Optimized Dispatch Control Of Thermoelectric Decoupling Of CHP Unit

The proportion of highly random renewable energy on-grid has been increasing year by year,which has weakened the power system’s peak regulation capability.Coal-fired units are the main force of peak regulation sources in China.However,the Northeast Power Grid in the alpine region,most of the coal-fired units in this area are combined heat and power(CHP)units.The CHP unit is affected by the “power determined by heat”operation constraint,and its peak regulation capability is limited,which exacerbates the peak regulation pressure of the power grid.Therefore,fully exploiting the deep peak regulation capability of the CHP unit is an idea to solve such problems.However,due to the high cost of retrofitting,the CHP unit is not willing to perform deep peak regulation.However,after the establishment of the deep peak regulation auxiliary service market,CHP units can benefit from the provision of deep peak regulation auxiliary service,which has stimulated their enthusiasm for flexibility and retrofitting.Therefore,this article analyzes how to formulate a reasonable bidding strategy to maximize the revenue when the CHP unit participates in the deep peak regulation auxiliary service market and the electricity market at the same time.The main research contents are as follows:(1)Analyzes the modeling and evaluation methods of uncertain parameters including scenario generation and reduction and evaluation indicators,risk management and conditional value-at-risk(CVa R)indicators,and analyzes the generation of competitor quote scenario sets in the deep peak regulation auxiliary service market process.The process of solving the mathematical model of the deep peak regulation auxiliary service clearing is analyzed.(2)Established a deep peak regulation auxiliary service market bidding strategy based on a two-stage stochastic programming model and using thermal storage tank to power and heat decoupling.The first-stage scheduling model first evaluated the quality of the load scenario generated by the Latin Hypercube Sampling(LHS)algorithm using relevant evaluation indicators.Then,a dynamic queuing algorithm is used to solve the deep peak regulation auxiliary service market clearing model to obtain the market clearing price and the possible quotation,bidding generation capacity,and bidding time period of all market participants,including strategic subject and its competitors.The second-stage scheduling model aims at maximizing the profit of the CHP units,and solves the final bidding coefficient.The example results show that,compared with the Monte Carlo algorithm,the scenario generated by Latin hypercube sampling is more useful as an input for the scheduling model.After reducing the number of scenario to the threshold and continuing to increase the number of retained scenario,the change in total profit of CHP units is no longer significant.In addition,the benefits of participating in the deep peak regulation auxiliary service market and the electricity market at the same time are higher than the benefits of participating in only one of the markets,and the use of the heat storage tank will further increase the benefits.(3)A bidding strategy based on a two-stage stochastic programming risk-averse model and a deep peak regulation auxiliary service market for CHP units utilizing the district heating network energy storage was established.The first-stage scheduling model uses the same data processing method in(2).The second-stage scheduling model measures the risk of profit from the CHP unit through the conditional value-at-risk indicator,and determines the final bidding coefficient after comprehensively considering the expected profit and risk.The simulation results show that,it is feasible to make use of the energy storage capacity of the district heating network.Only the time period when the predicted market clearing price of the deep peak regulation auxiliary service market is higher than the on-grid electricity price of coal-fired units is the time period for the final participation in the deep peak regulation auxiliary service market bidding.When considering risk factors,strategic subject tend to reduce bidding generation capacity and possible quotation in order to win bids as much as possible.As the risk aversion coefficient increases,the more conservative the bidding strategy adopted by the strategic subject.By rationally configuring the risk avoidance coefficient,a compromise solution that takes into account expected profit and risk factors can be obtained.