Efficient Energy Management in a Microgrid with Intermittent Renewable Energy and Storage Sources

Abstract

Substituting a single large power grid into various manageable microgrids is the emerging form for maintaining power systems. A microgrid is usually comprised of small units of renewable energy sources, battery storage, combined heat and power (CHP) plants and most importantly, an energy management system (EMS). An EMS is responsible for the core functioning of a microgrid, which includes establishing continuous and reliable communication among all distributed generation (DG) units and ensuring well-coordinated activities. This research focuses on improving the performance of EMS. The problem at hand is the optimal scheduling of the generation units and battery storage in a microgrid. Therefore, EMS should ensure that the power is shared among different sources following an imposed scenario to meet the load requirements, while the operational costs of the microgrid are kept as low as possible. This problem is formulated as an optimization problem. To solve this problem, this research proposes an enhanced version of the most valuable player algorithm (MVPA) which is a new metaheuristic optimization algorithm, inspired by actual sporting events. The obtained results are compared with numerous well-known optimization algorithms to validate the efficiency of the proposed EMS.Sustainability 2019, 11, 3839 2 of 28 algorithms were used to optimize power sharing among active DGs. In order to determine the optimal component sizing in a microgrid, the mixed integer linear programming (MILP) method has been used to model the microgrid components with consideration of demand response [5]. In another study [6], similar sizing problems of microgrid components were solved using a genetic algorithm (GA) and the energy management issue was formulated using MILP. In addition to component sizing, system configuration was optimized in [7] using the multi-objective PSO by taking into account production cost, reliability, and environmental impact. The studied system comprised of a diesel generator, solar panels, wind turbines, and battery storage. Several methods have also been used for optimizing multi variable problems of energy management systems (EMS) in microgrids [8][9][10][11][12][13]. Wang et al. [14] investigated EMS of a microgrid with multi period optimization problems using an MPI based PSO algorithm and concluded that the proposed algorithm could be effectively used to improve the operation time.Four techniques were used in [15] to determine the optimized operational strategy for an entire day based on least operating cost and minimum carbon emissions. These techniques were a non-dominated sorting genetic algorithm (NSGA), multi-objective PSO, multi-objective uniform water cycle algorithm (WCA), and normal constraint algorithm. Reference [16] presented a real time EMS that had the tendency to optimally minimize carbon emissions and energy cost, and simultaneously maximized the power coming from renewable DGs using binary PSO. An improved binary PSO with double-structure coding was applied to optimize a microgrid operatio...

Technical and Economic Assessment of Micro-Cogeneration Systems for Residential Applications

“…Currently, there is a great diversity of micro-cogeneration technologies available on the market (e.g., Stirling engine, fuel cells, microturbines, internal combustion engines, Rankine Organic Cycle) that can harness primary energy resources, both conventional and renewable [4][5][6][7][8][9]. There is also a tendency for more than one primary energy source available to be used on a single site [10][11][12].…”

A novel hybrid algorithm for solving emerging electricity market pricing problem of microgrid

“…Authors in Ramli et al, 9 studied two more scenarios for the aforementioned islanded microgrid test system with 10% increase in the load demand, including an energy storage system and connecting the microgrid to utility for unilateral power flow. Enhanced most valuable player algorithm (EMVPA) proved to be the superior optimization tool in the article mentioned above.…”

Efficient Energy-Management System Using A Hybrid Transactive-Model Predictive Control Mechanism for Prosumer-Centric Networked Microgrids

“…Moreover, in the future smart grid, networked MGs could help mitigate the variability of DERs and allow consumers and prosumers to transact and exchange energy (i) among each other and (ii) with other MGs and (iii) to participate in a local retail market providing ancillary services with the rest of the distribution system [8]. Different approaches are proposed in the existing literature to manage and control networked MGs [9][10][11][12][13][14][15][16][17][18]. The role of networked MGs as distributed energy systems to improve power-grid resiliency during extreme weather events is analyzed in Reference [9].…”

“…Gregoratti and Matamoros [15] addressed a multiple-MG energy-trading strategy in order to minimize the global operation cost while satisfying local energy demand of MGs. A most valuable player algorithm is presented in Reference [16] to optimize the scheduling of the generation units and battery storage of an MG. In Reference [17], a distribution grid service market is proposed to provide voltage stability services in MGs.…”

“…Although network-MG control and management has been widely studied [7][8][9][10][11][12][13][14][15][16][17][18], many of these studies fail to analyze the impacts that these approaches might have on conventional distribution networks. As in some cases, the distribution network is not considered [12,15] and in other cases, a simplified version is considered [10,11,13,14].…”