Day‐ahead energy management framework for a networked gas–heat–electricity microgrid

Abstract

The integration of various energy supplying systems increases the energy efficiency and energy system reliability. Smart microgrids are an ideal area to use multi-carrier energy systems. In this context, this study presents a novel modelling framework for optimal day-ahead scheduling of a networked multi-carrier energy microgrid (NMCEMG) system. The NMCEMG system in this study is composed of heat, gas, and power supply networks. The presented framework has enhanced the multi-carrier microgrid modelling against the previous works that modelled the multi-carrier microgrid as an energy hub due to difficulties in the energy flow analysis of heat and gas networks. The proposed framework optimises the day-ahead operating cost of the NMCEMG system considering nodal and energy flow constraints of each network. The proposed microgrid includes various energy interdependent equipment such as combined heat and power units, gas-fired boilers, power to gas units, electrical and heat storages and electric heat pumps. This study presents a new optimisation algorithm named self-adaptive modified whale optimisation algorithm based on wavelet theory to solve the day-ahead optimal scheduling of the NMCEMG problem. The numerical results corroborate the proposed modelling framework as superior over conventional hub-based multi-carrier microgrid models in terms of energy system security.