| As a flexible regulatory resource that can provide various auxiliary services,such as peak regulation and frequency regulation,peak shaving,power quality improvement,and emergency backup for the power grid,energy storage will play an important role in establishing a renewable energy-dominated new power system.However,due to the restriction of the operating characteristics and capacity,a single-type energy storage technique is difficult to cope with the multi-type regulation requirements in the modern power system.For instance,the stochastic fluctuations of renewables,deeply coupled with the uncertain behaviors of load and electric vehicles,will affect the supply-demand balance and operational reliability of the power system on different time scales.Joint configuration and coordinately complementing a variety of energy storage techniques,the hybrid energy storage system is used to achieve cooperative operation on multiple time scales,which is an important pathway to effectively support the stability,safety,and economy of the power grid under complex operating conditions.Thus,given the operation characteristics of different types of energy storage techniques in the distribution network,this dissertation focuses on the multiple regulatory functions of energy storage techniques,exploring the effects of coordinated complementarity of different energy storage techniques on the reliability,economy,renewable energy consumption,and three-phase power unbalance improvement of the distribution network.According to this,the optimal configuration and scheduling strategy of hybrid energy storage systems under different operation conditions is developed in this dissertation,which is expected as a theoretical support and application basis for the implementation of multi-type storage techniques in new power systems.The main contents of this dissertation can be safely drawn as follows:1)To improve the power supply reliability of the distribution network under contingencies,enhancing the load-supplied level from energy storage when the critical equipment is faulted,a bi-level stochastic expansion planning model of source-network-storage is formulated.A multi-scenario generation method considering wind,solar,and load is developed through the Latin Hypercube Sampling method to analyze the impact of multiple uncertainties on the planning and operation of the distribution network.At the planning level,based on the spanning tree theory,the joint expansion planning model of substations,distribution network lines,renewable energy units,and energy storage systems is established under normal operation mode to determine the optimal topology of the distribution network and the optimal allocation scheme of distribution network assets.At the operation level,the probabilistic model with random contingency is formulated,and then an optimization model aiming to minimize the present value of the cost of expected energy not supplied is proposed.Compared with the traditional methods,the case study shows that the present value of load loss cost in the proposed model is reduced by 8.16×10~6$and 3.82×10~6$,respectively,which validates that the proposed model can effectively improve the power supply reliability of the distribution network under contingencies.2)To alleviate the influence of multi-time scale imbalance characteristics of renewable energy,improving the hosting capacity of renewable energy in the distribution network,an optimal configuration strategy of the coordinated operation of seasonal hydrogen storage and battery energy storage is proposed.To avoid the operation risk caused by the uncertainties of wind-solar-load,the conditional value at risk function is used to evaluate the effect of the risk on distribution network operation.According to this,a risk-averse bi-level stochastic planning model is formulated in this dissertation.In the upper level,a multi-objective optimization model is developed to find the compromised solution between the investment cost of the hybrid energy storage system composed of hydrogen energy storage and battery energy storage and the renewable energy hosting capacity.The lower level is conducted on the day-ahead stage,where the stochastic scenarios are generated,and the price-based demand response strategy is used to cooperate with the hybrid energy storage system to improve the risk-resistance capability of the distribution network under random fluctuation.Compared with traditional methods,the case study in the proposed model shows that the installed capacity of renewable energy can be increased by 2.30MW and 0.37MW respectively,and the total benefit of DSO is increased by 28063.2$and 17823.7$,respectively,which effectively mitigate the seasonal imbalance characteristics of renewable energy and increase the consumption level of renewable energy.3)To quantify the impact of capacity degradation on battery lifetime and economic cost,improving the economy of the distribution network planning and operation,a unified stochastic planning model of energy storage systems and charging stations is proposed with the battery degradation of EV and ESS.To construct an optimization model comprised of multiple uncertainties,various probability density functions are used to describe the uncertainties of renewable energy,load demand,and random behavior of electric vehicles.Based on the half-cycle capacity degradation model,the capacity degradation cost of battery energy storage systems and grid-connected electric vehicles is evaluated and introduced into the objective function.The optimal configuration scheme and the optimal operation strategy of the distribution network can be obtained by minimizing the total investment and operation cost of the distribution network,including investment cost,substation operation cost,electricity purchasing cost,network loss cost,and battery degradation cost.According to the simulation analysis,the capacity loss of energy storage is improved by 43.37%,which is effective in increasing the operation economy of the distribution network.4)To alleviate the multi-time scale three-phase unbalance issue,improving the power supply quality and operation safety of the distribution network,a multistage scheduling model with the hybrid energy storage system consisting of battery,electric vehicle,and supercapacitor is presented.In the day-ahead stage,the penalty cost of the three-phase unbalance and the capacity degradation cost of the hybrid energy storage system are introduced into the objective function,while the influence of multiple uncertainties is taken into account.A chance-constraint-based coordinated scheduling model of the hybrid energy storage system is proposed to minimize the operating cost of the distribution network while reducing the three-phase power imbalance caused by single-phase connected renewable energy and random charging behaviors of electric vehicles.In the intra-day stage,the operation strategy of the supercapacitor is formulated by the implementation of the rolling optimization method to quickly smooth out the real-time power unbalance induced by the instantaneous fluctuations of renewables.A linearized method is developed in this dissertation to linearize the nonconvex issue caused by the three-phase power flow model to construct a multistage linearized stochastic optimization model.The simulation results show that compared with two traditional models,the real-time total power unbalance of the proposed method is reduced by 3.01%and 6.39%,respectively,which verifies the good performance of the proposed model in suppressing three-phase power unbalance.Through a large number of simulation analyses,this dissertation proves that the supply-demand balance of the distribution network,the consumption of renewable energy,and the operation reliability and economy of the distribution network can be effectively guaranteed by optimizing the configuration of multiple types of energy storage techniques under different operation conditions and realizing the coordinated complementarity of hybrid energy storage techniques on multiple time scales.The proposed method can provide a scientific scheme and valuable reference for the distribution network configuration of hybrid energy storage systems under complex operating conditions coupled with multiple uncertainties.Also,it is conducive to promoting the development of hybrid energy storage techniques in new power systems. |
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