Economic and environmental assessment of multi-energy microgrids under a hybrid optimization technique

Abstract

Nowadays, multi-vector energy communities are receiving special attention from smart grid operators due to the integration of several types of energy sources. In this regard, multi-carrier microgrids (MCMGs) are known as a flexible platform to supply energy demands with an acceptable range of affordability and reliability by relying on the various energy conversion facilities. Given the pivotal role of MCMGs in future energy networks, accurate economic and environmental assessment of MCMGs, along with energy market plans has become a challenging task. In order to address this open issue, this paper proposes a hybrid robust/stochastic optimization strategy for optimal scheduling of the renewable-based MCMG to participate in electricity, gas, and district heat markets. The main objectives of this study are to minimize the total energy cost of the MCMG and decrease CO2 emission rates by considering the combined heat and power (CHP) unit, boiler unit, electrical energy storage (EES), thermal energy storage (TES), power-to-gas (P2G) storage, and wind turbine as the main components of the MCMG to provide the required energy. In addition, the role of the electric vehicle parking lots (EV-PLs) and demand response (DR) programs in the form of the day-ahead load shifting program is considered in improving the economic performance of the MCMG in energy markets. To accurately model the behavior of the MCMG, the uncertainties associated with wind power output, electrical loads, electricity market price, and behavior of electric vehicle (EV) (arrival/departure times and state of the charge) are handled by a hybrid robust-stochastic approach. The proposed robust/stochastic model is modeled as the mixed-integer linear programming (MILP) model, and solved by GAMS software. The effectiveness of the proposed structure is examined through various case studies. According to the obtained results, the total energy cost of the MCMG and the emission cost are decreased by up to 3.51 %, and 2.36 %, in the presence of EV-PLs, multi-carrier energy storage, and DR programs.