heuristic moment matching method that effectively captures the stochastic moments and correlation among the historical scenarios. The numerical results obtained from the case-study in the 19-bus microgrid test system confirm that the proposed methodology provides significant reductions in the investment and operation costs as well as the Carbon dioxide emissions. Finally, the superiority of the proposed planning solution is also validated using the deterministic planning solution as the comparison benchmark.