Optimal Scheduling Strategy Considering The Response Uncertainty Of Load Aggregators And Electric Vehicles In Grid

In recent years,with the rapid development of smart grid technology,wireless communication technology and advanced measurement system,conditions have been provided for the implementation of load aggregation scheduling.A large number of small and medium-sized users participating in the market via load aggregators,largescale electric vehicle integrated in power grids and new energy grid connection,will bring threat to the reliable operation of power grid.Based on this problem,the paper studies the response uncertainty of the load aggregators,the electric vehicle and the real-time power fluctuation of the new energy in order to achieve the win-win goal of stable operation and user benefit.According to the users' electricity consumption history data and electric vehicle travel statistics,the load sampling method of load aggregators clustering and electric vehicle disordered charge and discharge load distribution are established.In the case of guaranteeing users personalized travel demand in the future,expectations for charging and discharging of charge state are proposed considering distance traveled spare margin coefficients,then the charge urgent level and discharging abundance index are built,and electric vehicles regulable capacity are quantified and sorted so that the upper and lower limits of time series power regulable domain could be determined.Based on these,for the minimization of grid operating cost,an optimal scheduling model is proposed to meet the demand response of load aggregators and the orderly charge and discharge of electric vehicle,and a bilayer particle swarm optimization is proposed to solve it.the validity of the model is verified by the modified IEEE 9-bus example.The optimal scheduling model of time-space charge and discharge price considering load aggregators and the response reliability of electric vehicle is established.In space,the node price model is established for each node considering the optimal trend of the spatial characteristic,and guiding the electric vehicle users to change the charge and discharge habits through real-time electricity price,and reducing the running cost.In the terms of time,the marginal cost of electric vehicle discharge and power generation side of the cost of electricity are taken into account to determine the upper and lower boundaries of the discharge price,and the principles of consumer psychology are introduced to characterize the response uncertainty of electric vehicle users to electricity price,and pricing strategies for charge and discharge prices considering load aggregators and electric vehicle response reliability are made,then,the optimal scheduling model is established for the time scales of load aggregators and electric vehicles..The example analysis of the modified IEEE 33-bus verified that the model can achieve a win-win goal of grid operating cost,scheduling strategy response reliability and user economic benefit.The double real-time scheduling model based on priority scheduling is created and it could provide coordination control for load aggregators to consume the real-time power fluctuation caused by the uncertainty of the new energy integrated and the response of the electric vehicle.At the macro layer,the contribution degree and confidence degree of the electricity indexes are defined according to the electrical risk characteristics of load aggregators to quantify the risk.From the perspective of subjective and objective point of view,the comprehensive evaluation of each indexes is calculated using the analytic hierarchy process and entropy weight method to determine the scheduling priority in accordance with the specific requirements.Operators can make the real-time scheduling scheme of the load aggregators based on the scheduling priority.At the micro layer in order to reduce the response uncertainty of the load aggregators when real-time power fluctuations are disposed of at the macro layer,the compensation degree for interruptible time and the consumptive contribution weight are put forward respectively considering the differences of the work time in the load aggregators and users economic level.Finally The example analysis of the modified real micro-grid show the scientific character and effectiveness of the proposed model.