Optimal Capacity Configuration Of Wind-Photovoltaic-Pumped Storage Hybrid System

Nowadays,the construction of a hybrid system composed of wind power,photovoltaic(PV)power and pumped storage is considered an effective way to increase the utilization rate of wind and solar energy resources significantly and ensure the safe and stable operation of the system.The key to improve the market share of the hybrid system is to fully consider the performance of the system in build and running cost,economic benefit,power supply dependability,pollutant discharge and other aspects,and to realize optimal capacity configuration for the studied area.In this thesis,the key issues in the capacity configuration process of off-grid and grid-connected system were studied respectively,and the capacity configuration of hybrid system was realized,and a relatively complete set of research methods for optimal capacity configuration was formed.The work of this thesis mainly included the following three aspects:(1)The mathematical models of the main components of the hybrid system were constructed.This thesis introduced the operating principles and output features of wind power,PV power and pumped storage in the hybrid system,and built the wind power models including the total power of the fan,wind speed probability distribution,wind speed at the height of the fan hub,and wind speed-output power function.PV power models including PV cell output current,solar radiation intensity probability distribution,PV power performance and tilt angle relationship function,PV output power;Pumped storage models including pumping and generating power,upper reservoir water volume and energy storage.(2)For off-grid hybrid system,a capacity configuration method based on hybrid optimization of multiple energy resources(HOMER)software was proposed.According to the actual data of a suburban rural district in China,an off-grid hybrid system was established,and the optimal capacity configuration scheme suitable for the study area was obtained by HOMER solution.The results showed that the off-grid hybrid system could maintain continuous and stable operation,and the optimal capacity configuration scheme was feasible.In addition,wind speed,solar radiation,loss of power supply probability(LPSP),the initial investment costs of wind turbine,PV cell and pumped storage system were selected as sensitivity variables to analyze the sensitivity of the system.(3)For grid-connected hybrid system,an optimal capacity configuration method considering the carbon emissions in the whole life cycle of the system was proposed.In this thesis,a grid-connected hybrid system was developed for an offshore island in China,and the fast and elitist non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)was used to achieve a multi-objective optimization solution from three objective functions of minimum cost,maximum economic benefit and minimum carbon emission,and the gray relation analysis(GRA)was applied for decision making to obtain the optimal capacity configuration scheme applicable to the studied area.The results showed that the grid-connected hybrid system using the optimal capacity configuration scheme could ensure continuous and stable power supply on two sample days with different operating conditions.The curtailment rate(CR)and loss of load probability(LOLP)of the system were 0%and 0.06%respectively.Finally,the influence of different grey relational degrees,influence factor weights,different system combinations,different access rates,and different optimization algorithms and decision methods on capacity configuration of the hybrid system were comprehensively analyzed.The research in this thesis enriches the correlation theories of optimal capacity configuration of the Wind-PV-Pumped Storage hybrid system,expands the application of optimization calculation software and artificial intelligence algorithm in system capacity configuration and forms a relatively complete set of research methods for optimal capacity configuration of the hybrid system,which has certain reference value to improve the planning and design accuracy of renewable energy power systems.