Electricity purchasing and selling application system of provincial transaction center

Abstract

The invention relates to the technical field of electricity market transaction, in particular to an electricity purchasing and selling application system of an in-province transaction center, which comprises the following modules: an electricity demand curve optimization module, a user electricity consumption prediction module, an electricity purchasing market simulation and analysis module and an electricity purchasing and selling cockpit decision support module. The method is used for solving the problem of connection between the price quantity strategy and the electricity purchasing scheme of the electricity transaction center. The problems that a cross-department data interaction mechanism is incomplete when electricity purchasing and selling participate in spot market transaction at the present stage, the basis of a spot transaction big data environment is weak, and the scientificity of a quantity price strategy and an electricity purchasing scheme cannot be pre-judged and evaluated are solved; according to the method, high-quality transmission of spot transaction full-service data and real-time simulation calculation of an electricity purchasing strategy are facilitated, the accuracy of an electricity purchasing and selling price strategy is further improved, optimization of participation of electricity purchasing and selling in a spot transaction mode of a power grid is facilitated, and a better supporting effect is achieved for improvement of construction of an electricity purchasing and selling transaction market.

Description

Technical Field

[0001] The present invention relates to the technical field of power market trading, and particularly to a purchase and sale electricity application system for an intra-provincial trading center. Background Art

[0002] At present, the development of the power industry requires standardizing the scale of electricity purchase, sale and consumption, predicting the purchase price, optimizing the adjustment of the user-side curve of electricity purchase and sale, strengthening the information disclosure of electricity purchase and sale, and preventing and controlling the price fluctuation risk of electricity purchase and sale. It is required that the deviation electricity of electricity purchase and sale be settled according to the spot price. At the present stage, there are still problems in participating in the spot market trading of electricity purchase and sale, such as imperfect cross-departmental data interaction mechanism, weak foundation of the spot trading big data environment, and inability to predict and evaluate the scientific nature of quantity-price strategies and electricity purchase plans.

[0003] Therefore, it is necessary to design a purchase and sale electricity application system for an intra-provincial trading center to realize high-quality transmission of all business data of spot trading, real-time simulation and calculation of electricity purchase strategies, further improve the accuracy of electricity purchase and sale quantity-price strategies, help optimize the spot trading mode of power grid electricity purchase and sale, and play a better supporting role in improving the construction of the electricity purchase and sale trading market. Summary of the Invention

[0004] In view of the above problems, the purpose of the present invention is to provide a purchase and sale electricity application system for an intra-provincial trading center, which standardizes the prediction of electricity purchase and sale prices, assists in protecting against electricity purchase and sale price fluctuations, reduces the electricity purchase cost of electricity purchase and sale users, reduces the deviation settlement cost of electricity purchase and sale, reduces the scale of unbalanced funds for electricity purchase and sale, and optimizes the trading mode of participating in the spot market for electricity purchase and sale.

[0005] To achieve the above object, the present invention provides a purchase and sale electricity application system for an intra-provincial trading center, including:

[0006] An electricity demand curve optimization module for generating an optimized electricity consumption curve according to historical electricity consumption data of users;

[0007] A user electricity consumption prediction module for generating a monthly electricity consumption prediction value based on the optimized electricity consumption curve;

[0008] A power purchase market simulation and analysis module for:

[0009] Based on the monthly electricity consumption prediction value, constructing a simulation algorithm library including a spot price fluctuation model, a deviation assessment cost model and an unbalanced fund sharing model;

[0010] Simulating the settlement electricity charges and market operation costs under different electricity purchase packages based on the simulation algorithm library;

[0011] Generating an economic evaluation report based on the simulated settlement electricity charges and market operation costs and pushing it to the purchase and sale electricity cockpit decision support module;

[0012] The purchase and sale of electricity cockpit decision support module is used for:

[0013] Integrate the real-time price of the spot market, the predicted monthly electricity consumption value, and the economic evaluation report, and display the market structure, transaction clearing curve, and settlement cost distribution through a dynamic dashboard;

[0014] Generate optimization suggestions for the electricity purchase plan according to the strategy adjustment instructions input by the user, and feedback the suggestions to the electricity demand curve optimization module;

[0015] Trigger the electricity demand curve optimization module to recalculate the optimal electricity cost solution and update the optimized electricity curve.

[0016] Furthermore, the electricity demand curve optimization module is specifically used for:

[0017] Analyze the user's historical electricity consumption data, extract the monthly total, peak-valley time-of-use electricity consumption, and corresponding electricity costs, and generate a daily granularity electricity curve visualization interface;

[0018] Based on the real-time peak-valley electricity price strategy, simulate the electricity cost calculation results after the user adjusts the electricity consumption distribution at 24 time points, and determine the optimal electricity cost solution by comparing the electricity cost differences of different adjustment schemes;

[0019] Generate an optimized electricity curve including the recommended electricity consumption at 24 time points according to the optimal electricity cost solution, and transmit the optimized electricity curve to the user electricity consumption prediction module.

[0020] Furthermore, the user electricity consumption prediction module is specifically used for:

[0021] Receive the optimized electricity curve, combine the temperature fluctuation coefficient, industry season coefficient, and user business growth coefficient of the meteorological database, use the optimized electricity curve as an input feature, and predict the user's electricity consumption for the next month through a time series model;

[0022] Output the predicted monthly electricity consumption value with a confidence interval based on the predicted user electricity consumption for the next month, and transmit it to the electricity purchase market simulation and analysis module.

[0023] Furthermore, the optimal electricity cost solution is the time allocation plan with the lowest electricity consumption cost.

[0024] Furthermore, the deviation assessment fee is calculated based on the predicted monthly electricity consumption value, combined with the actual electricity consumption difference and the package liability ratio; the unbalanced funds are allocated to the electricity purchase and sale entities through a game theory model.

[0025] Furthermore, the time series model includes weighted regression or LSTM neural network.

[0026] Furthermore, the electricity purchase package includes a service fee model and a deviation liability ratio.

[0027] Furthermore, the economic evaluation report includes cost comparison and risk rating.

[0028] Furthermore, the strategy adjustment instruction includes transaction scale and electricity price threshold.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] By integrating multiple modules such as optimized electricity demand curve, electricity consumption prediction, market simulation, and decision support, the present invention flexibly adjusts peak-valley electricity prices and market-based electricity purchase plans. Users can more efficiently plan their electricity consumption strategies, reduce electricity procurement costs, and monitor market dynamics and settlement results in real time to ensure the transparency and economic benefits of the electricity purchase process. In addition, refined market cost analysis and intelligent decision support help users optimize electricity purchase transactions according to actual needs, improving the operational efficiency and stability of the electricity market. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the present invention, the following will briefly introduce the drawings required for the implementation. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0032] Figure 1 It is a schematic structural diagram of a power purchase and sale application system of an intra-provincial trading center in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] To make the objectives and technical solutions of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] As Figure 1 shown, an embodiment of the present invention provides a power purchase and sale application system for an intra-provincial trading center, including: an optimized electricity demand curve module, a user electricity consumption prediction module, a power purchase market simulation and analysis module, and a power purchase and sale cockpit decision support module.

[0035] The optimized electricity demand curve module is used to generate an optimized electricity consumption curve based on the user's historical electricity consumption data, specifically for:

[0036] Analyze the user's historical electricity consumption data, extract the monthly total amount, peak-valley time-of-use electricity consumption and corresponding electricity charges, and generate a daily-granularity electricity consumption curve visualization interface;

[0037] Based on the real-time peak-valley electricity price strategy, simulate the electricity bill calculation results after the user adjusts the electricity consumption distribution at 24 time points. By comparing the electricity bill differences of different adjustment schemes, determine the optimal solution for the electricity bill (i.e., the time point allocation scheme with the lowest electricity consumption cost).

[0038] Generate an optimized electricity consumption curve (including the recommended electricity consumption at 24 time points) according to the optimal solution of the electricity bill, and transmit the optimized electricity consumption curve to the user electricity consumption prediction module.

[0039] The user electricity consumption prediction module is used to generate a monthly electricity consumption prediction value based on the optimized electricity consumption curve, specifically:

[0040] Receive the optimized electricity consumption curve, combine the temperature fluctuation coefficient, industry season coefficient and user business growth coefficient in the meteorological database, use the optimized electricity consumption curve as the input feature, and predict the user's electricity consumption for the next month through a time series model (weighted regression or LSTM neural network);

[0041] Output a monthly electricity consumption prediction value with a confidence interval based on the predicted user electricity consumption for the next month, and transmit it to the electricity purchase market simulation and analysis module.

[0042] The electricity purchase market simulation and analysis module is used for:

[0043] Based on the monthly electricity consumption prediction value, construct a simulation algorithm library including a spot price fluctuation model, a deviation assessment cost model and an imbalance fund sharing model;

[0044] Based on the simulation algorithm library, simulate the settlement electricity bill and market operation cost under different electricity purchase packages (service fee mode, deviation liability ratio), where:

[0045] The deviation assessment cost is calculated based on the monthly electricity consumption prediction value, combined with the actual electricity consumption difference and the package liability ratio;

[0046] The imbalance fund sharing is dynamically allocated to the power purchase and sale entities through a game theory model;

[0047] Based on the simulated settlement electricity bill and market operation cost, generate an economic evaluation report (including cost comparison, risk rating), and push it to the power purchase and sale cockpit decision support module.

[0048] The power purchase and sale cockpit decision support module is used for:

[0049] Integrate the real-time price of the spot market, the monthly electricity consumption prediction value and the economic evaluation report, and display the market structure, transaction clearing curve and settlement cost distribution through a dynamic dashboard;

[0050] Adjust the strategy adjustment instructions (such as trading scale, electricity price threshold) input by the user, generate optimization suggestions for the electricity purchase plan, and feedback the suggestions to the electricity demand curve optimization module;

[0051] Trigger the electricity demand curve optimization module to recalculate the optimal electricity cost solution and update the optimized electricity curve.

[0052] In the embodiment of the present invention, the electricity demand curve optimization module provides a better solution choice for users to purchase electricity in the market and convenient simulation deduction results by optimizing the market-oriented procurement method of power purchase and sale, and speeds up the pace of users' market-oriented transactions;

[0053] The user electricity consumption prediction module conducts predictions on the trading scale of power purchase and sale, electricity price curve, and spot price, establishes a spot price prediction model, and continuously optimizes relevant models to make the predicted spot price gradually approach the actual spot price. Monitor and analyze the trends of relevant typical load curves and prediction data, anticipate in advance the impact of power purchase and sale price fluctuations on the market, and do a good job in risk prevention and control of price fluctuations, etc., to provide a reference basis for market-oriented power purchase and sale transactions.

[0054] The power purchase market simulation and analysis module analyzes the impact of the power purchase and sale scale and spot price on the settlement results of power purchase and sale users, the deviation of power purchase and sale, and market operation costs such as unbalanced funds for power purchase and sale by building a simulation algorithm library for power purchase and sale simulation settlement and market operation cost deduction, provides strong support for optimizing relevant power purchase and sale transactions and settlement rules, and plays an auxiliary decision-making role in establishing a perfect power market power purchase agency rule.

[0055] The power purchase and sale cockpit decision support module can build an integrated dashboard for the power purchase and sale cockpit, create a comprehensive data analysis platform for power purchase and sale, track market dynamics in real time, and provide a scientific basis for power purchase and sale.

[0056] The present invention can connect the quantity-price strategy of the power trading center with the electricity purchase plan, avoid problems such as imperfect cross-departmental data interaction mechanism, weak foundation of the spot trading big data environment, and inability to predict and evaluate the scientific nature of the quantity-price strategy and electricity purchase plan when participating in the spot market transaction at the present stage, contribute to the high-quality transmission of all-business data in spot transactions, real-time simulation calculation of electricity purchase strategies, further improve the accuracy of the quantity-price strategy of power purchase and sale, help optimize the mode of participating in spot transactions in the power grid's power purchase and sale, and play a better supporting role in the construction of the power purchase and sale trading market.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A power purchase and sales application system for a provincial trading center, characterized in that: include: The power demand curve optimization module is used to generate an optimized power demand curve based on the user's historical power demand data; A user power consumption prediction module, used to generate a monthly power consumption prediction value based on the optimized power consumption curve; Electricity purchasing market simulation and analysis module for: Based on the monthly electricity consumption forecast value, a simulation algorithm library including a spot price fluctuation model, a deviation assessment cost model and an unbalanced fund allocation model is constructed; Simulate the electricity bill settlement and market operation costs under different electricity purchase packages based on the simulation algorithm library; Generate an economic evaluation report based on the simulated electricity bills and market operating expenses and push it to the decision support module of the power purchase and sales cockpit; The power purchase and sales cockpit decision support module is used to: Integrate real-time spot market prices, monthly electricity consumption forecasts and economic evaluation reports, and display market structure, transaction clearing curves and settlement fee distribution through dynamic dashboards; Generate optimization suggestions for power purchase plans based on the strategy adjustment instructions input by the user, and feed the suggestions back to the power demand curve optimization module; The electricity demand curve optimization module is triggered to recalculate the optimal solution for electricity charges and update the optimized electricity consumption curve.

2. The method according to claim 1, characterized in that The electricity demand curve optimization module is specifically used for: Analyze the user's historical electricity consumption data, extract the monthly total, peak and valley time-of-use electricity consumption and corresponding electricity charges, and generate a daily granular electricity consumption curve visualization interface; Based on the real-time peak-valley electricity price strategy, the electricity fee calculation results after users adjust the 24-hour electricity consumption distribution are simulated, and the optimal solution for electricity fee is determined by comparing the differences in electricity fees of different adjustment schemes; An optimized electricity consumption curve including recommended electricity consumption at 24 hours is generated according to the optimal solution of electricity charges, and the optimized electricity consumption curve is transmitted to the user electricity consumption prediction module.

3. The method according to claim 1, characterized in that The user power consumption prediction module is specifically used for: The optimized power consumption curve is received, and combined with the temperature fluctuation coefficient, industry seasonal coefficient and user business growth coefficient of the meteorological database, the optimized power consumption curve is used as an input feature, and the user's power consumption next month is predicted through a time series model; Based on the predicted user's next month's electricity consumption, the monthly electricity consumption forecast value with confidence interval is output and transmitted to the electricity purchase market simulation and analysis module.

4. The method according to claim 2, characterized in that: The optimal solution for electricity charges is the allocation plan at the time point with the lowest electricity cost.

5. The method according to claim 1, characterized in that The calculation of deviation assessment fees is based on the monthly electricity consumption forecast, combined with actual electricity consumption differences and package responsibility ratios; the imbalanced funds are dynamically allocated to electricity buyers and sellers through a game theory model.

6. The power purchase and sale application system of the provincial trading center according to claim 3 is characterized in that: The time series model includes weighted regression or LSTM neural network.

7. The power purchase and sale application system of the provincial trading center according to claim 1 is characterized in that: The electricity purchase package includes a service fee model and a deviation liability ratio.

8. The power purchase and sale application system of the provincial trading center according to claim 1 is characterized in that: The economic assessment report includes cost comparison and risk rating.

9. The power purchase and sale application system of the provincial trading center according to claim 1 is characterized in that: The strategy adjustment instruction includes transaction scale and electricity price threshold.

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