Application of Different Optimization Algorithms for Optimal Sizing of PV/Wind/Diesel/Battery Storage Stand-Alone Hybrid Microgrid

Diab, Ahmed A. Zaki; Sultan, Hamdy M.; Mohamed, Ihab S.; Kuznetsov, Oleg N.; Duc, Ton

doi:10.1109/access.2019.2936656

Cited by 177 publications

(73 citation statements)

References 37 publications

(68 reference statements)

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“…The appearance of the test bench is shown in Figure 7. The test bench consists of the following parts: (1 and 2) DGS and wind turbine simulators based on an asynchronous variable frequency drive and an alternator, (3) a DGS based on a gasoline ICE and synchronous generator, (4) connecting terminals for connecting a wind turbine, (5) an accumulator battery, (6) a programmable logic controller, (7) an autonomous inverter, (8)…”

Section: Experimental Studies and Discussionmentioning

confidence: 99%

Economy Mode Setting Device for Wind-Diesel Power Plants

et al. 2020

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The article is devoted to the problem of reducing fuel consumption in a diesel generator set (DGS) as a part of a wind-diesel power plant (WDPP). The object of the research is a variable speed DGS. The goal is to develop the WDPP intelligent control system, providing an optimal shaft speed of an internal combustion engine (ICE). The basis of the intelligent control system is an economy mode setting device (EMSD), which controls the fuel supply to the ICE. The functional chart of EMSD has been presented. The main EMSD blocks contain a controller and an associative memory block. The associative memory block is a software model of an artificial neural network that determines the optimal shaft speed of the ICE. An algorithm for the WDPP intelligent control system has been developed and tested using the WDPP Simulink model. The EMSD prototype has been created, and its research has been conducted. Dependences of the change in specific and absolute fuel consumption on the load power have been obtained for two 4 kW DGS: with constant rotation speed and variable rotation speed DGS with EMSD. It has been established that the use of EMSD in the mode of low loads allow one to reduce fuel consumption by almost 30%. The error in determining the optimal engine speed using EMSD prototype is not more than 15%.

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Section: Experimental Studies and Discussionmentioning

confidence: 99%

Economy Mode Setting Device for Wind-Diesel Power Plants

et al. 2020

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“…In [27], the wind power and energy price were estimated using radial functional network. In [28], the optimal sizing of microgrid with hybrid PV+WT+BESS+DG was determined using the whale optimization algorithm (WOA), water cycle algorithm (WCA), moth-flame optimizer (MFO), and hybrid particle swarm-gravitational search algorithm to minimize the COE. In [29], the energy management in a community microgrid was presented considering the uncertainty of renewable energy sources, electricity price and load demand to minimize the total cost.…”

Section: Parameters Of Beta Distributionmentioning

confidence: 99%

“…The uncertainty of electricity demand is modeled using the normal distribution function [34] as given in (27) and (28).…”

Section: Modeling Of Load Uncertaintymentioning

confidence: 99%

Optimal Energy Management and Techno-economic Analysis in Microgrid with Hybrid Renewable Energy Sources

Murty

Kumar

2020

Journal of Modern Power Systems and Clean Energy

139

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Microgrids with hybrid renewable energy sources are increasing and it is a promising solution to electrify remote areas where distribution network expansion is not feasible or not economical. Standalone microgrids with environment-friendly hybrid energy sources is a cost-effective solution that ensures system reliability and energy security. This paper determines the optimal capacity, energy dispatching and techno-economic benefits of standalone microgrid in remote area in Tamilnadu, India. Microgrids with hybrid energy sources comprising photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS) and diesel generator (DG) are considered in this paper. Various case studies are implemented with hybrid energy sources and for each case study a comparative analysis of techno-economic benefits is demonstrated. Eight different configurations of hybrid energy sources are modeled with renewable fractions of 50%, 60%, 65%, and 100%, respectively. The optimization analysis is carried out using Hybrid Optimization Model for Electric Renewable (HOMER) software. Impact of demand response is also demonstrated on energy dispatching and technoeconomic benefits. Simulation results are obtained for the optimal capacity of PV, WT, DG, converter, and BESS, charging/discharging pattern, state of charge (SOC), net present cost (NPC), cost of energy (COE), initial cost, operation cost, fuel cost, greenhouse gas emission penalty and payback period considering seasonal load variation. It is observed that PV+BESS is the most economical configuration. COE in standalone microgrid is higher than the conventional grid price. The results show that CO 2 emissions in hybrid PV+WT+DG+BESS are reduced by about 68% compared with the traditional isolated distribution system with DG.

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“…Table 2 lists various optimization techniques that are used to identify the most feasible solution to the problem of cost minimization in MGs [15][16][17]. Various optimization techniques, such as PSO for MG sizing, are applied in [18]. The authors discuss the convergence speeds of and the quality of the solutions that are derived by various methods.…”

Section: Optimization Techniquesmentioning

confidence: 99%

Review on the cost optimization of microgrids via particle swarm optimization

Phommixay

Doumbia

St-Pierre

2019

Int J Energy Environ Eng

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Economic analysis is an important tool in evaluating the performances of microgrid (MG) operations and sizing. Optimization techniques are required for operating and sizing an MG as economically as possible. Various optimization approaches are applied to MGs, which include classic and artificial intelligence techniques. Particle swarm optimization (PSO) is one of the most frequently used methods for cost optimization due to its high performance and flexibility. PSO has various versions and can be combined with other intelligent methods to realize improved performance optimization. This paper reviews the cost minimization performances of various economic models that are based on PSO with regard to MG operations and sizing. First, PSO is described, and its performance is analyzed. Second, various objective functions, constraints and cost functions that are used in MG optimizations are presented. Then, various applications of PSO for MG sizing and operations are reviewed. Additionally, optimal operation costs that are related to the energy management strategy, unit commitment, economic dispatch and optimal power flow are investigated.

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Application of Different Optimization Algorithms for Optimal Sizing of PV/Wind/Diesel/Battery Storage Stand-Alone Hybrid Microgrid

Cited by 177 publications

References 37 publications

Economy Mode Setting Device for Wind-Diesel Power Plants

Economy Mode Setting Device for Wind-Diesel Power Plants

Optimal Energy Management and Techno-economic Analysis in Microgrid with Hybrid Renewable Energy Sources

Review on the cost optimization of microgrids via particle swarm optimization

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