Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm

Javed, Muhammad; Song, Aotian

doi:10.1016/j.energy.2019.03.131

Cited by 212 publications

(55 citation statements)

References 39 publications

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“…With is used. It corresponds to the ratio of all energy deficit to the load demand during operational modes [23]. So according to the number of batteries, Table 3 presents different performances of the HRES.…”

Section: Simulations and Resultsmentioning

confidence: 99%

Management of Hybrid Renewable Energy Systems Using Differential Hybrid Petri Nets

Fohoue-Tchendjou¹,

Kamla²,

Bouchet³

2020

Technium

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Investigations in this paper concern management of Hybrid Renewable Energy systems. To achieve it, a supervisory system based on hybrid systems concept is designed, in order to ensure power flow between energy generators (solar panel and pico-hydroelectric), batteries and load. Differential Hybrid Petri Net is used to model the proposed supervisory and simulations are made in Matlab environment.Results obtained present a good performance criteria Loss of Power Supply Probability, and this show the effectiveness of our approach in the coordination of HREs components during the energy sharing process by reducing load shedding in microgrid system.

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Section: Simulations and Resultsmentioning

confidence: 99%

Management of Hybrid Renewable Energy Systems Using Differential Hybrid Petri Nets

Fohoue-Tchendjou¹,

Kamla²,

Bouchet³

2020

Technium

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“…The methods employed in the reviewed literature (cf. Table 5) range from simple energy balancing calculations (e. g. [71,100,105]) to simulations (e. g. [80,95,103]), metaheuristics (e. g. genetic algorithm [70], discrete harmony search [89], artificial bee swarm optimization [90,91] or flower pollination algorithm [114]), mixedinteger linear optimizations (e. g. [31]) and multi-objective optimizations (e. g. [113]). When investigating the methods, it is striking that in most cases only simplified calculations are carried out.…”

Section: Methodologies and Modelsmentioning

confidence: 99%

Reviewing energy system modelling of decentralized energy autonomy

Weinand

Scheller

McKenna

2020

Energy

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Research attention on decentralized autonomous energy systems has increased exponentially in the past three decades, as demonstrated by the absolute number of publications and the share of these studies in the corpus of energy system modelling literature. This paper shows the status quo and future modelling needs for research on local autonomous energy systems. A total of 359 studies are roughly investigated, of which a subset of 123 in detail. The studies are assessed with respect to the characteristics of their methodology and applications, in order to derive common trends and insights. Most case studies apply to middle-income countries and only focus on the supply of electricity in the residential sector. Furthermore, many of the studies are comparable regarding objectives and applied methods. Local energy autonomy is associated with high costs, leading to levelized costs of electricity of 0.41 $/kWh on average. By analysing the studies, many improvements for future studies could be identified: the studies lack an analysis of the impact of autonomous energy systems on surrounding energy systems. In addition, the robust design of autonomous energy systems requires higher time resolutions and extreme conditions. Future research should also develop methodologies to consider local stakeholders and their preferences for energy systems.

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“…Technical characteristics of the photovoltaic panels are shown in such Table 2. 7,8,14,17,22 START SOC BAT (%) < 100 Calculate P RS , P load , SOC BAT , P BAT , P DG P RS -P BAT = P load…”

Section: Pv Modelingmentioning

confidence: 99%

“…14 BAT is used as an energy storage system in this study. The process of recharging and discharging the BATs during the time (t), is shown in Equations (8) and (9), the BAT technical characteristics are shown in Table 5. 8,9,24,28,58 BAT recharge process…”

Section: Dg Modelingmentioning

confidence: 99%

Techno‐economic evaluation of renewable energy systems combining PV‐WT‐HKT sources: Effects of energy management under Ecuadorian conditions

Arévalo

Benavides

Lata‐García

2020

Int Trans Electr Energ Syst

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Sustainable development reached a new energy paradigm in recent decades, by promoting renewable generation technologies. The present study performs a techno-economic analysis of several hybrid energy systems that combine wind generators, photovoltaic systems, hydrokinetic turbines, lead acid batteries, and diesel generators in southern Ecuador. From real data, the sizing optimization of each renewable system was done under three proposed energy control algorithms. Then, the combinations of renewable systems are compared based on costs, energy, and environment. Additionally, this study includes several sensitivity analyzes varying the cost of the components and fuel, minimum state of charge in batteries, scaled electric load and time step to better understand the impact caused in each renewable hybrid system. The results show that a system composed of three renewable sources under load following and cycle charging energy controls, is cheaper and less polluting with respect to any combination of sources proposed. In addition to this, the systems that include photovoltaic systems and diesel generators present lower cost, 0.36 US$/kWh in the best case. To reduce the operability of the diesel List of Symbols and Abbreviations: P PV , output power of a photovoltaic system (kW); Y PV , rated capacity of the photovoltaic array (kW); f PV , photovoltaic derating factor (%); G T , incident solar radiation on the photovoltaic array (kW/m 2); G T,STC , incident solar radiation at standard test conditions (kW/m 2); α P , power coefficient of photovoltaic array (%/ C); T c , photovoltaic cell temperature (C); T c,STC , photovoltaic cell temperature at standard test conditions (C); η mp , maximum power point efficiency of photovoltaic array at standard test conditions (%); τ, solar transmittance of the photovoltaic array (%); α, solar absorptance of the photovoltaic array (%); P WT , output power of wind turbine (kW); v cin , cut in wind speed (m/s); v count , cut off wind speed (m/s); v r , rated wind speed (m/s); P rated , nominal power limit of wind turbine (kW); ρ air , air density (kg/m 3); R, rotor radius of wind turbine (m); C p , power coefficient of wind turbine (%); v i , wind speed (m/s); P HKT , hydrokinetic turbine electrical power output (kW); ρ w , water density (kg/m 3); C p,H , hydrokinetic turbine performance coefficient (%); η HKT , combined hydrokinetic turbine-generator efficiency (%); A, hydrokinetic turbine sweep area (m 2); v, river speed (m/s); t, time (s); E HKT , energy of hydrokinetic turbine (kWh); P DG , diesel generator electrical power output (kW); η DG , diesel generator efficiency (%); E batt (t), energy stored in batteries over time t (kWh); E batt (t − 1), energy stored in batteries over time (t − 1) (kWh); σ, battery self-discharge rate; η batt , efficiency of battery during the charging process (%); P Linv (t), power of bidirectional converter in alternating current (kW); P inv (t), power of bidirectional converter in direct current (kW); η inv , efficiency of bidirectional converter (%); C...

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Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm

Cited by 212 publications

References 39 publications

Management of Hybrid Renewable Energy Systems Using Differential Hybrid Petri Nets

Management of Hybrid Renewable Energy Systems Using Differential Hybrid Petri Nets

Reviewing energy system modelling of decentralized energy autonomy

Techno‐economic evaluation of renewable energy systems combining PV‐WT‐HKT sources: Effects of energy management under Ecuadorian conditions

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