Research On Optimal Operation Of Distribution Network With Renewable Energy

As the resource shortage and environmental pollution becoming more and more serious,countries have made great efforts to develop renewable energy.Thanks to advanced techniques,distribution generators(DGs)especially wind turbines and solar panels directly integrate with distribution power networks(DPNs)and DPNs could do more than simply receiving electric energy.Admittedly,renewable energy penetrations contributes to saving resources and protecting environment.However,renewable energy such as wind and photovoltaic are notorious for their uncertainties and intermittency,which brings about new challenges to the operations of DPNs.In last decades,scholars focus on network loss,secure voltage,etc.Recently,as increasing DGs connect to DPNs,the absorption of renewable energy has been paid more attention.Distribution power network reconfiguration(DPNR)and load dispatch(LD)are two of the important techniques in DPNs.Thereby,with high renewable energy integrated,they are investigated in this paper to enhance the absorption of renewable energy.Specifically,this thesis proposes a two-stage stochastic DPNR model consisted by master problem stage and slave problem stage.To establish and solve this model,this paper focuses on:1)To deal with the uncertainties of renewable energy,machine learning method is adopted to fit the historical data of wind speed and sunshine irradiance and during the optimal dispatching of distribution network the relevant parameters of wind speed and irradiance could be predicted via learnt model.On this basis,the scenario reduction technique is used to generate typical samples.Consequently,the output samples of distributed wind turbines and solar panels are obtained;2)In the slave problem stage,this paper considers the load dispatch and proposes a new optimal power flow(OPF)model.Meanwhile,its equivalent model is derived.The proposed OPF model ensures that the constraints required for the safe operation of the DPNs are not activated by optimizing the value of curtailment and load dispatch,and also helps to promote the consumption of wind power and photovoltaics;3)In the master problem stage,DPNR is considered,which further optimizes the topology of DPN to maximize the absorption of renewable energy and improve the voltage stability.Specifically,it is formulated as a multi-objective optimization problem(MOP).Meanwhile,a modified multi-objective Bayesian optimization algorithm(MMOBOA)is applied to yield a Pareto front for DPNR,which shows the trade-off between absorption rate and voltage stability.Afterwards,the technique for order preference by similarity to an ideal solution(TOPSIS)is used to determine the dispatching solution.