Research On Coordinated Operation Optimization Of "Wind-Storage-Load" Based On Market Transaction

With the depletion of fossil energy and the increasing ecological and environmental problems brought by it,"clean alternatives" have become more and more important,and wind power has developed rapidly worldwide due to its pollution-free and renewable characteristics.After the promulgation of Circular No.9,the reform of the power market is in full swing,and the market trading mechanism is constantly improved.It is an inevitable trend for wind power to directly participate in the competition in the power market.However,the fluctuating and intermittent nature of wind power output restricts wind power consumption and is not conducive to its participation in market competition.As flexible scheduling resources,energy storage systems and elastic loads can effectively deal with the uncertainty of wind power output.Therefore,this article takes the "wind-storage-load" joint system as the research object.Based on the modeling and analysis of the joint system,it studies the joint sytem’s coordinated optimization strategy for participating in the electricity market.The main research results are as follows:Firstly,wind power forecasting technology,operation characteristics of energy storage systems,and demand response characteristics of elastic loads are studied.A frequency division prediction method based on Hilbert-Huang transform(HHT)is proposed to predict wind power,and the original data is decomposed into high-frequency components and low-frequency components through empirical mode decomposition and Hilbert spectral analysis.The high-frequency component and the low-frequency component were predicted using the BP neural network method and the ARIMA prediction method respectively.For energy storage systems,their operation constraints and operating losses are analyzed.The relationship of AA-CAES between charging/discharging efficiency and charging/discharging power is studied and the power-efficiency curve is taken to describe the dynamic efficiency characteristics of energy storage.For elastic loads,the secondary clustering method combining the Ward system clustering method and the improved FCM method is used to cluster the user’s historical load data,and a secondary classification model is proposed to cluster the original data twice to get the refined power consumption pattern,then analyzing the load response characteristics from multiple dimensions.Secondly,according to the HHT based split frequency forecasting method to obtain the wind power forecast output,and considering the dynamic efficiency characteristics of the energy storage device,based on the three-stage spot market transactions,the day ahead optimal scheduling model and the day inside optimal adjustment model which aiming at the maximum revenue of the "wind-storage-load" joint system are established,and the difference balance is carried out in the real-time market.The final results show that the combination of wind power and energy storage system can effectively improve the economy of wind power generation;compared with the static efficiency model,considering the dynamic working efficiency characteristics of energy storage is more conducive to the economic benefits of the "wind-storage-load" joint system;the economic benefits of the joint system are related to the initial SOC value of energy storage,and appropriate initial SOC state of energy storage can help it play a more important role;the economic benefit of the three-stage settlement mode including the day inside market is higher than that of the two-stage settlement mode,and the abandoned wind power is smaller.Finally,the optimization research of "wind-storage-load" bidding strategy considering the uncertainty of wind power is proposed.This paper studies the wind speed probability distribution and wind speed scenario modeling.The market participation mode of the joint system is also set up,where the energy storage service provider and the elastic load aggregator mainly participate in the auxiliary service market to obtain income,and can also join the wind power provider to participate in the day ahead electricity market.The energy storage service provider realizes the arbitrage of peak valley price difference through "low-cost charging and high-cost discharging",and the elastic load aggregator solves the bidding deviation.A coordinated optimization model of "wind-storage-load" is established to maximize the profit of the joint system.The case study shows that the total revenue of the joint system is far greater than the sum of the revenue of wind power providers,energy storage service providers and elastic load aggregators participating in the market competition independently;and the respective revenue of the three parties are distributed reasonably according to the shapely value method.The revenue of wind power,energy storage and elastic load are all greater than their respective independent revenue,which shows that it is effective for the three parties to participate in the market bidding jointly.