研究目的
To optimize the size of an off-grid PV system with respect to the capacity shortage value, focusing on minimizing costs while maintaining system reliability.
研究成果
The optimization shows that increasing capacity shortage from 0% to 8% significantly reduces costs (NPC and IC by over 50%), but beyond 8%, system availability drops sharply without proportional cost benefits. O&M costs also impact NPC, with higher percentages increasing overall expenses. The optimal balance for cost-effectiveness and reliability is around 8% capacity shortage, but investor preferences for availability may influence the final decision.
研究不足
The study relies on simulation software (HOMER) and assumes specific conditions, such as the use of average market prices and generic components, which may not reflect real-world variations. The load data is based on a short measurement period (7 days) and assumed to be representative for a full year, potentially limiting accuracy. Additionally, the unpredictability of solar radiation and system performance in practice is not fully addressed.
1：Experimental Design and Method Selection:
The study uses HOMER software for simulation and optimization of an off-grid PV system model, which includes PV modules, a converter, batteries, and an electrical load. The design rationale is to find the optimal system size by varying capacity shortage and O&M costs.
2：Sample Selection and Data Sources:
Solar radiation data (GHI) is obtained from PVGIS for Osijek, Croatia, based on a 10-year period (2007-2016). Load data is measured from a residential home in Osijek over 7 days, with samples taken every 10 minutes and averaged to hourly values.
3：6). Load data is measured from a residential home in Osijek over 7 days, with samples taken every 10 minutes and averaged to hourly values.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: The model uses generic components from HOMER software, including PV modules, a converter, and Li-Ion batteries. Specific models or brands are not detailed; costs are based on average market prices.
4：Experimental Procedures and Operational Workflow:
The HOMER Optimizer is used to simulate different scenarios by varying capacity shortage (0% to 10%) and O&M costs (0% to 3%). The software calculates net present cost (NPC) and initial cost (IC) for each configuration.
5：Data Analysis Methods:
Sensitivity analysis is performed to examine the impact of capacity shortage and O&M on NPC and IC. Results are presented in tables and graphs, with trends analyzed to determine optimal system parameters.
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