Research On Photovoltaic Operation Control And Benefit Evaluation

With the problems of energy shortages,environmental pollution,global warming and other issues becoming increasingly serious,the researches of renewable energy has turned into hot spots,one of which is the development of photovoltaic technology.This dissertation focuses on the research of photovoltaic generation system operation control technology and benefit evaluation.The main contents include:grid-connected operation control of photovoltaic power generation system;coordinated control strategy for photovoltaic generation and hybrid energy storage system;coordinated scheduling optimization for photovoltaic generation and electric vehicles charging;comprehensive benefit evaluation of photovoltaic power plant.Specific research contents and achievements are summarized as follows:(1)In view of the independent photovoltaic(PV)generation system,corresponding grid-connected operation control strategies are researched.In the first place,the basic principle of photovoltaic generation and the system composition is introduced.The unit simulation model and equivalent aggregation model of grid-connected PV systems are established.Under partially shaded conditions,there are multiple local MPPs on power-voltage characteristic curve of PV array.As a result.an improved MPPT algorithm named POC algorithm is proposed.A novel control method for three-phase grid-connected PV inverter based on differential evolution algorithm is described.Simulation results demonstrate that the PWM control sequences of three-phase grid-connected inverter optimized by DE algorithm can reduce the THD of the output waveform to a great extent.The PV generation islanding detection principle and method are then introduced,on the basis of whicha combined islanding detection method is proposed to avoid misjudgment.Finally,simulations are carried out to analyze the control strategy of low voltage ride through in PV power substations.(2)For micro-grid containing PV generation system and hybrid energy storage system,the coordinated control strategies are studied.Characteristics and mathematical models of the super capacitor and battery are introduced respectively.Then,the topological structures of the hybrid energy storage system composed by super capacitors and batteries are analyzed.Combined with the energy distribution for hybrid energy storage system,the simulation model of a microgrid including PV generation and hybrid energy storage is established to study the output power fluctuation suppression strategy of PV generation.Simulation results show that the control strategy could reduce the PV output power fluctuation significantly.Rational and effective energy distribution for hybrid energy systems could contribute to stabilize the output power on the premise of avoiding the state of charge that exceeds the limit.What’s more,the synthetical control strategy for smooth switching between grid-connected and islanded operation modes of micro-grid based on hybrid energy storage system is studied subsequently.Micro-grid including photovoltaic generation and hybrid energy storage system in islanding operation mode,the voltage-frequency fluctuation of the system would become greater due to the effect of impact load and the absence of large grid support.To solve this problem,a new coordinated control strategy is proposed.Super capacitor is used to track and compensate the active and reactive currents of impact load.In addition,model current predictive control method is applied to control the super capacitor inverter.According to the simulation results,the model current predictive control method is effective.Besides,compared to the control method with no compensation for impact load,the proposed control strategy could restrain the voltage-frequency fluctuation of the system within allowable range,and ensure the reliability and stability of the micro-grid.Furthermore,the model current predictive control method has greater improvement in aspect of harmonic content for inverter output current compared to the traditional PI control method.(3)Aimed at optimal charging strategy of electric vehicle(EV)charging,coordinated scheduling problem of PV generation and EV charging is studied.To achieve coordinated scheduling of PV generation and EVs charging,a three-objective optimization model with objectives of minimizing the fluctuation of PV output power,minimizing the EVs’ charging total cost and maximizing the EVs SOC is proposed.In order to solve the established multi-objective optimization model,multi-objective optimization problem is described and meshing method is integrated into the basic differential evolution cellular(DECell)genetic algorithm for the improvement of distributivity.As a result,an improved differential evolution cellular(IDECell)genetic algorithm is developed.Then,the feasibility and superiority of IDECell algorithm are verified through algorithm performance tests.Applying the proposed IDECell algorithm to the established model,the corresponding Pareto sets are gained,as a result,the optimal strategy could be selected and its effectiveness is verified by the simulation results.(4)Focusing on the problem of operating performance and Comprehensive benefit evaluation of photovoltaic generation.Firstly,the evaluation methods and procedure of photovoltaic power plant performance are investigated,and the corresponding assessment indicators are proposed.According to the proposed evaluation method,two photovoltaic power plants in Changzhou are evaluated and analyzed.On this basis,comprehensive benefit assessment methods of the photovoltaic power plants are studied.Comprehensive benefit evaluation system of photovoltaic power plants is constructed based on a combination of economic and environmental benefits of PV power plant indicators.With reference to the matter element model extension theory,a comprehensive benefits assessment model of photovoltaic power station is established.Then,AHP and entropy weight method is combined to calculate the weight coefficients of each indicator in the evaluation model.At last,the proposed comprehensive evaluation model and method are verified by a computational example.