Peak shaving method and device for partitioned power utilization, computer equipment and storage medium

Abstract

The invention provides a peak regulation method and device for partitioned power utilization, computer equipment and a storage medium, and belongs to the technical field of power system analysis, and the method comprises the steps: carrying out the region division of a target region, and determining the peak regulation parameter of each partition; performing clean energy scheduling peak regulation among the partitions based on the consumption gap time period of the clean energy and the load side power consumption valley time period, and determining peak regulation cost per kilowatt hour, reference power purchase price, peak regulation income and load side income; and constructing an NSGA-II algorithm, carrying out iterative optimization on the NSGA-II algorithm by taking maximization of the peak regulation income and the load side income as a target, and determining the peak regulation electric quantity and the peak regulation electricity purchase price. In this way, the absorption capacity of the clean energy is considered, the peak regulation problem of the load side power consumption trough period and the absorption gap period of the clean energy is comprehensively considered, the stability of the power grid is maintained, finally, the cost problem in all aspects is comprehensively considered, the income is maximized, and the economic benefit is improved. The problem of low peak regulation power utilization income of a load side and a power grid is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system analysis, and in particular relates to a peak-shaving method, device, computer equipment and storage medium for zoned electricity consumption. Background Art

[0002] The peak-shaving market is an important guarantee for maintaining safe and stable operation of the power system, ensuring power quality, and promoting the consumption of new energy. From the perspective of market scope, it is divided into intra-regional peak-shaving and inter-regional peak-shaving.

[0003] In the past, the regional peak-shaving market took into account the peak-shaving demand of the entire region and carried out overall peak-shaving market clearing, without taking into account the zoning of the power grid and the cost of peak-shaving, resulting in the abandonment of a large amount of clean energy.

[0004] In the existing technology, by building a multi-energy complementary system, a comprehensive model of multi-energy complementary coordinated development is realized, energy interaction and cascade utilization are achieved, and the absorption capacity of clean energy is improved. However, only considering the absorption of clean energy will increase the peak load pressure of the power grid, further increase the peak load cost, and cause the negative impact of low peak load electricity revenue on the load side and the power grid.

[0005] Therefore, the existing technology still has the problem of low returns for peak-load electricity consumption. Summary of the invention

[0006] In order to solve the problem of low returns in the prior art for peak-shaving electricity, the present invention provides a peak-shaving method, device, computer equipment and storage medium for zoned electricity consumption.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] First, a peak-shaving method for power consumption in different zones is provided, the method comprising:

[0009] Divide the target area into regions, determine the clean energy cost per kilowatt-hour and the consumption gap period in each region, the corresponding price per kilowatt-hour and time period for peak and trough electricity consumption on the load side, and the transmission cost between regions;

[0010] Clean energy dispatching and peak shaving are carried out between different zones based on the clean energy consumption gap period and the load-side electricity consumption valley period, and the peak shaving cost between different zones is determined based on the cost per kilowatt-hour and the unit transmission cost between the zones;

[0011] Determine the benchmark electricity purchase price on the load side based on the corresponding kilowatt-hour prices and time periods during peak and valley periods of electricity consumption on the load side;

[0012] Determine the peak-shaving revenue based on the peak-shaving electricity cost, peak-shaving electricity quantity and peak-shaving electricity purchase price;

[0013] Determine the load-side revenue based on the benchmark electricity purchase price, peak-shaving electricity quantity and peak-shaving electricity purchase price;

[0014] Constructing the NSGA-II algorithm, constructing the chromosome encoding according to the peak-shaving electricity purchase price and the peak-shaving electricity quantity, and generating the initial population according to the peak-shaving electricity cost and the benchmark electricity purchase price;

[0015] The NSGA-II algorithm is iteratively optimized with the goal of maximizing the peak-shaving revenue and load-side revenue to determine the peak-shaving power and peak-shaving electricity purchase price.

[0016] Optionally, the clean energy dispatching and peak shaving between the partitions based on the clean energy consumption gap period and the load-side electricity consumption valley period includes:

[0017] The partitions in the off-peak period of electricity consumption are taken as target partitions, the partitions in the clean energy consumption gap period are determined as matching partitions that match the target partitions, and the matching partitions are sorted according to the distance between the partitions as the priority;

[0018] Peak shaving is performed on the matching partitions and the target partitions in sorted order.

[0019] Optionally, the calculation formula of the electricity cost is:

[0020] Cost per kilowatt-hour = operating cost / power generation;

[0021] The calculation formula of the transmission cost is:

[0022] Unit transmission cost = unit transmission cost per kilometer * number of kilometers;

[0023] The peak load shaving cost per kilowatt-hour is the sum of the cost per kilowatt-hour and the unit transmission cost.

[0024] Optionally, determining the base electricity purchase price on the load side according to the kilowatt-hour prices and time periods corresponding to the peak and valley electricity consumption on the load side includes:

[0025] Calculate the product of the time period length corresponding to the peak electricity consumption and the price of electricity per kilowatt-hour and the product of the time period length corresponding to the valley electricity consumption and the price of electricity per kilowatt-hour respectively;

[0026] The quotient of the sum of the two products and the total length of the two time periods is taken as the benchmark electricity purchase price.

[0027] Optionally, the calculation formula of the peak load regulation benefit is:

[0028] Peak-shaving revenue = peak-shaving electricity volume * (peak-shaving electricity purchase price - peak-shaving electricity cost).

[0029] Optionally, the calculation formula of the load side benefit is:

[0030] Load side revenue = peak-shaving electricity quantity * (benchmark electricity purchase price - peak-shaving electricity purchase price).

[0031] Optionally, the iterative optimization of the NSGA-II algorithm with the goal of maximizing the peak-shaving revenue and the load-side revenue to determine the peak-shaving power and the peak-shaving power purchase price includes:

[0032] The population is sorted according to non-dominance, and for the last selected frontier, the crowding comparison operator is used to sort it in descending order, and the individuals in front are selected by the binary tournament selection operator until the population is filled, so as to obtain a first-generation population; the first-generation population is used as the parent generation, and the second-generation population is generated through selection, crossover and mutation, and it is iterated until the number of iterations reaches a preset number, the iteration is terminated, and the finally obtained population is determined as the optimization result;

[0033] Peak load is regulated in the target area according to the peak load purchasing price and peak load quantity corresponding to the optimization result.

[0034] Secondly, a peak load shaving device for zoned electricity consumption is provided, the device comprising:

[0035] The acquisition module is used to divide the target area into regions, determine the clean energy cost per kilowatt-hour and the consumption gap period in each zone, the corresponding price and time period of peak and trough electricity consumption on the load side, and the transmission cost between zones;

[0036] A determination module is used to dispatch clean energy for peak load regulation between different zones based on the clean energy consumption gap period and the load side electricity consumption valley period, and determine the peak load regulation kilowatt-hour cost between different zones according to the kilowatt-hour cost and the unit transmission cost between the zones; determine the benchmark electricity purchase price on the load side according to the kilowatt-hour price and time period corresponding to the peak and valley electricity consumption on the load side; determine the peak load regulation revenue according to the peak load regulation kilowatt-hour cost, peak load regulation quantity and peak load regulation purchase price; determine the load side revenue according to the benchmark purchase price, peak load regulation quantity and peak load regulation purchase price;

[0037] A construction module is used to construct an NSGA-II algorithm, build a chromosome code according to the peak-shaving electricity purchase price and the peak-shaving electricity quantity, and generate an initial population according to the peak-shaving electricity cost and the benchmark electricity purchase price;

[0038] The optimization module is used to iteratively optimize the NSGA-II algorithm with the goal of maximizing the peak-shaving revenue and the load-side revenue, and to determine the peak-shaving power and the peak-shaving power purchase price.

[0039] Then, a computer-readable storage medium is also provided, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned peak-shaving method for zoned electricity consumption is implemented.

[0040] Finally, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned peak-shaving method for zoned electricity consumption when executing the program.

[0041] The peak-shaving method for zoned electricity consumption provided by the present invention has the following beneficial effects:

[0042] First, through reasonable regional division, the distribution and consumption of clean energy can be managed more effectively, and the utilization rate of clean energy can be improved. Secondly, by dispatching clean energy between different zones, the clean energy generation capacity of each zone can be fully utilized to improve the stability and economy of the power grid. Then, the peak-shaving electricity cost, benchmark electricity purchase price, peak-shaving income and load-side income are determined, and the economic cost and income of peak-shaving are further determined, which is helpful to formulate a reasonable electricity price policy and encourage users to participate in peak-shaving. Finally, by constructing the NSGA-II algorithm and iteratively optimizing it, the optimal solution for maximizing peak-shaving income and load-side income is obtained. This not only takes into account the consumption capacity of clean energy, but also comprehensively considers the peak-shaving problem during the low-consumption period on the load side and the consumption gap period of clean energy, which is conducive to maintaining the stability of the power grid. Finally, the cost issues of various aspects are comprehensively considered to maximize the income, and the problem of low peak-shaving electricity income on the load side and the power grid is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 The present invention is a flowchart of a peak-shaving method for zoned electricity consumption provided according to an exemplary embodiment of the present invention.

[0045] Figure 2 A schematic diagram of functional modules of a peak-shaving market technical support system provided according to an exemplary embodiment of the present invention.

[0046] Figure 3 A block diagram of a peak-shaving device for zoned electricity consumption provided according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0048] The technical solutions provided by various embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0049] First, the present invention provides a peak load regulation method for power consumption in different areas, specifically: Figure 1 As shown, the following steps are included:

[0050] S101. Divide the target area into regions and determine the peak load parameters of each region.

[0051] Specifically, the target area is first divided into regions to determine the clean energy cost per kilowatt-hour and the time period for absorbing the gap in each zone, the corresponding price per kilowatt-hour and time period for peak and trough electricity consumption on the load side, and the transmission cost between zones.

[0052] The target area may be divided into regions based on one or more factors such as administrative regions, resource endowment of the power grid, or topography.

[0053] In one embodiment, a provincial-regional model is first established within the province according to the regions, and the resource endowment and peak-shaving supply and demand characteristics of the regional power grid are analyzed, with the goal of promoting clean energy consumption. Clean energy units declare peak-shaving demands, and adjustable resources on the load side provide peak-shaving capabilities, thus forming a realistic and feasible provincial peak-shaving market supply and demand relationship.

[0054] S102. Clean energy is dispatched and peak-shaving is performed among the zones based on the clean energy consumption gap period and the load-side electricity consumption valley period.

[0055] In this step, based on the principle of giving priority to power generation of clearing and settling energy and the goal of maximizing economic benefits, the peak-shaving supply and demand relationship can be determined as follows: clearing and settling energy has a peak-shaving demand during the low-power consumption period of the day, and the adjustable resources on the load side provide peak-shaving capacity through staggered power consumption. The peak-shaving services are traded in the peak-shaving markets of each region and flow from the adjustable resource area on the load side to the clearing and settling energy power generation area.

[0056] Specifically, we can first analyze the operating costs of load-side resources and clearing energy, design a trading model with market economic benefits, and formulate market rules accordingly; finally, we can design system functions according to the market model and build a technical support system for the provincial-regional peak-shaving market for load-side resource access. This can be applied to the control system and trading system of the provincial power grid. On the basis of considering the low power generation cost of clean energy units, we can control the peak power consumption of load-side resources through market-oriented means.

[0057] For example, the partitions in the off-peak period can be used as target partitions, and the partitions in the clean energy consumption gap period can be determined as matching partitions that match the target partitions. The matching partitions are sorted according to the distance between the partitions as the priority; the matching partitions and the target partitions are peak-shifted in the sorting order. When the matching partitions in the front column of the sorting complete the consumption gap, the subsequent matching partitions and target partitions are peak-shifted in turn according to the sorting order. Alternatively, the target partitions can be sorted, and the arranged target partitions and matching partitions can be peak-shifted in turn according to the sorting order.

[0058] In one embodiment, the market operation is based on the principle of priority consumption of clear energy, and analyzes the operating costs and market benefits of various market entities on the premise of meeting the balance of power generation and consumption of the power grid. The market transaction price is investigated by calculating the power generation cost on the power supply side; the market bidding space is evaluated by analyzing the power spot cycle price; and the provincial regional peak-shaving market transaction model is designed from the perspective of economic benefits. The analysis of the types of market entities in the regional peak-shaving market includes calculating the power generation cost of clean energy units, analyzing the cyclical fluctuation pattern of power spot prices, and clarifying the market bidding space.

[0059] For the peak-load electricity regulation of each zone, the peak-load electricity cost between different zones is first determined based on the cost per kilowatt-hour and the unit transmission cost between the zones.

[0060] For example, the spot price of electricity has typical peak-valley characteristics and shows intraday cyclical fluctuations. The price during peak hours is between 0.6 and 1.0 yuan / KWh, and the price during trough hours is between 0.2 and 0.5 yuan / KWh.

[0061] Qingjie Energy only considers operating costs and estimates that the cost per kilowatt-hour is less than 0.1 yuan / KWh. The power generation cost is lower than the spot electricity price during the off-peak period, which means that participating in the peak-shaving market at the spot price during the off-peak period has profit margins. The calculation formula for the cost per kilowatt-hour is:

[0062] Cost per kilowatt-hour = operating cost / electricity generation.

[0063] The formula for calculating the transmission cost is:

[0064] Unit transmission cost = unit transmission cost per kilometer * number of kilometers.

[0065] The peak-shaving electricity cost is the sum of the electricity cost and the unit transmission cost.

[0066] Secondly, the benchmark electricity purchase price on the load side is determined based on the corresponding kilowatt-hour prices and time periods during the peak and trough periods of electricity consumption on the load side.

[0067] For example, calculate the product of the time period length corresponding to the peak electricity consumption and the price per kilowatt-hour and the product of the time period length corresponding to the trough electricity consumption and the price per kilowatt-hour respectively; and use the quotient of the sum of the two products and the total length of the two time periods as the benchmark electricity purchase price.

[0068] Then, based on the peak-shaving electricity cost and the benchmark electricity purchase cost, the correlation between the peak-shaving electricity purchase price and the peak-shaving revenue and load-side revenue is determined respectively.

[0069] For example, the peak-shaving revenue can be determined based on the peak-shaving electricity cost, the peak-shaving electricity quantity and the peak-shaving electricity purchase price; and the load-side revenue can be determined based on the benchmark electricity purchase price, the peak-shaving electricity quantity and the peak-shaving electricity purchase price.

[0070] For example, the calculation formula for the peak load benefit can be:

[0071] Peak-shaving revenue = peak-shaving electricity volume * (peak-shaving electricity purchase price - peak-shaving electricity cost).

[0072] The clean energy units ensure the consumption of clean energy by increasing their production during off-peak periods. Different types of power sources have different consumption gap periods. For example, hydropower faces consumption pressure throughout the day during the flood season, wind power usually faces consumption pressure at night, and photovoltaic power faces consumption pressure at noon. Organizing peak-shaving transactions can avoid the risks of abandoning water, wind and light.

[0073] For another example, the calculation formula for the load side benefit can be:

[0074] Load side revenue = peak-shaving electricity quantity * (benchmark electricity purchase price - peak-shaving electricity purchase price).

[0075] The load side provides peak-shaving capacity through staggered electricity consumption. Clear energy is difficult to consume during the off-peak period and there is a peak-shaving demand. Therefore, the load side can respond to the market's peak-shaving demand and change the original peak-time electricity consumption habits to the off-peak period to obtain the economic benefits of purchasing electricity at a low price. The load side can adjust resources as electricity users. The benchmark electricity purchase price is equal to the average spot price of electricity, which is estimated to be around 0.5 yuan / KWh. When load users purchase electricity at a price lower than the benchmark electricity purchase price, they can save electricity bills and have economic benefits.

[0076] S103, constructing the NSGA-II algorithm, building chromosome encoding according to the peak-shaving electricity purchase price and the peak-shaving electricity quantity, and generating an initial population according to the peak-shaving electricity cost and the benchmark electricity purchase price.

[0077] In this step, the specific algorithm construction process can be as follows:

[0078] (1) Chromosome coding design. The chromosome length designed by the present invention is 2*S (n) , these two chromosome codes represent the peak-shaving electricity purchase price and peak-shaving electricity quantity respectively.

[0079] (2) Generate the initial population. First, randomly generate an initial population of a preset size npop, and then perform the first round of screening to screen out individuals that do not meet the conditions. Assume that the number of individuals screened out in the mth round is nc m (nc m ≤npop) After the screening is completed, nc is randomly generated again m The above steps are repeated until the screening is completed and the population size is npop, then the initial population generation is completed.

[0080] S104. Iteratively optimize the NSGA-II algorithm with the goal of maximizing the peak-shaving revenue and the load-side revenue to determine the peak-shaving power and the peak-shaving power purchase price.

[0081] For example, the population can be sorted according to non-dominance, and the last selected frontier is sorted in descending order using a crowding comparison operator, and the front individuals are selected through a binary tournament selection operator until the population is filled, thereby obtaining a first-generation population; the first-generation population is used as the parent generation, and a second-generation population is generated through selection, crossover, and mutation. The iteration is performed iteratively until the number of iterations reaches a preset number, at which point the iteration ends and the final population is determined to be the optimization result; finally, the target area is peak-shaving according to the peak-shaving electricity purchase price and peak-shaving power corresponding to the optimization result.

[0082] It should be noted that the NSGA-II algorithm is iterated, and the population is sorted according to non-dominance. The solution belonging to the best non-dominated set is the best solution in the combined population and must be closer to the target than any other solution in the combined population. In order to accurately select population members, the present invention uses a crowding comparison operator to sort the solutions of the last frontier in descending order and selects the best solution required to fill all populations. The new size population is now used for selection, crossover and mutation to create a new size population. It is worth noting that the present invention uses a binary tournament selection operator, but the selection criteria are now based on a crowding comparison operator. Since the operator requires the rank and crowding distance of each solution in the population, the present invention calculates the objective function values ​​of the adjacent individuals before and after sorting while forming the population. The present invention takes the non-dominated sorted population after 300 population iterations as the optimization result, and combines the correlation to obtain the optimized peak-shaving power purchase price and peak-shaving power.

[0083] By adopting the above method, firstly, through reasonable regional division, the distribution and consumption of clean energy can be managed more effectively, and the utilization rate of clean energy can be improved. Secondly, by dispatching clean energy between each partition, the clean energy generation capacity of each partition can be fully utilized to improve the stability and economy of the power grid. Then, the peak-shaving electricity cost, benchmark electricity purchase price, peak-shaving income and load-side income are determined, and the economic cost and income of peak-shaving are further determined, which is helpful to formulate a reasonable electricity price policy and encourage users to participate in peak-shaving. Finally, by constructing the NSGA-II algorithm and iteratively optimizing it, the optimal solution for maximizing peak-shaving income and load-side income is obtained. This not only takes into account the consumption capacity of clean energy, but also comprehensively considers the peak-shaving problem during the low-consumption period on the load side and the consumption gap period of clean energy, which is conducive to maintaining the stability of the power grid. Finally, the cost issues of various aspects are comprehensively considered to maximize the income, and the problem of low peak-shaving electricity income on the load side and the power grid is solved.

[0084] Further, such as Figure 2 As shown, a peak-shaving market trading system is designed based on the technical solution of the present invention. For example, it can be divided based on administrative regions, and according to the maximization of economic benefits, the peak-shaving market is divided into three levels: provincial regulation, local regulation and county regulation. Each level includes the balance analysis of the power generation side and the load side, the judgment of the regulation capacity, the market organization and the corresponding market results. The functional modules of the peak-shaving market technical support system are designed, mainly including the functional processes such as market declaration, market clearing, and result release:

[0085] 1) The market declaration function is used to realize the declaration of market transaction data in the peak-shaving market, complete the declaration of peak-shaving demand data, the declaration of peak-shaving capacity data, as well as the declaration, reception and aggregation of provincial sub-district power grid data, and respond to peak-shaving needs to carry out provincial sub-district peak-shaving auxiliary service transactions. The specific functions supported include:

[0086] Peak-shaving demand zoning data declaration: The load-side regulation resources providing peak-shaving services declare the peak-shaving capacity and electricity price curve for 96 points throughout the day, which corresponds to the peak-shaving capacity and peak-shaving electricity purchase price for each period.

[0087] Regional data declaration of peak-shaving capacity: Clean energy enterprises that propose peak-shaving demand shall declare the peak-shaving demand electricity price curve for 96 points throughout the day, which means the peak-shaving demand and peak-shaving electricity sales price for each period.

[0088] 2) The market clearing adopts the trading mechanism of "prioritized clearing within the sub-zone, bilateral bidding between buyers and sellers, and unified marginal clearing". Under the condition of meeting the grid security constraints, the demand-capacity within the sub-zone is cleared first, and the seller's bids in each time period are sorted from low to high, and the buyer's bids in each time period are sorted from high to low, until the prices of both parties meet or meet the peak load demand of the time period, forming a unified marginal clearing price and winning power, and the transaction price is the corresponding marginal clearing price of the last winning power generation enterprise.

[0089] 3) Result release function. The market clearing results are released to market entities as their implementation standards and settlement basis. The market clearing results include the overall market transaction power curve, electricity price curve, transaction volume, as well as the transaction power and electricity price curve of each new energy unit and load-side entity.

[0090] Secondly, the present invention also provides a peak load shaving device for power consumption in different areas, such as Figure 3 As shown, including:

[0091] The acquisition module 301 is used to divide the target area into regions, determine the clean energy cost per kilowatt-hour and the consumption gap period in each region, the corresponding price per kilowatt-hour and time period of the peak and valley electricity consumption on the load side, and the transmission cost between the regions;

[0092] Determination module 302, for performing clean energy dispatch peak load regulation between different zones based on the clean energy consumption gap period and the load side electricity consumption valley period, and determining the peak load regulation kilowatt-hour cost between different zones according to the kilowatt-hour cost and the unit transmission cost between the zones; determining the load side benchmark electricity purchase price according to the kilowatt-hour price and time period corresponding to the load side electricity consumption peak and electricity consumption valley; determining the peak load regulation revenue according to the peak load regulation kilowatt-hour cost, the peak load regulation quantity and the peak load regulation purchase price; determining the load side revenue according to the benchmark purchase price, the peak load regulation quantity and the peak load regulation purchase price;

[0093] A construction module 303 is used to construct an NSGA-II algorithm, build a chromosome code according to the peak-shaving electricity purchase price and the peak-shaving electricity quantity, and generate an initial population according to the peak-shaving electricity cost and the benchmark electricity purchase price;

[0094] The optimization module 304 is used to iteratively optimize the NSGA-II algorithm with the goal of maximizing the peak-shaving revenue and the load-side revenue, and determine the peak-shaving power and the peak-shaving power purchase price.

[0095] By adopting the above device, firstly, through reasonable regional division, the distribution and consumption of clean energy can be more effectively managed, and the utilization rate of clean energy can be improved. Secondly, by dispatching and peaking clean energy between each partition, the clean energy generation capacity of each partition can be fully utilized to improve the stability and economy of the power grid. Then, the peak-shaving electricity cost, the benchmark electricity purchase price, the peak-shaving income and the load-side income are determined, and the economic cost and income of peak-shaving are further determined, which is helpful to formulate a reasonable electricity price policy and encourage users to participate in peak-shaving. Finally, by constructing the NSGA-II algorithm and iteratively optimizing it, the optimal solution for maximizing the peak-shaving income and the load-side income is obtained. This not only takes into account the consumption capacity of clean energy, but also comprehensively considers the peak-shaving problem during the low-consumption period on the load side and the consumption gap period of clean energy, which is conducive to maintaining the stability of the power grid. Finally, the cost issues of various aspects are comprehensively considered to maximize the income, and the problem of low peak-shaving electricity income on the load side and the power grid is solved.

[0096] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 The steps of the peak-shaving method for zoned electricity consumption are provided.

[0097] The present invention also provides a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 The steps of the peak-shaving method for zoned electricity consumption are provided.

[0098] It should be noted that the above specific implementation method can enable those skilled in the art to understand the invention more comprehensively, but does not limit the invention in any way. Therefore, although the present invention has been described in detail in this specification, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

Claims

1. A peak-shaving method for power consumption in different regions, characterized in that: The method comprises: Divide the target area into regions, determine the clean energy cost per kilowatt-hour and the consumption gap period in each region, the corresponding price per kilowatt-hour and time period for peak and trough electricity consumption on the load side, and the transmission cost between regions; Clean energy dispatching and peak shaving are carried out between different zones based on the clean energy consumption gap period and the load-side electricity consumption valley period, and the peak shaving cost between different zones is determined based on the cost per kilowatt-hour and the unit transmission cost between the zones; Determine the benchmark electricity purchase price on the load side based on the corresponding kilowatt-hour prices and time periods during peak and valley periods of electricity consumption on the load side; Determine the peak-shaving revenue based on the peak-shaving electricity cost, peak-shaving electricity quantity and peak-shaving electricity purchase price; Determine the load-side revenue based on the benchmark electricity purchase price, peak-shaving electricity volume and peak-shaving electricity purchase price; Constructing the NSGA-II algorithm, building chromosome encoding according to the peak-shaving electricity purchase price and peak-shaving electricity quantity, and generating an initial population according to the peak-shaving electricity cost and the benchmark electricity purchase price; The NSGA-II algorithm is iteratively optimized with the goal of maximizing the peak-shaving revenue and load-side revenue to determine the peak-shaving power and peak-shaving electricity purchase price.

2. A method for peak load regulation of power consumption by different regions according to claim 1, characterized in that: The clean energy dispatching and peak shaving between the zones based on the clean energy consumption gap period and the load side electricity consumption valley period includes: The partitions in the off-peak period of electricity consumption are taken as target partitions, the partitions in the clean energy consumption gap period are determined as matching partitions that match the target partitions, and the matching partitions are sorted according to the distance between the partitions as the priority; Peak shaving is performed on the matching partitions and the target partitions in sorted order.

3. A peak load regulation method for zoned electricity consumption according to claim 1, characterized in that: The calculation formula of the electricity cost is: Cost per kilowatt-hour = operating cost / electricity generation; The calculation formula of the transmission cost is: Unit transmission cost = unit transmission cost per kilometer * number of kilometers; The peak load shaving cost per kilowatt-hour is the sum of the cost per kilowatt-hour and the unit transmission cost.

4. A method for peak load regulation of power consumption by region according to claim 1, characterized in that: The method of determining the base electricity purchase price on the load side according to the corresponding kilowatt-hour prices and time periods of the peak and valley electricity consumption on the load side includes: Calculate the product of the time period length corresponding to the peak electricity consumption and the price of electricity per kilowatt-hour and the product of the time period length corresponding to the valley electricity consumption and the price of electricity per kilowatt-hour respectively; The quotient of the sum of the two products and the total length of the two time periods is taken as the benchmark electricity purchase price.

5. A peak load regulation method for zoned electricity consumption according to claim 1, characterized in that: The calculation formula of the peak load regulation benefit is: Peak-shaving revenue = peak-shaving electricity volume * (peak-shaving electricity purchase price - peak-shaving electricity cost).

6. A method for peak load regulation of power consumption by different regions according to claim 1, characterized in that: The calculation formula of the load side benefit is: Load side revenue = peak-shaving electricity quantity * (benchmark electricity purchase price - peak-shaving electricity purchase price).

7. A method for peak load regulation of zoned electricity consumption according to claim 1, characterized in that: The NSGA-II algorithm is iteratively optimized with the goal of maximizing the peak-shaving revenue and the load-side revenue to determine the peak-shaving power and the peak-shaving power purchase price, including: The population is sorted according to non-dominance, and for the last selected frontier, the crowding comparison operator is used to sort it in descending order, and the individuals in front are selected by the binary tournament selection operator until the population is filled, so as to obtain a first-generation population; the first-generation population is used as the parent generation, and the second-generation population is generated through selection, crossover and mutation, and it is iterated until the number of iterations reaches a preset number, the iteration is terminated, and the finally obtained population is determined as the optimization result; Peak load is regulated in the target area according to the peak load purchasing price and peak load quantity corresponding to the optimization result.

8. A peak load shaving device for zoned electricity consumption, characterized in that: The device comprises: The acquisition module is used to divide the target area into regions, determine the clean energy cost per kilowatt-hour and the consumption gap period in each zone, the corresponding price and time period of peak and trough electricity consumption on the load side, and the transmission cost between zones; A determination module is used to dispatch clean energy for peak load regulation between different zones based on the clean energy consumption gap period and the load side electricity consumption valley period, and determine the peak load regulation kilowatt-hour cost between different zones according to the kilowatt-hour cost and the unit transmission cost between the zones; determine the benchmark electricity purchase price on the load side according to the kilowatt-hour price and time period corresponding to the peak and valley electricity consumption on the load side; determine the peak load regulation revenue according to the peak load regulation kilowatt-hour cost, peak load regulation quantity and peak load regulation purchase price; determine the load side revenue according to the benchmark purchase price, peak load regulation quantity and peak load regulation purchase price; A construction module is used to construct an NSGA-II algorithm, build a chromosome code according to the peak-shaving electricity purchase price and the peak-shaving electricity quantity, and generate an initial population according to the peak-shaving electricity cost and the benchmark electricity purchase price; The optimization module is used to iteratively optimize the NSGA-II algorithm with the goal of maximizing the peak-shaving revenue and the load-side revenue, and to determine the peak-shaving power and the peak-shaving power purchase price.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program.

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