Stochastic Investment Planning Model of Multi-energy Microgrids considering Network Operational Uncertainties

Abstract

This work proposes a scenario-based stochastic microgrid investment planning model in the presence of various forms of generation and demand with operational uncertainties. The solution aims to minimize the overall cost and carbon dioxide emissions in microgrid through determining the optimal placement and capacities (i.e. siting and sizing) of the distributed energy resources (DERs). The DER mix comprises of the wind turbines., photovoltaics., gas-boiler., and combined heat and power units. The proposed planning model is based on linear power flow and heat transfer equations, and explicitly captures the interaction between electricity and heating DERs. To address the operational uncertainties associated with the wind and photovoltaic generation as well as the electricity and heating demands, an uncertainty matrix is adopted. The uncertainty matrix is generated using the heuristic moment matching (HMM) method that effectively captures the stochastic moments and correlation among the historical data. The numerical results from a case-study on 19-bus microgrid test system confirm the effectiveness of the proposed model.