Optimal energy management for an island microgrid by using dynamic programming method

Energy Management in Microgrids with Renewable Energy Sources: A Literature Review

“…Luu et al [66] presented a dynamic programming method and methodology based on the rules applied to a stand-alone MG containing diesel and photovoltaic generators, and a battery. The constraints are governed by the power balance between generation and consumption, along with the capacity of each distributed generator.…”

Reliability improvement of future microgrid with mixed load models by optimal dispatch of DGs

“…Hierarchical microgrid management system using task sharing and an evolutionary game theory–based dispatch strategy is presented in Mojica‐Nava et al Wu et al proposed a novel future smart microgrid model where the energy consumers and distributed energy providers can perform local energy trading controlled by a local trading manager. A dynamic programming method to build the optimal energy management for an island microgrid is proposed in Luu et al Schwaegerl et al formulated a combined dispatch strategy that can simultaneously satisfy all constraints and provide a proper compromise for conflicting objectives of different stakeholders involved in energy supply chain. Mejia and Patiño discussed the behavioral and technical difficulties that emerge in a microgrid that incorporates a high percentage of renewable energy sources (RES) and their dispatch actions.…”

“…Hierarchical microgrid management system using task sharing and an evolutionary game theory-based dispatch strategy is LIST OF SYMBOLS AND ABBREVIATIONS: Symbols, Expansion; A, loudness of bat; ABC, artificial bee colony; a i , b i , c i , quadratic cost coefficients of ith generator; bf, frequency of bat; BOA, bat optimization algorithm; DG, distributed generators; E i , energy generated by ith generated; EIR, energy index of reliability; FOR, forced outage rate; GA, genetic algorithm; ICOST, index of generation cost; ILP, index of active power loss; ILQ, index of reactive power loss; i pq , current flow from bus p to bus q; IVD, index of maximum voltage deviation; Ploss, active power loss; pr, pulse emission rate; PSO, particle swarm optimization; Qloss, reactive power loss; RES, renewable energy source; r k , resistance of kth line; S pq , apparent power flow from bus p to bus q; TLBOA, teaching learning-based optimization algorithm; V p , voltage at bus p; WOA, whale optimization algorithm; x i , bat echolocation; x k , reactance of kth line; α, active power coefficient for voltage sensitive load; β, reactive power coefficient for voltage sensitive load presented in Mojica-Nava et al 3 Wu et al 4 proposed a novel future smart microgrid model where the energy consumers and distributed energy providers can perform local energy trading controlled by a local trading manager. A dynamic programming method to build the optimal energy management for an island microgrid is proposed in Luu et al 5 Schwaegerl et al 6 formulated a combined dispatch strategy that can simultaneously satisfy all constraints and provide a proper compromise for conflicting objectives of different stakeholders involved in energy supply chain. Mejia and Patiño 7 discussed the behavioral and technical difficulties that emerge in a microgrid that incorporates a high percentage of renewable energy sources (RES) and their dispatch actions.…”

Estimation of Load Pattern for Optimal Planning of Stand-Alone Microgrid Networks

“…With recent concerns regarding large-scale centralized power supply systems using fossil fuels, such as non-sustainability, safety, environmental pollution, and accelerating climate change, new technologies are being developed to replace existing fossil fuels [1]. In addition, the massive power outages in September 2011 in Korea have forced us to revise the large-scale, centralized power production and supply plans that have been typical.…”