A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids

The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency.</jats:p

A review on peak load shaving in microgrid—Potential benefits, challenges, and future trend

This study aims to review the potential benefits of peak load shaving in a microgrid system. The relevance of peak shaving for a microgrid system is presented in this research review at the outset to justify the peak load shaving efficacy. The prospective benefits of peak shaving in microgrid systems, including technological, economic, and environmental advantages, are thoroughly examined. This review study also presents a cost–benefit numerical analysis to illustrate the economic viability of peak load shaving for a microgrid system. Different peak shaving approaches are briefly discussed, as well as the obstacles of putting them into practice. Finally, this review study reveals some potential future trends and possible directions for peak shaving research in microgrid systems. This review paper lays a strong foundation for identifying the potential benefits of peak shaving in microgrid systems and establishing suitable projects for practical effectuation

Applications of Utility-Scale Power to Gas Energy Storage Systems in Smart Grids

ABSTRACT This thesis aims to develop the engineering tools required to simulate, design, and optimize the operation of utility-scale power to gas (PtG) energy storage. First, a co-simulation platform for power and gas distribution networks is developed. The co-simulation platform could help quantifying the role of PtG technology in shaping the future of power distribution systems. Using the co-simulation platform, several research studies can be carried out such as operation scheduling and planning of power and gas networks. Second, a new formulation is developed for the optimal design i.e., sizing, of PtG energy storage. The developed formulation aims at minimizing the capital and operation costs of PtG and maximizing the harvested power during periods of surplus. Third, a new mathematical formulation is proposed for the optimal production scheduling of hydrogen to supply fuel cell buses. The proposed formulation takes into account the operation requirements of both power distribution and electric bus transit networks