Research On Trading Mechanism And Strategy Of Multi-energy Market

Under the background of low carbon policy implementation,multi-energy system is the key technology to improve energy utilization efficiency and transform energy structure.The energy sharing and collaborative operation of multi-energy systems in a market environment is conducive to tapping the substitution potential between energy sources,realizing flexible conversion,transportation as well as consumption of different energy sources,promoting renewable energy consumption under large scale,achieving optimal resource allocation and promoting the low-carbon development of multi-energy systems.For multi-energy coupled systems/networks,improving energy utilization efficiency,energy balance under the fluctuation of renewable energy output,decision making methods considering trader characteristics have significant differences in modeling methods and solution algorithms in different scenarios and cannot be treated as equivalent.In view of this,this paper investigates multi-energy systems in terms of market trading mechanism construction and strategy optimization according to different time scales and diverse market models,respectively,for the deviated quantity balance in trading,so as to improve the social welfare and operational efficiency of the market.The specific contents include:1.A medium-and long-term trading mechanism for auxiliary services under the gaselectricity market is proposed.Aiming at the current situation that the cost of auxiliary services increases due to the increase of domestic renewable energy market trading share,but no perfect auxiliary service market mechanism has been formed,which makes it difficult to recover the cost of standby capacity of thermal power units,this paper proposes a medium-and long-term trading model based on system dynamics of gas-electricity coupling.Firstly,simulation analysis is conducted on the basis of the existing generation rights transfer trading mechanism,while a trading model with decoupled main energy market and auxiliary service market is constructed.Secondly,the system dynamics is used to optimize the key factors in the market trading to achieve the balance of market supply and demand and maximize the market revenue of RE.The results of the algorithm test show that the concession multiplier ratio and carbon quota are the key factors affecting the equilibrium of the gas-electricity coupled market and the market revenue of RE in the power transfer transaction.In decoupling transactions,carbon quotas and subsidy policies for RE affect gas and electricity supply and demand and ancillary service markets.In the long term,decoupled trading is more conducive to the market equilibrium and market revenue of RE.2.A day-ahead intra-day trading mechanism containing heating and cold power energy sharing under the gas-electricity market is proposed.To address the problem of deviations in spot market transactions in distributed integrated energy parks caused by the volatility of renewable energy output,this paper designs a model of CCHP energy sharing managed by a market organizer integrated energy service provider,and adopts incentive compatibility theory to allocate the cooperative surplus,and gives each user a corresponding market surplus incentive based on its energy sharing value to improve the motivation of market participation.At the same time,adaptive robust optimization is used to cope with the stochasticity of distributed renewable energy,and an algorithm based on key scenario identification is used to solve the problem,which effectively improves the efficiency of market clearing.The algorithm test results show that the designed trading mechanism can effectively promote energy sharing,with improvements in both social welfare and computational speed.3.A real-time trading mechanism considering robustness under the gas-electricity market is proposed.To address the problem of the amount of market trading deviations caused by fluctuations in renewable energy output and load demand in the real-time market,this paper designs a robust distributed trading mechanism based on IGDT for gas-electric coupled networks.The Lagrangian decomposition method based on the original pairwise gradient decentralizes the objective function iteratively to achieve market clearing,and the mechanism updates the decisions of tradable energy users through the transmission of price information,which ensures the privacy and security of users.Meanwhile,the IGDT method is used to construct a robust optimization model for the P2 P multi-energy trading market considering multiple uncertainties,and the NBI method is used to transform the multi-objective optimization model to ensure the global optimality of the market.The algorithm test results show that the designed trading mechanism guarantees the robustness of the market trading results despite the influence of randomness factors.4.The optimal offer strategy for heat and power users with multiple time scales is proposed.The paper designs a trading strategy model based on prospect theory and adaptive quotation,which takes into account the differences in characteristics,subjectivity and risk preferences of producers and consumers,and makes the optimal quotation decision based on objective market information,historical transaction prices and forecast prices,in order to address the bias in trading decisions caused by different energy use characteristics and subjective preferences of distributed multi-energy users participating in market transactions.It also proposes a transaction matching and settlement mechanism based on Ethernet smart contracts under the framework of blockchain to realize decentralized and efficient transactions in the distributed electric energy market.The algorithm test results show that the designed trading mechanism can be effectively implemented on the blockchain platform and has some improvement over the traditional trading strategy in terms of social welfare and market efficiency.