Optimal Sizing And Techno-economical Analysis Of Stand-alone Hybrid Renewable Energy Systems

Unitilization of renewable energy has been a very important research topic in past decades.However,the characteristics of instability and intermittency create serous challenge on the large-scale utilization of variable renewable energy,such as solar and wind.Therefore,this thesis combines energy storage systems,including batteries and fuel cells,with renewable energy to form a stand-alone hybrid renewable energy system,which can effectively improve the utilization of variable renewable energy and provide sollutions to power supply in remote areas like country side and islands.Batteries are widely applied to PV-based stand-alone renewable energy systemsfor energy storage and dispatch.At present,battery technology,which is rapidly developing,has the advantage of being easy to implement and fast response and requires improvements in the efficiency of energy conversion,safty and economic performance.By comparison,fuel cells(hydrogen generation with electrolyzers)is a very popular technology for energy storage in recent years due to its superiority in long-term energy storage,energy intensity and environmental impacts.However,its economic performance is still worse than batteries in hybrid energy systems.In general,most existing studies implemented optimization of a hybrid energy system with battreries or fuel cells under a specific situation and there is a lack of systematic comparison between the two types of systems for energy storage.Therefore,this thesis established two systems,namely a photovoltaic(PV)/battery system and a PV/fuel cell(electrolyzer)system,and compared the reliability and economic performance of the two systems using genetic algorithms.Firstly,the study defined the mathematical settings of every equipment and the control strategy in the parallel systems.Five scenarios with different weather and load setting were assumed to represent the situations in reality.Reliability and economic performance of the systems were employed as the objectives of system operation in different scenarios and genetic algorithms were used to solve the multi-objective optimization problems.Results show that,in all scenarios,the PV/fuel cell(electrolyzer)system has a higher rate of energy utilization than the PV/battery system does.In terms of economic performance,the photovoltaic/battery system performs better than the PV/fuel cell(electrolyzer)system does,only except in the scenario,where weather-load suitability is extremely low.Moreover,a sensitivity analysis of cost of energy(COE),life cycle cost(LCC)and dump load was implemented to the two systems regarding four factors,including the proportion of days without sunshine,reliability LPSP,fuel cell system cost and photovoltaic cost.Results show that,the PV/fuel cell(electrolyzer)system has a higher rate of energy utilization than the PV/battery system does,regardless the changes in the four factors.The economic performance of the PV/fuel cell(electrolyzer)system can overtake the PV/battery system when the proportion of days without sunshine exceeds 20%,LPSP exceeds 4%,or the cost of the fuel cell system is lower than 80%of the original price.