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Optimal Sizing of PV-Storage Systems Based on Multi-Scenario Simulation and Marginal Analysis
by
Yang, Ying
, Alam Firoz
, Jin Yingai
in
Alternative energy sources
/ Batteries
/ Business metrics
/ capacity allocation
/ Consumption
/ Demand side management
/ Economic analysis
/ Efficiency
/ Energy storage
/ energy storage optimization
/ high penetration PV power plant
/ Industrial plant emissions
/ Marginal analysis
/ Optimization
/ Payback periods
/ power curtailment loss
/ Power plants
/ Renewable resources
/ Research methodology
/ Wind power
2025
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Optimal Sizing of PV-Storage Systems Based on Multi-Scenario Simulation and Marginal Analysis
by
Yang, Ying
, Alam Firoz
, Jin Yingai
in
Alternative energy sources
/ Batteries
/ Business metrics
/ capacity allocation
/ Consumption
/ Demand side management
/ Economic analysis
/ Efficiency
/ Energy storage
/ energy storage optimization
/ high penetration PV power plant
/ Industrial plant emissions
/ Marginal analysis
/ Optimization
/ Payback periods
/ power curtailment loss
/ Power plants
/ Renewable resources
/ Research methodology
/ Wind power
2025
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Optimal Sizing of PV-Storage Systems Based on Multi-Scenario Simulation and Marginal Analysis
by
Yang, Ying
, Alam Firoz
, Jin Yingai
in
Alternative energy sources
/ Batteries
/ Business metrics
/ capacity allocation
/ Consumption
/ Demand side management
/ Economic analysis
/ Efficiency
/ Energy storage
/ energy storage optimization
/ high penetration PV power plant
/ Industrial plant emissions
/ Marginal analysis
/ Optimization
/ Payback periods
/ power curtailment loss
/ Power plants
/ Renewable resources
/ Research methodology
/ Wind power
2025
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Optimal Sizing of PV-Storage Systems Based on Multi-Scenario Simulation and Marginal Analysis
Journal Article
Optimal Sizing of PV-Storage Systems Based on Multi-Scenario Simulation and Marginal Analysis
2025
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Overview
The issue of solar curtailment and generation limitations, driven by insufficient grid absorption capacity, is becoming increasingly severe, significantly reducing the capacity factor and economic returns of photovoltaic (PV) power plants. The present study proposes a scenario-based simulation framework, developed using PVsyst software (version 7.4), with a view to investigating the impact of collaborative optimisation using different energy storage capacities on PV integration. The construction of an optimisation model is undertaken with the dual objectives of minimising curtailment losses and maximising the capacity factor. Through the implementation of scenario simulations, a coordinated control strategy is devised for divergent storage capacities, incorporating a charging approach during periods of photovoltaic over-generation and a discharging approach during instances of under-generation. Such an approach is coupled with marginal benefit analysis to simulate system performance under a range of technical conditions. The findings of the present study demonstrate that the implementation of storage coordination optimisation has the potential to result in a substantial reduction in curtailment losses and enhancement of the capacity factor. As energy storage capacity increases from 0 MWh to 10 MWh, curtailment losses decrease by approximately 52%, and capacity factors improve by about 11%. However, as storage capacity increases, the marginal benefits decrease. When storage capacity reaches 9 MWh, and the marginal rate of return exhibits a distinct critical point with increasing storage capacity per unit. The most critical parameter influencing the MRR (Marginal Rate of Return) is the Power Curtailment, which is the primary source of losses, and increasing the Power curtailment can immediately liberate substantial amounts of high-value, otherwise-curtailed solar energy.
Publisher
MDPI AG
Subject
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