Game Research Of Virtual Power Plant With Combined Heat And Power Units

There is a situation of low energy utilization rate and serious primary energy waste which exists in China,the further Large-scale development of renewable energy,reduction of environmental contamination and less emissions of carbon have become the transformation target of China’s power system.However,during the heating period,the reverse peak shaving characteristics of wind power make the"wind-heat contradiction" particularly serious,leading to the abandonment of wind power and electricity curtailment in some parts of northern China and fails to achieve better economic benefits.Virtual Power Plant(VPP)is a power management system that uses advanced information communication technology.Through a variety of strategies and scheduling,it is easy to coordinate various power resources to achieve complementary advantages.Game theory as a method of energy traders participate in the competition,VPP can use the theory to participate in all kinds of market to achieve different purposes,on the one hand the non-cooperative game theory can be used to realize the energy trader fight with each other for their own best benefits of the game,on the other hand cooperative game can be achieved the bidding and distribution strategy of different energy traders.So the game of virtual power plant with cogeneration unit is studied in this paper.During the heating season,combined heat and power(CHP)units needs to operate by "setting electricity by heat",a large number of pure condensing units are forced to shut down,and the peak regulation resources in system are insufficient,leading to limited consumption of renewable energy in some areas,though conventional energy units of northern areas can be aggregated into a interests in VPP,but the energy traders may belong to different business companies,and they still have individual economic independence,therefore chapter two studied a internal game model of VPP dispatching the user load resources to join in the game model by using comfort which converts the heat load to a flexible adjustable resources,participants’bidding price and electricity output are decision variables,the target function is to minimize the operating cost of VPP;And further consider the strategies of comfort compensation and heat storage tank to improve the flexibility of cogeneration units.The analysis of calculation examples shows that the comfort compensation and other strategies in this paper can not only effectively increases the consumption of renewable energy,but also cuts down the operating cost.Secondly considering where energy companies can be more profitable by participating in multiple energy markets,setting up a multi-objective framework of the electricity market,the thermal energy market and green certifications market,a non-cooperative game model is established to achieve the lowest purchase cost in the whole market under the condition of users’ thermal and electrical demand get satisfied,and by establishing a robust regret degree model to solve the uncertainties of renewable energy;The results show that the green certifications market can effectively increase consumption of renewable energy,lower the overall cost of three markets,what’s more,the different weight ratios of the three markets will affect the game results.When the proportion of green certifications market is too high,it will affect the overall income.Therefore,the market decision maker needs to select the appropriate important coefficient when making the scheduling scheme.In addition,using the scheduling model based on robust regret degree to participate in the game can effectively deal with the uncertainty of renewable energy,which is helpful for decision makers to make the best scheduling scheme to adapt to randomness.Finally,considering that thermal power plants in the northern regions often need to participate in deep peak regulation,this paper establishes a bidding strategy considering multiple uncertainties for the VPP participating in deep peak regulation of auxiliary service market.Latin hypercube Scene(LHS)method is used to describle the uncertainty of user load and wind power,and considering the uncertainty of a competitor’s quotation and bid quantity and corresponding constraints,pre-clearance is performed for each participant in order to get the optimal bidding strategies,and using queuing method to get the marginal clearing price and clearing volume of deep peak regulation market;On this basis,VPP optimize the internal resources scheduling with the goal of maximizing the net revenue,and considering the use of shapley distribution method is not conducive to play each specialty of the unit,thus affecting the peakload enthusiasm,A coefficient considering the historical contribution and the capacity of peak regulation is introduced to modify the apportion method.The results proved the validity of the two-staged model.Through the pre-clearance,a better bidding strategy can be selected for the participants to achieve higher benefits,and the introduced correction factor can motivate more units to offer more peak regulation services.