Generation quotation system design and application
I. Introduction
With the separation of factories and networks and the deepening development of provincial power generation market towards regional power generation market, how to participate in competition in a fair, just and open manner to ensure the safe and stable operation of the generating units, optimize the allocation of resources, provide reasonable quotations, and improve the economic efficiency of power generation companies, especially Under the premise of the power market trading rules, how to adjust the quotation and power generation output in a timely and reasonable manner according to changes in the power market, carry out effective competition, and make full use of the opportunities provided by the electricity market mechanism to improve the economic efficiency of enterprises, has been imminent In front of the power generation company.
Power generators can increase profits by reducing costs, or increase profits through the analysis of bid strategies. There are two ways to choose the best bid strategy: first, to estimate the bidding behavior of other bidding power producers; second, to forecast the market in the next period. Marginal liquidation price. The literature [4,5] makes a more detailed analysis of the bidding strategies of power generation companies. It is estimated that the bidding behavior of other bidding power generators is mainly to grasp the historical quote data and cost data of competitors, as well as the unit operating conditions and planned maintenance. Quoting through probability analysis and simulating the behavior of opponents can actually affect the marginal market price. As for the system marginal clearing electricity price forecast, it is mainly based on the system load forecast obtained from the dispatching trading center, the historical marginal electricity price, the system non-competitive output plan, the bid unit plan maintenance situation, the network control and network line maintenance, the system auxiliary service, and the The historical quotation of the bidding power plant and the factory, as well as the contract electricity situation, etc., to predict the change of the marginal clearing electricity price at the end of the period. Literature [6] applied neural network BP model algorithm to predict the electricity price of Zhejiang power market, and literature [7] achieved better results by using neural network BP model algorithm for load forecasting. Therefore, in the power market competition, power generation companies must, on the one hand, improve the safety and reliability of the generating units, improve the economic performance of the units and the adjustability of the units, strengthen the supervision of the plates, improve the operation and operation level, and organize research projects to improve The adaptability of the unit to the electricity market; on the other hand, it is necessary to raise the forecasting level of market demand, use the public information provided by the power exchange technical support system, use scientific bidding strategies, and apply computer technology to develop an auxiliary pricing decision system. This paper uses the computer simulation system load balance to forecast the marginal clearing price of electricity at the end of the market, so that we can know and know each other's quotation to obtain the maximum economic benefit.
The basic requirements for the system design of flight quotation are to reduce the work intensity and difficulty of manual quotation analysis, so that we can know what we know and what we offer, we can better conduct pre-quote analysis and post-quote evaluation. The quotation system should be able to meet the following basic requirements:
1) It can automate the collection of electricity market information, and through the analysis of the quotation of the previous day's bidding plants, and combining the marginal market price with the ability to calculate the performance of each bidding plant automatically.
2) The remote computer can automatically read the on-grid power, perform settlement check on the power generation status of the previous Japanese power generation company, provide reference for the modification of the current day's quote and quote on the next day, and conduct quantitative analysis based on the existing cost information.
3) Based on the system load curve, historical quotation of each plant, and the output of the system, we propose a proposal for a better unit portfolio. The simulation forecast method is used to consider the market marginal price trend analysis when one of the factors (such as load, output, and quotation) changes and the other factors remain unchanged.
4) Ability to calculate auxiliary service fee, auxiliary service compensation fee and output deviation calculation, and preset output deviation alarm to reduce output deviation assessment service.
Second, the functional module of the quotation system
According to the above design requirements, the quotation system is mainly composed of functional modules such as data collection and storage, market settlement, market analysis, quotation decision and system management.
2.1 Data Acquisition and Storage Module
The data acquisition and storage module collects and analyzes the company's internal real-time data and power soup real-time data, so that all types of personnel of the company can timely and accurately grasp the operation of the power grid and analyze the supply and demand of the power market. This type of information includes cost information obtained from the Management Information System (MIS), power generation status and on-grid electricity status from the Dispatch Automation System/Distributed Control System (DAS/DCS) and ERTU power collection terminals, and the electricity market technology from Zhejiang Power Grid. Support system to obtain the system load, market price, calendar quote information.
2.2 Market Settlement Module
2.2.1 Income and Income Statement
According to the system, the ERTU power collection software collects the gateway gateway power with time and the market clearing price downloaded by the market, calculates the power generation revenue according to the settlement formula of the CFD contract, and generates income, monthly, and daily income and income statements.
2.2 Checking of ancillary services and their compensation settlement
According to the system's auxiliary operation hours and input auxiliary service capacity of the company's collection and market downloading, the auxiliary service fee and auxiliary service compensation are checked according to the auxiliary service fee and auxiliary service compensation formula, and the annual, Monthly school statistics.
2.3 Output Deviation Award Corrections and Output Deviation Alarms
According to the output power of each unit l0min collected by this system, the l0min output situation and deviation awards and punishments downloaded on the power market will be evaluated and rewarded for each l0min of each unit and the output of each time period (output integral value). Generate annual and daily school nuclear statistics. In addition, the output deviation alarm is issued to remind the personnel to adjust the output.
Third, the market analysis module
The market analysis module includes the start and stop status of bidding units and non-competing units, margin conditions of bidding units, historical performance and load ratios of bidding and non-bid plants, analysis of historical bid prices of various bidding plants, and analysis of historical business operations of e-commerce providers. Market unit maintenance and so on.
The historical operation status and load rate of each bidding plant and the business operations of each generation company’s calendar are based on the various bidding power generation and historical quotation conditions downloaded from the electricity market, as well as the market’s actual load and clearing price, constrains, unit operation and maintenance. Computer analysis and calculation.
3.4 Quote Decision Module
3.4.1 Pre-scheduling plan market price analysis and evaluation
According to the comprehensive information on the next day's system load forecast obtained from the electricity market, the market price of dispatch, the history of this power producer and other power producers, and the company’s power generation cost, according to the transaction rules of the Zhejiang Power Market, using a simulation system A change in one factor predicts the change in the marginal price of electricity the next day. According to the company's forecast, the analysis results predicted by the pre-scheduled plan, and the grid load forecasting demand, the company's on-grid power generation and forecasted power generation revenues will be calculated on the next day, which will provide market personnel with an auxiliary reference for the next day's quotation.
2.4.2 Real-time scheduling plan forecast analysis and assessment
According to the comprehensive information of the system's ultra-short-term load forecast and system actual load, clearing price, historical price quoted by the company and other power generators obtained from the electricity market, according to the trading rules of the Zhejiang power market, the use of a certain factor in the simulation system changes The computer predicts changes in the clearing tariff of the grid during the last period.
Based on the forecast price of the system and the analysis results of the real-time dispatch plan forecast, the company calculates the grid-connected electricity at the end of the period and predicts the power generation revenue. Based on the results of the real-time dispatch plan analysis, the market personnel provide assisted decision-making information for making adjustments to the quotes during the last trading session.
2.5 System Management Module
This system is an integrated system. It will involve multiple departments and different personnel of the company and subordinate factories in the running process. Therefore, the system management module provides different functions for different types of personnel to set different permissions.
Third, the structure of the quotation system
In view of the geographical distribution of the company's headquarters and its two power plants, the quotation system makes full use of the existing network and terminal facilities, taking full account of the company's existing computer network facilities, using TCP/IP network technology. ,Southeast company accesses the quotation system through LAN. The company's headquarters and its two power plants transmit data through the provincial power system data network permanent virtual circuit (PVC); the outside uses dial-up access through the Internet, the quotation system and Zhejiang Province’s power generation Market technical support systems communicate and access information through the power system data network.
The quotation system adopts a multi-layer client/server architecture. The client program connects to the database through the BDE (Borland database engine) database interface, and obtains the data required by the foreground application program from the web server and the system application server. The system background application program and data acquisition program acquire various data required by the system from various real-time, non-real-time systems (such as MIS, DAS/DCS, power generation market technical support systems, and ERTU power collection terminals) of the power generators. Information, and connection to a relational database through the BDE data interface. The system hardware structure is shown in Figure 1.
The company's database server and application server are used to store various data and information required by the quotation system, and centralize the business logic and data processing logic of the company's part of the entire software system. At the same time, it is responsible for taking from the database application servers of the two power plants. The company headquarters performs the data needed to assist the decision.
The database and application server of Xiaoshan Power Plant and Taizhou Power Plant are used to save all kinds of data and information required by auxiliary decision systems of Xiaoshan Power Plant and Taizhou Power Plant, and provide the business logic processing functions and data processing functions of the two power plants, respectively. Xiaoshan Power Plant, Taizhou The power plant's data acquisition server collects data from various real-time and non-real-time systems.
The workstation (client) is the interface between the system and the user. Various users use the workstation and the system to perform various interactive operations to complete the quotation and information query and decision-making.
The network operating system selected by the system is a Windows 2000 server. SQL server was chosen as the database running and development platform of this system. Using a common and efficient software development tool Delphi5 for software development.
Fourth, the actual operation of the quotation system
The quotation system has been developed and perfected for more than one year and has been installed at the company headquarters and subordinate power plants. In actual operation, the system can help the quoting staff to conduct market analysis, settlement check and quantitative profit analysis, and it plays a good role in analyzing the market conditions of other bidding power generators. It can be able to know and know the bid and reduce the blindness of the quotation; reduce the quotation Personnel's calculation and analysis of labor intensity, and the operation personnel to reduce the output of the deviation assessment and the value of the long-term quotation section of the adjustment of the quoted section capacity has a great guiding role for the company in the electricity market competition has achieved better economic benefits , And for the future for the company's headquarters and a number of power plants far away from the quotation-assisted decision-making system connectivity, resource sharing and scientific quotations, has played a successful demonstration role.
However, this quotation system still needs to be further improved in market marginal price forecasting and quotation-assisted decision analysis. This is mainly due to the fact that there are many factors that affect the market marginal clearing electricity price, and there are many uncertain factors, such as load changes, output changes, and network constraints. It is difficult to establish a more practical mathematical model to conduct intelligent quotation and market price trend analysis, which is also the difficulty of the quotation system. This quotation system adopts the simulation forecasting method and uses the computer simulation system load balance to predict the marginal clearing electricity price at the end of the market, and can only be used as a reference in the quotation assistance decision.
V. Conclusion
Implementing separate factories and networks, bidding for access to the Internet, and establishing a standardized and orderly power coin market can play a fundamental role in market allocation and optimization of resources, thereby realizing the power industry's goal of sustainable development.
In order to be invincible in the power generation market competition, power generation companies must strengthen management and adopt cost leadership strategies. They must actively research quotation skills and conduct design and application of quotation systems. In order to make quote analysis more practical and faster, computer technology must be used to analyze and forecast the marginal market price trend and the behavior of competitors. This system has met the requirements of the "Zhejiang Power Grid Market Regulations" and the use of publicly available information in the electricity market, combined with the cost of generating units for generating units, and based on relevant historical data and data, analyzed the trend of the electricity market and forecasted the market marginal electricity price requirements for the end of the period. Therefore, the work intensity and difficulty of the manual quotation analysis are reduced, and the quotation is known. However, as the provincial power generation market expands into the regional power generation market and the market scope is wider, it is even more important to combine the regional power market research quotation strategy and the use of computer technology for quotation system design and application. It is the power generation companies that grasp the market opportunities and win the battle. The magic of the electricity market remains to be further studied in the future.
With the separation of factories and networks and the deepening development of provincial power generation market towards regional power generation market, how to participate in competition in a fair, just and open manner to ensure the safe and stable operation of the generating units, optimize the allocation of resources, provide reasonable quotations, and improve the economic efficiency of power generation companies, especially Under the premise of the power market trading rules, how to adjust the quotation and power generation output in a timely and reasonable manner according to changes in the power market, carry out effective competition, and make full use of the opportunities provided by the electricity market mechanism to improve the economic efficiency of enterprises, has been imminent In front of the power generation company.
Power generators can increase profits by reducing costs, or increase profits through the analysis of bid strategies. There are two ways to choose the best bid strategy: first, to estimate the bidding behavior of other bidding power producers; second, to forecast the market in the next period. Marginal liquidation price. The literature [4,5] makes a more detailed analysis of the bidding strategies of power generation companies. It is estimated that the bidding behavior of other bidding power generators is mainly to grasp the historical quote data and cost data of competitors, as well as the unit operating conditions and planned maintenance. Quoting through probability analysis and simulating the behavior of opponents can actually affect the marginal market price. As for the system marginal clearing electricity price forecast, it is mainly based on the system load forecast obtained from the dispatching trading center, the historical marginal electricity price, the system non-competitive output plan, the bid unit plan maintenance situation, the network control and network line maintenance, the system auxiliary service, and the The historical quotation of the bidding power plant and the factory, as well as the contract electricity situation, etc., to predict the change of the marginal clearing electricity price at the end of the period. Literature [6] applied neural network BP model algorithm to predict the electricity price of Zhejiang power market, and literature [7] achieved better results by using neural network BP model algorithm for load forecasting. Therefore, in the power market competition, power generation companies must, on the one hand, improve the safety and reliability of the generating units, improve the economic performance of the units and the adjustability of the units, strengthen the supervision of the plates, improve the operation and operation level, and organize research projects to improve The adaptability of the unit to the electricity market; on the other hand, it is necessary to raise the forecasting level of market demand, use the public information provided by the power exchange technical support system, use scientific bidding strategies, and apply computer technology to develop an auxiliary pricing decision system. This paper uses the computer simulation system load balance to forecast the marginal clearing price of electricity at the end of the market, so that we can know and know each other's quotation to obtain the maximum economic benefit.
The basic requirements for the system design of flight quotation are to reduce the work intensity and difficulty of manual quotation analysis, so that we can know what we know and what we offer, we can better conduct pre-quote analysis and post-quote evaluation. The quotation system should be able to meet the following basic requirements:
1) It can automate the collection of electricity market information, and through the analysis of the quotation of the previous day's bidding plants, and combining the marginal market price with the ability to calculate the performance of each bidding plant automatically.
2) The remote computer can automatically read the on-grid power, perform settlement check on the power generation status of the previous Japanese power generation company, provide reference for the modification of the current day's quote and quote on the next day, and conduct quantitative analysis based on the existing cost information.
3) Based on the system load curve, historical quotation of each plant, and the output of the system, we propose a proposal for a better unit portfolio. The simulation forecast method is used to consider the market marginal price trend analysis when one of the factors (such as load, output, and quotation) changes and the other factors remain unchanged.
4) Ability to calculate auxiliary service fee, auxiliary service compensation fee and output deviation calculation, and preset output deviation alarm to reduce output deviation assessment service.
Second, the functional module of the quotation system
According to the above design requirements, the quotation system is mainly composed of functional modules such as data collection and storage, market settlement, market analysis, quotation decision and system management.
2.1 Data Acquisition and Storage Module
The data acquisition and storage module collects and analyzes the company's internal real-time data and power soup real-time data, so that all types of personnel of the company can timely and accurately grasp the operation of the power grid and analyze the supply and demand of the power market. This type of information includes cost information obtained from the Management Information System (MIS), power generation status and on-grid electricity status from the Dispatch Automation System/Distributed Control System (DAS/DCS) and ERTU power collection terminals, and the electricity market technology from Zhejiang Power Grid. Support system to obtain the system load, market price, calendar quote information.
2.2 Market Settlement Module
2.2.1 Income and Income Statement
According to the system, the ERTU power collection software collects the gateway gateway power with time and the market clearing price downloaded by the market, calculates the power generation revenue according to the settlement formula of the CFD contract, and generates income, monthly, and daily income and income statements.
2.2 Checking of ancillary services and their compensation settlement
According to the system's auxiliary operation hours and input auxiliary service capacity of the company's collection and market downloading, the auxiliary service fee and auxiliary service compensation are checked according to the auxiliary service fee and auxiliary service compensation formula, and the annual, Monthly school statistics.
2.3 Output Deviation Award Corrections and Output Deviation Alarms
According to the output power of each unit l0min collected by this system, the l0min output situation and deviation awards and punishments downloaded on the power market will be evaluated and rewarded for each l0min of each unit and the output of each time period (output integral value). Generate annual and daily school nuclear statistics. In addition, the output deviation alarm is issued to remind the personnel to adjust the output.
Third, the market analysis module
The market analysis module includes the start and stop status of bidding units and non-competing units, margin conditions of bidding units, historical performance and load ratios of bidding and non-bid plants, analysis of historical bid prices of various bidding plants, and analysis of historical business operations of e-commerce providers. Market unit maintenance and so on.
The historical operation status and load rate of each bidding plant and the business operations of each generation company’s calendar are based on the various bidding power generation and historical quotation conditions downloaded from the electricity market, as well as the market’s actual load and clearing price, constrains, unit operation and maintenance. Computer analysis and calculation.
3.4 Quote Decision Module
3.4.1 Pre-scheduling plan market price analysis and evaluation
According to the comprehensive information on the next day's system load forecast obtained from the electricity market, the market price of dispatch, the history of this power producer and other power producers, and the company’s power generation cost, according to the transaction rules of the Zhejiang Power Market, using a simulation system A change in one factor predicts the change in the marginal price of electricity the next day. According to the company's forecast, the analysis results predicted by the pre-scheduled plan, and the grid load forecasting demand, the company's on-grid power generation and forecasted power generation revenues will be calculated on the next day, which will provide market personnel with an auxiliary reference for the next day's quotation.
2.4.2 Real-time scheduling plan forecast analysis and assessment
According to the comprehensive information of the system's ultra-short-term load forecast and system actual load, clearing price, historical price quoted by the company and other power generators obtained from the electricity market, according to the trading rules of the Zhejiang power market, the use of a certain factor in the simulation system changes The computer predicts changes in the clearing tariff of the grid during the last period.
Based on the forecast price of the system and the analysis results of the real-time dispatch plan forecast, the company calculates the grid-connected electricity at the end of the period and predicts the power generation revenue. Based on the results of the real-time dispatch plan analysis, the market personnel provide assisted decision-making information for making adjustments to the quotes during the last trading session.
2.5 System Management Module
This system is an integrated system. It will involve multiple departments and different personnel of the company and subordinate factories in the running process. Therefore, the system management module provides different functions for different types of personnel to set different permissions.
Third, the structure of the quotation system
In view of the geographical distribution of the company's headquarters and its two power plants, the quotation system makes full use of the existing network and terminal facilities, taking full account of the company's existing computer network facilities, using TCP/IP network technology. ,Southeast company accesses the quotation system through LAN. The company's headquarters and its two power plants transmit data through the provincial power system data network permanent virtual circuit (PVC); the outside uses dial-up access through the Internet, the quotation system and Zhejiang Province’s power generation Market technical support systems communicate and access information through the power system data network.
The quotation system adopts a multi-layer client/server architecture. The client program connects to the database through the BDE (Borland database engine) database interface, and obtains the data required by the foreground application program from the web server and the system application server. The system background application program and data acquisition program acquire various data required by the system from various real-time, non-real-time systems (such as MIS, DAS/DCS, power generation market technical support systems, and ERTU power collection terminals) of the power generators. Information, and connection to a relational database through the BDE data interface. The system hardware structure is shown in Figure 1.
The company's database server and application server are used to store various data and information required by the quotation system, and centralize the business logic and data processing logic of the company's part of the entire software system. At the same time, it is responsible for taking from the database application servers of the two power plants. The company headquarters performs the data needed to assist the decision.
The database and application server of Xiaoshan Power Plant and Taizhou Power Plant are used to save all kinds of data and information required by auxiliary decision systems of Xiaoshan Power Plant and Taizhou Power Plant, and provide the business logic processing functions and data processing functions of the two power plants, respectively. Xiaoshan Power Plant, Taizhou The power plant's data acquisition server collects data from various real-time and non-real-time systems.
The workstation (client) is the interface between the system and the user. Various users use the workstation and the system to perform various interactive operations to complete the quotation and information query and decision-making.
The network operating system selected by the system is a Windows 2000 server. SQL server was chosen as the database running and development platform of this system. Using a common and efficient software development tool Delphi5 for software development.
Fourth, the actual operation of the quotation system
The quotation system has been developed and perfected for more than one year and has been installed at the company headquarters and subordinate power plants. In actual operation, the system can help the quoting staff to conduct market analysis, settlement check and quantitative profit analysis, and it plays a good role in analyzing the market conditions of other bidding power generators. It can be able to know and know the bid and reduce the blindness of the quotation; reduce the quotation Personnel's calculation and analysis of labor intensity, and the operation personnel to reduce the output of the deviation assessment and the value of the long-term quotation section of the adjustment of the quoted section capacity has a great guiding role for the company in the electricity market competition has achieved better economic benefits , And for the future for the company's headquarters and a number of power plants far away from the quotation-assisted decision-making system connectivity, resource sharing and scientific quotations, has played a successful demonstration role.
However, this quotation system still needs to be further improved in market marginal price forecasting and quotation-assisted decision analysis. This is mainly due to the fact that there are many factors that affect the market marginal clearing electricity price, and there are many uncertain factors, such as load changes, output changes, and network constraints. It is difficult to establish a more practical mathematical model to conduct intelligent quotation and market price trend analysis, which is also the difficulty of the quotation system. This quotation system adopts the simulation forecasting method and uses the computer simulation system load balance to predict the marginal clearing electricity price at the end of the market, and can only be used as a reference in the quotation assistance decision.
V. Conclusion
Implementing separate factories and networks, bidding for access to the Internet, and establishing a standardized and orderly power coin market can play a fundamental role in market allocation and optimization of resources, thereby realizing the power industry's goal of sustainable development.
In order to be invincible in the power generation market competition, power generation companies must strengthen management and adopt cost leadership strategies. They must actively research quotation skills and conduct design and application of quotation systems. In order to make quote analysis more practical and faster, computer technology must be used to analyze and forecast the marginal market price trend and the behavior of competitors. This system has met the requirements of the "Zhejiang Power Grid Market Regulations" and the use of publicly available information in the electricity market, combined with the cost of generating units for generating units, and based on relevant historical data and data, analyzed the trend of the electricity market and forecasted the market marginal electricity price requirements for the end of the period. Therefore, the work intensity and difficulty of the manual quotation analysis are reduced, and the quotation is known. However, as the provincial power generation market expands into the regional power generation market and the market scope is wider, it is even more important to combine the regional power market research quotation strategy and the use of computer technology for quotation system design and application. It is the power generation companies that grasp the market opportunities and win the battle. The magic of the electricity market remains to be further studied in the future.
Suzhou Sikor Industry Co., Ltd. , https://www.sikor-group.com