Study On Trading Strategies Of Large Consumers Direct-purchasing

Large consumers will have chance to be the independent business entity based on direct-purchasing,which can obtain electrical energy by means of purchasing electricity in multiple power markets.On the one hand,large consumers can reduce the electric cost by reasonable purchasing portfolio,while on the other large consumers may face the different decision risk arising from the different purchasing portfolio.Additionally,Under the background of the vigorous development for distributed generation technology and vigorous promotion of the national energy conservation policies,some high energy-consuming large consumers may have access to distributed power supply.In this case,large consumers will change roles from traditional power consumers to prosumers,trading risk is also increasing and their trading behavior will be more complicated and various.In competitive electricity market,large consumers are commonly risk-averse decision makers,therefore,this paper mainly focus on the trading strategies of risk-averse large consumers based on direct-purchasing.First of all,this paper analyzes risk factors of large consumers directly involved in multiple trading markets and mainly focus on the introduction of price risk and credit risk.Then,considering the condition of large consumers which have access to the distributed power supply directly involved in multiple power markets,this paper takes large consumers containing wind power,solar power and energy storage for research objects and mostly analyses the unbalanced cost for large consumers containing wind power,solar power and energy storage directly involved in day-ahead market.After that,to risk including the loss of uncertainty and size and other characteristics,based on the analysis and comparison of several commonly used risk measurement indexes,this paper presents a new method using the conditional value at risk and the information entropy to measure the risk of purchasing electricity and constructs the optimal purchasing portfblio model with a target of minimum the conditional value at risk and the information entropy by controlling the actual purchase cost which is higher than the given target purchase cost in a certain confidence level at chance constrained form.This model can be calculated based on fuzzy multi-objective particle swarm algorithm.This paper takes advantages of the model above to analyze the impact on power consumption distribution in direct-purchasing market,day-ahead market,electricity options market and its captive power plant for large consumers when the changes of market parameters and model parameters are considered.The results of example shows that the proposed model can evaluate the risk of purchasing portfolio comprehensively,achieve the purpose of controlling the power purchasing cost and effectively reduce the purchasing loss of uncertainty and size of expected tail loss.Considering that large consumers may have access to distributed power supply,this paper focus on the strategy of trading for large consumers participating in day-ahead market which own distributed wind turbines,distributed photovoltaic cells and battery energy storage under the quantity of direct-purchasing contract decomposed to day-ahead is determined.Using the discrete conditional value at risk to quantify risk and considering the effect of the discharge loss of battery energy storage and the unbalanced cost caused by the volatility of wind turbine output and photovoltaic output,by introducing risk trade-off coefficient,this paper constructs decision-making and optimization model for large consumers containing wind power,solar power and energy storage directly involved in day-ahead market to maximize the expected profit and minimize the trading risk,and utilizes the mixed integer programming solver CPLEX to solve it.A example illustrates the influence of benefits and risk losses participating in day-ahead market for large consumers containing wind power,solar power and energy storage when battery energy storage and risk trade-off coefficient are considered.