研究目的
To propose a novel photovoltaic-pumped hydro storage microgrid design that is more cost-effective than photovoltaic-battery systems, by modifying existing irrigation infrastructure to store energy at a low cost and manage energy generation, demand, water demand, energy tariff, and system losses efficiently.
研究成果
The proposed photovoltaic-pumped hydro storage microgrid design is a cost-effective and eco-friendly alternative to photovoltaic-battery systems, capable of reducing electricity costs by more than 31% compared to conventional methods. The system efficiently manages energy storage and irrigation, with a payback period of less than 3.2 years, making it an attractive option for rural areas.
研究不足
The study focuses on the integration of PHS with PV systems in rural farmhouses, which may limit its applicability to urban or non-agricultural settings. The efficiency of the PHS system is lower than that of battery storage systems, and the system's performance is highly dependent on the availability of water resources and suitable terrain for PHS.
1:Experimental Design and Method Selection:
The study involves designing a microgrid that integrates photovoltaic (PV) systems with pumped hydro storage (PHS) for energy storage, utilizing existing irrigation infrastructure. The methodology includes modifying irrigation systems to store surplus PV energy as gravitational potential energy and using it for electricity generation or irrigation.
2:Sample Selection and Data Sources:
The experimental setup includes a real pump and turbine to verify the performance of the proposed system. Data sources include measured data (PV power generation, pump flow rate, pump power, turbine flow rate, turbine power, precipitation, and evaporation) and forecast data (temperature, cloud cover percentage, relative humidity, wind speed, precipitation).
3:List of Experimental Equipment and Materials:
The experimental setup includes PV arrays, a pump, a hydro turbine, a reservoir, water level sensors, and valves for the PHS system.
4:Experimental Procedures and Operational Workflow:
The EMS controls the pump power and turbine flow rate based on current and future system states, energy generation, demand, water demand, and energy tariffs. The system is tested experimentally to validate the management system's performance.
5:Data Analysis Methods:
The study uses artificial neural networks (ANNs) for PV power and demand forecasting, and a genetic algorithm (GA) for optimization to minimize operating costs.
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