An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Abstract

The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.

Appropriateness analysis of implementing a smart grid system in campus buildings using the fuzzy method

“…Which aims to actualize the automation system on the smart grid system. The optimization technique is required in an automated system to apply some resources optimally [24], [25]. Furthermore, the smart grid power system is analyzed using the fuzzy method.…”

Optimal Energy Management of a Campus Microgrid Considering Financial and Economic Analysis with Demand Response Strategies

“…To properly schedule the energy usage in the EMS, the battery output power P b t was included in the equality constraint stated in Equation (8) represent the ESS charging/discharging, respectively, in just about any interval "t". To simply avoid the BESS charging/discharging issue for the equivalent durations, the binary pattern characteristics that are shown in Equations ( 11)-( 13) may not be "1" at the regular intervals.…”

“…The involvement of these µGs in power systems lowers their operating energy costs, with the focus on the benefits of the distribution system [7]. The grid operator additionally provides different price-based and incentive-based DR schemes to entice such large-scale users to actively participate in energy markets [8].…”

Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges

“…The DG depends on the control of the distributed energy resources (DER) and the optimal scheduling of the microgrid. The optimal scheduling of power generation expressively affects the stability of the energy system [ 6 ]. Different scheduling techniques of the power system are used to improve the power quality and voltage control of microgrids based on the real microgrid solution with multiple implementation scenarios that aimed to get green energy and to make an efficient smart campus to achieve sustainable energy for the campus microgrid with the reduction in GHG emissions [ 7 ].…”