Methodology to Size an Optimal Stand-Alone PV/wind/diesel/battery System Minimizing the Levelized cost of Energy and the CO2 Emissions

Bilal, Boudy; Sabourin, Vincent; Kébé, Cheikh Mouhamed Fadel; Ndiaye, P. D.; Ndongo, Mamoudou

doi:10.1016/j.egypro.2011.12.1145

Cited by 95 publications

(32 citation statements)

References 18 publications

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“…[Condition #1: P MD_limit < P load_net with solar PV]:-Condition #1: P MD_limit < P load_net with solar PV P load_net = P load_actual − P PV (18) [Condition #2: P MD_limit > P load_net with solar PV]:-…”

Section: System Optimizationmentioning

confidence: 99%

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

et al. 2019

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Under the present electricity tariff structure in Malaysia, electricity billing on a monthly basis for commercial and industrial consumers includes the net consumption charges together with maximum demand (MD) charges. The use of batteries in combination with photovoltaic (PV) systems is projected to become a viable solution for energy management, in terms of peak load shaving. Based on the latest studies, maximum demand (MD) reduction can be accomplished via a solar PV-battery system based on a few measures such as load pattern, techno-economic traits, and electricity scheme. Based on these measures, the Maximum Demand Reduction (MDRed) Model is developed as an optimization tool for the solar PV-battery system. This paper shows that energy savings on net consumption and maximum demand can be maximized via optimal sizing of the solar PV-battery system using the MATLAB genetic algorithm (GA) tool. GA optimization results revealed that the optimal sizing of solar PV-battery system gives monthly energy savings of up to 20% of net consumption via solar PV self-consumption, 3% of maximum demand (MD) via MD shaving and 2% of surplus power supplied to grid via net energy metering (NEM) in regards to Malaysian electricity tariff scheme and cost of the overall system.

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Section: System Optimizationmentioning

confidence: 99%

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

et al. 2019

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“…When water is abundant, the cost optimization allows more energy to be produced from PV panels at this site for the reason given in the second paragraph of this section. Bilal et al [23] reported LCOE values in the range €1.77/kW h-€3.89/kW h for a stand-alone PVwind-diesel-battery system. In the present study, backup and energy storage devices (which would elevate the LCOE) were not taken into consideration.…”

Section: Resultsmentioning

confidence: 98%

Optimization of a PV–wind hybrid system under limited water resources

Madhlopa

Sparks

Keen

et al. 2015

Renewable and Sustainable Energy Reviews

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“…Tégani et al [50] used GA for optimal sizing of PV-wind hybrid system with a lifespan of 20 years. Multi-Objectives Genetic Algorithm approach is also used by Bilal et al [51] to design and optimize a stand-alone hybrid PV/wind/diesel/battery system minimizing the LCE and the CO 2 emission for Senegal.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems

Sinha

Chandel

2015

Renewable and Sustainable Energy Reviews

448

151

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Methodology to Size an Optimal Stand-Alone PV/wind/diesel/battery System Minimizing the Levelized cost of Energy and the CO2 Emissions

Cited by 95 publications

References 18 publications

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Optimization of a PV–wind hybrid system under limited water resources

Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems

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