A Framework for Profit Maximization in a Grid-Connected Microgrid With Hybrid Resources Using a Novel Rule Base-BAT Algorithm

Abstract

In this paper, an energy management system (EMS) is proposed for optimal operation of a microgrid (MG). Dispersed photovoltaic arrays (PVs) and wind turbine generators (WTs) as renewable energy sources (RES) supply a major part of the network demanded energy. Also, an energy storage system (ESS), a micro-turbine unit (MT), and a fuel cell unit (FC) are integrated. The uncertainty and stochastic nature of the network load and RES data are treated via probabilistic modeling and scenarioselection approach. The predicted day-ahead data of the most diverse hourly scenarios are entered into the proposed EMS to determine the active and reactive power (P-Q) participations of local distributed resources. Likewise, it specifies the discharging/charging power and state of the ESS in addition to the exchanged active/reactive power amounts with the main network. The main goal is to maximize the profit of the secondary grid while satisfying all technical constraints. In the proposed EMS, the day-ahead energy management is developed as a comprehensive optimization problem. Moreover, the paper proposes novel modifications to improve the BAT optimization technique. The optimization problem of the energy management in the microgrid is implemented using a new integrated rule base-improved BAT method. Furthermore, the proposed EMS competence is proven by comparing its performance to recent literature.

Recent advances of bat-inspired algorithm, its versions and applications

“…11 ), most of the BA applications under electrical and power system research domain. In this domain, the optimization problems addressed by BA are economic/emission dispatch [ 40 , 173 , 267 , 292 ], power economic dispatch [ 210 ], reactive power dispatch [ 209 , 214 ], optimal power flow [ 326 ], electronics, control, and communication [ 1 , 38 , 132 , 226 , 257 , 266 ], solar PV parameter estimation and solar radiation forecasting [ 3 , 310 , 337 ], photovoltaic energy system [ 76 , 94 – 96 , 145 , 176 , 194 , 225 , 259 ], forecasting of petroleum consumption [ 58 ], load frequency control [ 19 , 92 , 93 ], energy consumption [ 104 , 219 , 261 ], proportional-integral-derivative (PID) controller [ 60 , 122 , 164 , 187 , 188 , 193 , 224 , 233 , 330 ], wind speed forecasting [ 67 , 174 , 222 , 309 , 311 ], power system [ 30 , 31 , 36 , 70 , 81 , 91 , 106 , 121 , 162 , 258 , 278 , 284 ], dam–reservoir operation [ 99 ], and others [ 136 ]. These applications are presented in Fig.…”

Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots

“…Optimal scheduling of interconnected MGs with hybrid ESS and FC has been presented in [34], in which the degradation causes of ESS have been taken into account. In [35], a day-ahead energy management scheme for a MEMG with RE, ESS, and FC has been presented considering RE and load uncertainty. The impact of HVs on the operating costs of an islanded MG has been examined in [36], and the numerical findings are indicative of cost minimization.…”

“…The amount of charged power at time t is defined by (32) and the maximum and minimum power capacity of EVs are bounded by (33). Moreover, the maximum and minimum charge and discharge rates of EVs are limited by (34) and (35), respectively and equation (36) prevents simultaneous charging and discharging. The initial SoC of EVs is equal to their amount of SoCs at the arrival time and similarly, their SoCs at departure time should meet a specific amount.…”

The comparison of dual axis photovoltaic tracking system using artificial intelligence techniques

“…Bat algorithm (BA) is a stochastic global optimization algorithm based on bat echolocation mechanism and very good characteristics [26], [27]. Some simulation results show that the bat algorithm model has a good performance in the optimization function.…”