Model construction of coordinated operation mechanism of energy supply chain based on operations research big data algorithm

During rapid modernization, the policy of technological upgrading of the coordinated operation of the energy supply chain has been tested over many years of practice, with limited potential for future development, and further emission reductions are facing greater technological and cost pressures. Market trading policies mainly include the carbon emissions trading mechanism and the guaranteed mechanism for renewable energy power consumption, and the above policies will be formally implemented in 2020, which will be the main direction of development in the future. After introducing the low-carbon policies, this paper will focus on the coal-power energy supply chain considering the carbon credit quota and renewable electricity consumption limitations and analyze the impacts of the relevant parameters on the coal-power energy supply chain returns under the above policies in both non-cooperative and cooperative game scenarios. Finally, a preferential price-based green power certificate trading mechanism is constructed to propose a cost-reducing trading proposal for power users to purchase green power certificates to fulfill the amount of renewable energy power consumption.


Introduction
In terms of low-carbon policies, they are mainly categorized into technology upgrading policies and market trading policies.Therefore, technology upgrading policies have limited future potential for energy efficiency and emission reduction [1].The market trading policy is mainly to reduce carbon emissions by establishing a market trading mechanism.On the one hand, total carbon emission control is carried out, and the carbon emissions trading mechanism will be implemented nationwide in the thermal power industry starting in 2020 [2].On the other hand, clean energy replaces fossil energy, mainly for the green power certificate trading mechanism, which is divided into two kinds of transactions.The first is a voluntary trading mechanism.Individuals and enterprises voluntarily purchased the implementation of renewable energy green power certificate issuance and voluntary subscription trading system in 2017; the second is a mandatory trading mechanism, the implementation of 2020 renewable cattle.Energy power consumption guarantee mechanism: From a practical point of view, the voluntary trading mechanism under the green power certificate trading volume is very small, and the future mainly hopes on the mandatory trading mechanism [3].

Modeling the coal power energy supply chain under low-carbon policies
We study a coal power energy supply chain consisting of coal producers, coal-fired power producers, and power users.The government requires coal-fired power producers to fulfill a certain amount of carbon trading right quotas every year and power users to fulfill a certain amount of renewable energy power consumption every year [4].The energy supply chain for coal power under the low-carbon policy is shown in Figure 1.Coal-fired power generation enterprises can reduce carbon emissions by reforming emission reduction technologies or buying or selling the shortfall or excess through the carbon emissions trading market [5,6].

Green power certificate trading model considering preferential pricing
In a green power certificate trading market, it is assumed that all firms are rational persons and that the market maximum restriction price and the minimum economic selling price are public information known to all green power certificate holders [7].In the above scenario, the trading rules of the green power certificate trading model considering preferential prices are as follows: (1) Publication of the procurement notice by the purchaser The purchase notices contain information on purchase quantities, purchase prices, and optimized prices.There are n qualified suppliers in the market, of which m expect to sell at a low price to recoup their capital quickly.Still, above the minimum economic selling price in the market, the preferential price set in this section is higher than the minimum economic selling price and is lower than the maximum restricted price.The discount percentage is: To introduce competition, the number of vendors bidding for sale per vendor is: (2) Trade aggregation and settlement Using the Monte Carlo stochastic simulation of the green power certificate trading process, based on the probability theory, the transaction price model of green power certificate is:

Calculus analysis
For example, a large-scale power consumption enterprise in the West Mongolia Power Grid intends to purchase green power certificates from the newly built renewable power enterprises in 2016 in the region Calculations show that the maximum market price and the minimum market economic selling price for wind power green power certificates are  = 176.3/unitand  = 151.1/unit,respectively.The maximum market price and the minimum market economic sale price for PV green power certificates are  = 506.3per unit and  = 422.2per unit, respectively.Through comparison, it can be concluded that the price of wind power green power certificates is lower than that of PV green power certificates.Therefore, the enterprise should prioritize the purchase of wind power green power certificates.From the formula, the number of green power certificates that the business needs to purchase is  = 8000.
The procuring enterprise establishes a preferential price based on the lowest economic selling price, slightly higher than the market M low-economic price.Based on the above, the electricity consumer publishes a procurement notice, as shown in Table 2.In the transaction, assuming that 16 wind power companies meet the requirements of the subscription announcement, 8 of them are willing to sell at a discounted price to recoup capital, and the rest expect to sell at a high price.The possible transaction combinations are shown in Table 3. From probability theory, the theoretical transaction price of green power certificates for wind power is $154.4 per certificate.
In Monte Carlo simulation using Matlab, the number of simulations is increased from 1000 to 10000, and the change in transaction price is shown in Figure 2. As shown in Figure 2, the simulated transaction price under different simulation times fluctuates up and down around the theoretical transaction price and is very close to the theoretical transaction price, which shows that the transaction price has good stability.

Specific model analysis
Maximizing material savings and improving material utilization is an important means of increasing production efficiency [8].
Undercutting issues: A certain type of steel plate is to be utilized to undercut blanks of m parts.Based on the principle of saving material and easy handling, n different ways of undercutting have been devised.We let there be  parts of the ith type in the jth way of discharging, and it is known that the quantity required for the ith type of part is  .We try to develop an integer planning model to determine which undercutting scheme to use that will satisfy the need while trying to minimize the number of steel plates used.
denote the number of parts consumed by the  and way of discharging  = 1, 2, … , ,  ∈  , then the problem reduces to the following integer programming problem:

Green power certificate pricing model
Green power certificates are categorized into wind power, green power certificates, and photovoltaic green power certificates, and different types of green power certificates are priced differently in the green power certificate trading market, and the symbols are defined as shown in Table 4.The maximum restricted price in the market, as stipulated in the Green Power Certificates Limit Prices, is: Based on the cash value of money model, the market minimum economic sales price for green power certificates is: The relationship between the amount of renewable electricity consumed and the number of green power certificates is:

Green power certificate trading model considering preferential pricing
In the above scenario, the trading rules of the green power certificate trading model considering preferential prices are as follows [9]: (1) Publication of the procurement notice by the purchaser There are n qualified suppliers in the market, of which m expects to sell at a low price to recoup their capital quickly, but higher than the minimum economic selling price in the market, and the optimized price set in this section is higher than the minimum economic selling price and lower than the maximum restricted price [10].The discount percentage is: To introduce competition, the number of vendors bidding for sale per vendor is:

Conclusion
First, this paper introduces the low-carbon policy, analyzes the technology upgrade and market trading policies, and lays a theoretical foundation for researching the coordinated operation mechanism of the coal-power energy supply chain under the low-carbon policy.Then, a coal power energy supply chain model is constructed considering carbon emission quota and renewable energy power consumption child limitations.The changes in profits, prices, and sales volume of coal power energy supply chain enterprises in the non-cooperative and cooperative game scenarios are analyzed.It is concluded that the total profits of the coal power energy supply chain in the cooperative game scenario are larger than those in the non-cooperative scenario.The prices of the final products in the cooperative scenario are lower than those in the non-cooperative scenario.Finally, the reasonable price range of green power certificates is derived, and a green power certificate trading model considering preferential prices is established to save costs for power users.The analysis shows that the model can effectively alleviate the current renewable energy subsidy gap in China.It also positively affects the completion of the quota system for the consumption of renewable energy power.

Figure 1 .
Figure 1.Coal Power Energy Supply Chain under Low Carbon Policy.

Figure 2 .
Figure 2. Impact of the number of simulations on the transaction price of wind power green power certificates.

Table 1 .
to fulfill the 8 million kWh of renewable energy power consumption.The parameter settings are shown in Table1.Parameter Settings.