研究目的
To find the optimum unit sizing of a PV-WT-Battery hybrid system components using the Jaya algorithm to fulfill the consumer's load at minimal cost while considering system reliability through LPSP constraints.
研究成果
The Jaya algorithm effectively optimizes the unit sizing of PV-WT-Battery hybrid systems, achieving minimal total annual cost while adhering to reliability constraints defined by LPSP_max. The PV-WT-Battery system is the most cost-effective across all LPSP_max values, followed by PV-Battery and WT-Battery systems. A trade-off exists between cost and reliability, with higher LPSP_max leading to lower costs. Future work should include comparisons with other optimization algorithms like GA and PSO.
研究不足
The study uses simulation-based optimization without physical experimentation; real-world variations and environmental factors may affect results. The Jaya algorithm's performance is compared only conceptually with other meta-heuristics, and no hardware implementation or detailed component specifications are provided, limiting practical applicability. The data is specific to Rafsanjan, Iran, which may not generalize to other locations.
1：Experimental Design and Method Selection:
The study uses the Jaya optimization algorithm to minimize the total annual cost (TAC) of a stand-alone hybrid renewable energy system (HRES) comprising PV panels, wind turbines (WTs), and batteries. The algorithm is chosen for its lack of algorithmic-specific parameters, relying only on common control parameters like population size and termination criteria. The system model is based on a DC bus architecture with DC-DC, AC-DC, and DC-AC converters.
2：Sample Selection and Data Sources:
Hourly data for solar insolation, ambient temperature, wind speed at 10m height, and consumer load profile for one year (8760 hours) are used, sourced from Rafsanjan, Iran, obtained from the Ministry of Energy, Statistics on Renewable Met Mast Stations (SATBA).
3：List of Experimental Equipment and Materials:
The simulation involves hypothetical components: PV panels, wind turbines, and batteries, with no specific brands or models mentioned. MATLAB R2016a software is used for simulations on a system with a 2.9 GHz Intel Core i7 processor and 8 GB RAM.
4：9 GHz Intel Core i7 processor and 8 GB RAM.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The Jaya algorithm is applied to optimize the number of PV panels (N_pv), WTs (N_wt), and batteries (N_b) within bounds (0-300 for PV, 0-200 for WT, 0-20,000 for batteries). The initial battery charge is set to 30% of nominal capacity. The algorithm iterates to minimize TAC while satisfying LPSP constraints, updating solutions based on best and worst candidates.
5：Data Analysis Methods:
Results are analyzed in terms of TAC values for different LPSP_max values (0%, 0.3%, 1%, 2%, 5%), comparing PV-WT-Battery, PV-Battery, and WT-Battery systems. Convergence plots and hourly power/storage profiles are generated to evaluate performance.
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