Flexible Economic Energy Management Including Environmental Indices in Heat and Electrical Microgrids Considering Heat Pump with Renewable and Storage Systems

This study discusses energy management in thermal and electrical microgrids while taking heat pumps, renewable sources, thermal and hydrogen storages into account. The weighted total of the operating cost, grid emissions level, voltage and temperature deviation function, and other factors makes up the objective function of the suggested method. The restrictions include the operationflexibility model of resources and storages, micro-grid flexibility limits, and optimum power flow equations. Point Estimation Method is used in this work to simulate load, energy price, and renewable phenomenon uncertainty. A fuzzy decision-making methodology is used to arrive at a compromise solution that satisfies network operators’ operational, environmental, and financial goals. The innovations of this paper include energy management of various smart microgrids, simultaneous modeling of several indicators especially flexibility, investigation of optimal performance of resources and storage devices, and modeling of uncertainty considering low computational time and an accurate flexibility model. Numerical findings indicate that the fuzzy decision-making approach has the capability to reach a compromise point in which the objective functions approach their minimum values. The integration of the proposed uncertainty modeling with precise flexibility modeling results in a reduction in computational time when compared to stochastic optimization based on scenarios. For the compromise point and uncertainty modeling with PEM, by efficiently managing resources and thermal and hydrogen storages, scheme is capable of attaining high flexibility conditions. Compared to load flow studies, the approach can enhance the operational, environmental, and economic conditions of smart microgrids by approximately 33–57%, 68%, and 33–68%, respectively, under these circumstances.