Coordination Management Strategy For Loss And Voltage Of Distribution Network In Renewable Energy Environment

Energy and environmental crisis makes renewable resource such as solar and wind resource attract people's attention increasingly.Also,the zero-emission characteristics of electric vehicles make it gradually become a new trend of the development of the automobile industry.The output of renewable energy is affected by several factors such as weather,geographical location and seasonal changes.It is intermittent and uncertain.The uncertainty of users' vehicle behavior also makes the charging behavior of electric vehicles random.These uncertainties seriously impact the safety of distributed power distribution networks.The energy storage system is capable of switching between the two in real time with its'source-load' characteristic and can be used as a device for suppressing the intermittent output of renewable energy.The new energy distribution network is a system in which renewable energy,electric vehicles and energy storage devices coexist.How to solve the line loss and voltage cooperative management of the distribution network under the"source-load-vehicle-storage" coexistence environment and ensure the safety of the distributed power distribution network has become an urgent problem in the power industry.Based on the theory of fuzzy sets and cone programming,this study investigates two things from the perspective of line loss and voltage cooperative management of new energy distribution networks.For one thing,the influence of the uncertainty of distributed power output,the uncertainty of electric vehicle charging and the uncertainty of load power on the distribution of power flow in distribution network are studied.For the other thing,this study comprehensively considers various uncertain factors,establishes a variety of collaborative management models and solving algorithms,and systematically solves the problem of line loss and voltage coordination management of distribution network in new energy environment:(1)The power loss and voltage deviation in the distribution network is a pair of mutually restrictive and contradictory behaviors,research on line loss and voltage coordination optimization management is carried on.The relationship model between active power loss and node voltage of distribution network is analyzed.The output of DGs is used as the control variable to construct a multi-objective coordinated optimization model with the minimum line loss index and voltage deviation index as the objective function.The advantages of two optimization algorithms,PSO and simulated annealing particle swarm optimization(SAPSO)are compared.In the two charging modes of EVs,SAPSO is applied to multi-objective coordination optimization model optimization,and the best solution for line loss and voltage cooperative management of new energy distribution network is obtained.It is valid to verify the optimization model and algorithm with the IEEE-118 distribution network.(2)Aiming at the problem of line loss and voltage coordination optimization management in the distributed power supply and electric vehicle distribution network,a stochastic second-order cone programming method is introduced to consider the electric vehicle charging load and the general user load separately to achieve optimal management.Considering energy saving and emission reduction and grid operation safety factors,the total line loss of the distribution network is set as the objective function.Considering the system operation constraints,the objective function is divided into two parts according to the idea of stochastic second-order cone programming.The first part is the line loss caused by the general load operation of the distribution network.The second part is the line loss caused by the charging load of the electric vehicle.The stochastic second-order cone programming model,which sets the distributed power output power as the optimization variable,is constructed.The Monte Carlo method is used to simmulate the load of an electric vehicle,and the interior point method is embedded to solve the model of the stochastic second-order cone programming.The effectiveness of the proposed method is verified by an IEEE-69 node power distribution system.(3)Aiming at the stochastic fuzzy characteristics of uncertainties such as wind speed,illumination intensity and electric vehicle charging load in the new energy environment,the line loss and voltage cooperation management of new energy distribution network is studied based on the theory of probability statistics and fuzzy sets.Firstly,according to the principle of random fuzzy compatibility,the probability density function of uncertainties such as wind speed,illumination intensity and electric vehicle charging load is transformed into a probability distribution function.Combined with the wind speed-power relationship of the wind turbine and the light intensity-power relationship of the photovoltaic generator,the probability distribution function of the active output of the wind turbine and the photovoltaic generator set is obtained.Thus the wind power,the photovoltaic power and the electric vehicle charging power become simultaneously random fuzzy variables with randomness and ambiguity.A mathematical model of stochastic fuzzy chance constrained programming with line loss and voltage coordination management with random fuzzy variables is established.The improved NSGA-II algorithm is used to solve the stochastic fuzzy optimization model.Finally,the effectiveness of the scheme is verified by the improved IEEE-33 node distribution network model.(4)Aiming at the risk caused by the uncertainty of DGs output and EVs charging in the new energy distribution network,the multi-objective cooperation optimization model for line loss and voltage deviation is established.The model is restrained by the CVaR line loss risk and the CVaR voltage risk.The DG output is set as the control variable in the model.Variable substitution is used to transform the original optimization model into a second-order cone programming model,and the original dual interior point method is used to solve the problem.The effectiveness of the method is tested with an IEEE-118 node power distribution system.