Study on Risk Evasion in Electricity Market (II) - Realization of CFD Analysis System
With the introduction of power policies for fund-raising offices in China in the 1980s, the property rights of the power plants were diversified and formed the current situation of “multiple prices for a single plantâ€. In this case, the full meaning of the same network, homogenous, and the same "Price" will cause a large-scale shift in the unreasonable interest between new and old power plants. Newly-built generating units cannot pay back their principal and interest. In order to introduce a competition mechanism in the power generation market, we must take into account the actual situation of the new and old generating units. The “authorized CFD + single buyer†model developed by Australia’s PPI/TG (Pacific Power International/Transgrid) consulting group is a type of medium- and long-term contract that the two parties sign in order to avoid the risk of spot trading. In the contract, both parties agree on a contract electricity price. When the spot market electricity price is lower than the contract price, the purchase party should still pay the difference electricity fee less than the contract price to the seller. If the spot market price is higher than the contract price, the seller The party should return more than the contract tariff to the purchase party so that the market price risk can be avoided. Usually the power involved in CFDs is only a part of both parties. Both parties want to retain some of the traded power into the spot market in order to obtain more market opportunities. Among them, CFDs are authorized, and the contract price and the electricity charge are the contracts that the authorizing department is responsible for formulating. The purchaser refers to the only power purchaser that Zhejiang Electric Power Co., Ltd. purchases for the power generation of each power generation company. Combining the specific characteristics of the power generation market in Zhejiang Province, the paper introduces the CFD system based on the deterministic contract power factor decomposition algorithm developed by the author. 1 The specific characteristics of the power generation market in Zhejiang Province The power generation market in Zhejiang Province has just started, and it has its own characteristics. And requirements: a contract power decomposition to consider all plans to repair Zhejiang power grid power generation market is using the "authorized CFD + single buyer" bidding model, power generation companies are prohibited from buying contracts from other power generators, and in such a In the electricity market that has just emerged from the shadow of power shortages, other power generators sometimes have no ability to sell electricity. Therefore, the demolition of the contract power only considers major repairs. For both parties, the risk is very high, and it is not suitable for the power generation market of Zhejiang Province's power grid. The contracted power supply decomposition must consider all planned maintenance. b Monthly rolling correction of contracted electricity. In Australia, it is entirely up to the generators to determine whether or not the turbines are to be overhauled. In the power generation market of Zhejiang Province, the planned power overhaul is coordinated by the Zhejiang Electric Power Company according to the application of the power generators. Therefore, the annual contract power curve should be changed along with the monthly plan. Adjustment. c. Annual adjustments of electricity generation contractor's total electricity consumption Due to the impact of the macroeconomic environment, the electricity market in Zhejiang Province fluctuates significantly. Therefore, it is necessary to determine contract electricity consumption at the appropriate time in the fourth quarter of the contract year when the actual electricity consumption level is at the beginning of the year. When the level of electricity consumption varies greatly, the two parties negotiate with each other to adjust the total amount of contractual electricity for the contract year d. Minimum technical considerations In Australia, the peak-to-peak depth of the unit can generally reach about 70%, 660 MW units. The minimum technical output is about 200 MW, and the peak-to-peak depth of competitive bidding units for Zhejiang power grids is generally around 50%, and some units are even only 20%. Therefore, the minimum power required for the entire plant portfolio must be taken into account when deciding the contract power. e ticks off the impact of bidding power. In the power grid of Zhejiang Province, the power generation market is in trial operation. The power market involves only some of the power plants. The power load to participate in the bidding only accounts for about 60% of the call load of the entire province, and a considerable part of non-bidding power, such as in the electricity market. Finally, the power generation load curve of the real bidding unit is formed. Formula deterministic contracts, (thermal) electric machines and commissioning units, etc., this part of the non-competitive power supply has a greater impact on the electricity market. Therefore, the impact of non-competitive power sources must be deducted when the contract power is decomposed. 2 The design idea is combined with the above-mentioned Zhejiang grid power generation. The specific characteristics of the market, according to the basic principles of CFDs1, when conducting CFD analysis, firstly, the load curve of the unit representing the daily bidding unit is generated by the load curve module and the annual contract power module, and the bidding power plant is determined. The annual contract power, and then use the deterministic contractual power decomposition algorithm to decompose the contract power, and generate a contract curve for 48 periods per day for each auction power plant contract month, which has considered the plan inspection and then proceed to the curve. The verification of the minimum technical output of the entire plant portfolio, if passed, can be issued every 05h of the monthly contract power, or else the annual contract power should be re-adjusted before decomposing the contract power. At the same time, it is necessary to analyze the contract power in a timely manner. The purpose is to effectively track and analyze the operation and trading of the electricity market, so as to provide decision-making basis for the next contract development. 3 Functions The CFD analysis system adopts object-oriented technology. Therefore, it has good flexibility and extensibility. Its overall functional framework is shown as follows. The functional framework of the CFD analysis system is shown below. = is the system load curve matrix of the modified contract period representative day; a is the actual situation of the load based on the predicted contract date, the operation status of the integrated power market history, and the correction of points on the typical load curve of the current contract release representative day The matrix is ​​nhXnL dimension, its parameters are adjusted by human; Lw is the representative load curve of the initial representative day, the data of which are mainly taken from historical data, and then analyzed by similarity fitting method. The matrix is ​​nhXnL dimension. ; C is a matrix that matches the typical daily load according to the type shown in each trading day during the period of the contract, and is generated by the corresponding typical daily load curve of the representative day. The matrix is ​​nLXnd dimension; Lnc is the non-bid unit curve. Generated by historical and empirical data, the matrix is ​​nhXnd dimension; nh is the number of auction periods per day, for example, Zhejiang Electric Power Company uses every 05h as a bidding period, then nh = typical load curve number; nd is the number of days for formulating the contract trading day . According to the annual contract power model of the 32nd year, based on the annual demand forecast and the balance of electricity generation, the unified call power is used to calculate the total power consumption of the East China Power Grid and the non-competitive power unit. “Homogeneous, same priceâ€, the same unit has a principle of considerable utilization of hours, taking into account the average equipment capacity of the bidding unit, the proportion of the contracted electricity of the bidding unit, the unit's electricity consumption rate of the plant, and the loss of the transformer, etc., and obtaining the unit’s annual contract power, thus determining the whole plant The annual contract power. As the planned maintenance is affected by various subjective factors, the actual implementation of the annual maintenance plan is poor, and it is necessary to use the monthly amount as the unit. According to the monthly demand forecast and the balance of electricity generation and consumption, and the monthly maintenance plan, the annual contract is guaranteed. With the proportion of the total amount and the determined contracted electricity, if the monthly contracted electricity is arranged to deviate from the determined proportion of the total contracted electricity of the participating bidding units on the premise of actual implementation, then the contracted electricity of each generation company will be adjusted from the next month to the network constraints and The reason for the provincial adjustment causes the provincial unit schedule repair time to be inconsistent with the monthly schedule and the monthly maintenance schedule (PASA) announced maintenance time. The monthly contract curve can be revised in the late October of the contract year, through prediction, If it is found that the amount of contractual power for the contract proportion determined in the actual maintenance contract is greater than the annual contractual power, the total amount of contractual annual contract power can be adjusted through negotiations between the two parties. The definitive contract power decomposition algorithm method is The basic idea of ​​the system's core ki is based on the annual contract power The model, according to a certain ratio, carries out the apportionment of the contract power on the modified load curve of the bidding unit, and considers the planned maintenance, and finally generates a contract curve of 48 times per day during the contract period of each bidding power plant. The algorithm is expressed as follows: Seat inspection period The maintenance floor is satisfied: a. Maintenance plan. According to the maintenance plan announced by PASA, the contractual electricity quantity is not evenly allocated during the planned maintenance period, and the contractual electricity volume deducted during the inspection period is revised accordingly in order to guarantee the annual contract. The total amount of electricity remains unchanged b The minimum technical output requirement of the power plant is n, 1=12...,nh; N is the total number of bidding units of a bidding power company; M is the total number of bidding power companies; Qq. is a bidding power company; The contract power column vector on the trading day; Q'Cj is the contract power of the bidding power company j in the first period of t trading day; QL is the typical load curve column vector of the t trading day; AQOh is the trading day caused by the inspection The additional amount; Z is the contract share of the bidding unit i; W is the proportional factor of the bidding power company j difference contract; Q,-, Qjmax is the lower limit and upper limit of the power generation company j's unit technology. In equation (2), the setting of main parameters Z and W is related to the quality of the contracted electricity quantity Z. By forecasting the electricity consumption for the contract year, the annual equipment utilization hours of the bidding unit are determined, and the capacity of the unit and the power consumption of the integrated plant are taken into account. Factors such as quantity and damage are obtained; W is determined on the premise of balancing the risk aversion ability and system capacity demand of each generation company, and varies according to the different periods of operation of the electricity market. 34 Early-warning modules of the lowest technology output of the whole plant As the low-load period of the contract year, such as the Spring Festival or the large-scale hydropower generation period, the power output of the unit contract power conversion is lower than the minimum technical output of the unit, and even the output of the whole plant contract power is converted. Lower than the minimum technical output of a single unit, this requires an early warning of the minimum technical output of the entire plant combination. Revise the contract curve that does not meet the requirements, so as to achieve the lowest technical output of the whole plant combination, to meet the power output of the quotations that require 5 hours of contract electricity, U is the plant-wide integrated plant electricity rate, which is assumed to be the lowest unit Technical contribution, C is the nameplate capacity of the unit. For the sake of convenience of study, n units all refer to the same type of unit, then: a For the unit whose peak shaving depth is greater than 5 (% of the unit, the contract power per bidding period is only required to satisfy C. b For the unit whose peaking depth is less than 50% It is more complicated and discussed in the following circumstances: One unit is available in the ith auction period, and must satisfy the following conditions: Two units are available in the ith auction period, and must satisfy: The first three units are available during the first auction period, and must meet: i Auction period n units available, need to meet: 35 contract electricity comprehensive analysis module This module includes: interface with real-time online quotation system, and can download real-time market information at any time according to user needs; carry out market settlement and analysis; provide basic parameters of the electricity market The most basic function of making a comprehensive analysis of contracted electricity and contract revenue is to carry out the settlement of the market and power generation companies according to formula (3), because this is the basis for other analysis ( 3) It consists of two parts, one is market income and the other is contract revenue. Wj is the total income of the power company j during the contract period. p is the market settlement price column for the trading day t; pJ is the price of the difference contract price for the power company j. The price is negotiated by the contracting parties and reported to the price department for approval. The price adjustment is performed by the government price department; Q; j is the power grid company's online power column vector on the trading day t; V is the net loss factor of the power generation company j generator network point to the center point is settled using the CFD bidding model, the market will not guarantee how much the power plant's on-grid electricity, the Internet The amount of electricity depends on the market competitiveness of the power generation company.The market will use the settlement model to reflect the ability of the CFD model to avoid risks based on the amount of electricity on the grid.4 Application effect As a subsystem of the power market technical support system, the CFD analysis system has been applied. The annual monthly contract power in Zhejiang power generation market and the contractual power curve for 48 time periods per day were arranged and displayed the actual data of Zhejiang power generation market in the month of 2000. It can be seen that the proportion of contracts established using the system is stable at 85 on average. About %, basically in line with the expected control of risk. Due to the abnormal weather and low system load, the spot market transactions in this month showed that the market had the highest settlement price in 200 trading hours, and there was a period of excess output in 4 trading hours, namely, a negative price, and the lowest market price had reached -101 RMB/(MW.h) in the market electricity price is the market average price per day for 48 trading hours, but it can still be seen that the spot market is volatile and the average settlement price is relatively stable. Electricity market electricity price trend curve for one month Fig2EnergycurvesforZhejiangprovince Zhejiang electricity generation market electricity price trend curve for one month Fig3 PricecurvesforZhejiangprovince 5 Conclusion After adopting the CFD system based on the deterministic contract power decomposition algorithm to settle, the market demand-oriented, moderately introduced competition generator system has been achieved. The initial goal of the power generation market, taking into account the interests of all parties, effectively suppressed the low electricity prices and high electricity prices in the power generation market, and largely avoided the large-scale volatility in the price of electricity to bring the market risks to the buyers and sellers and ensured Zhejiang’s market risk. Grid power generation market is developing steadily and steadily The composition of adjustable street light:
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