Photovoltaic producer-consumer cluster peak shaving demand response method and system based on electro-carbon coupling

Abstract

The application discloses a photovoltaic producer-consumer cluster peak shaving demand response method and system based on electric-carbon coupling, and the method comprises the following steps: establishing an electric-carbon coupling photovoltaic producer-consumer cluster energy management framework and a peak shaving response operation mode; establishing a photovoltaic producer-consumer cluster basic model; considering dynamic carbon emission intensity and producer-consumer dynamic roles, combining the fixed load model and the translatable load model, and constructing a photovoltaic producer-consumer comprehensive energy purchasing cost model; based on the electricity utility model and the comprehensive energy purchasing cost model, constructing an electric-carbon coupling photovoltaic producer-consumer peak shaving response comprehensive cost model; according to the translatable load constraint and the peak shaving response comprehensive cost model, constructing a photovoltaic producer-consumer cluster peak shaving demand response model, and under the electric-carbon coupling photovoltaic producer-consumer cluster distributed peak shaving interaction strategy, a photovoltaic producer-consumer cluster peak shaving demand response strategy is obtained. The application can effectively promote renewable energy consumption and reduce carbon emissions.

Description

Technical Field

[0001] This invention belongs to the field of power load participation in grid demand response technology, and relates to a photovoltaic producer-consumer cluster peak shaving demand response method and system based on electric carbon coupling. Background Technology

[0002] With the large-scale integration of distributed photovoltaic (PV) systems on the user side, a large number of PV producers and consumers have emerged, combining user load with small-scale power generators.

[0003] The low-carbon optimization problem of photovoltaic user groups based on electricity-carbon coupling urgently needs to be solved. Since the capacity of individual photovoltaic producers and consumers is relatively small, if a large number of photovoltaic producers and consumers participate in the electricity market in a disorderly manner, it can easily lead to a significant increase in transaction and operation and maintenance costs. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a photovoltaic producer-consumer cluster peak-shaving demand response method and system based on electro-carbon coupling, which can promote the consumption of renewable energy and reduce carbon emissions.

[0005] The present invention adopts the following technical solution.

[0006] A photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling includes:

[0007] Establish an energy management framework for photovoltaic producer-consumer clusters with electro-carbon coupling and a peak-shaving response operation mode;

[0008] Based on the aforementioned photovoltaic producer-consumer cluster energy management framework and peak-shaving response operation mode with electro-carbon coupling, a basic model of photovoltaic producer-consumer cluster is established, including a fixed load model, a shiftable load model, and a shiftable load constraint and electricity utility model.

[0009] Considering dynamic carbon emission intensity and the dynamic role of producers and consumers, and combining the fixed load model and the shiftable load model, a comprehensive energy purchase cost model for photovoltaic producers and consumers is constructed.

[0010] Based on the electricity utility model and the comprehensive energy purchase cost model, a photovoltaic producer-consumer peak shaving response comprehensive cost model coupled with carbon emissions is constructed.

[0011] Based on the shiftable load constraint and the peak shaving response comprehensive cost model, a photovoltaic producer-consumer cluster peak shaving demand response model is constructed. Under the distributed peak shaving interaction strategy of photovoltaic producer-consumer cluster based on electricity-carbon coupling, the peak shaving demand response strategy of photovoltaic producer-consumer cluster is solved to realize the peak shaving demand response of photovoltaic producer-consumer cluster.

[0012] Preferably, the energy management framework of the photovoltaic producer-consumer cluster coupled with carbon energy includes an energy sharing service provider (ESP) and a photovoltaic producer-consumer cluster, wherein the ESP coordinates energy sharing among photovoltaic producers-consumers in the park, and each photovoltaic producer-consumer includes photovoltaic devices;

[0013] The peak shaving response operation mode is as follows: the power demand of photovoltaic producers and consumers is first met by the output of photovoltaic devices. If the output is insufficient, energy is purchased from the grid through ESP. If the output is excessive, the excess power is shared through ESP. The power load of each photovoltaic producer and consumer includes shiftable loads and has the ability to automatically respond to demand. Based on the peak shaving demand, the local optimization of producers and consumers is realized through EMS, and the shiftable load arrangement of each producer and consumer is decided.

[0014] Preferably, the fixed load model is:

[0015] f i =[f i 1 ,…,f i h ,…,f i H ], i∈[1,2,…,n] (1)

[0016] In the formula: f i For the fixed load model of the i-th photovoltaic power consumer; f i 1 f i h f i H Let be the fixed load of the i-th photovoltaic power consumer in the 1st, hth, and Hth time periods;

[0017] n represents the number of photovoltaic producers and consumers in the photovoltaic producer-consumer cluster;

[0018] The transferable load model is as follows:

[0019]

[0020] In the formula: s i For the i-th photovoltaic power consumer, a transferable load model is provided. Let be the transferable load of the i-th photovoltaic power consumer in the 1st and Hth time periods;

[0021] Let K be the portable load of the i-th photovoltaic power consumer in the h-th time period, where K i Let be the total number of controllable electrical devices owned by the i-th photovoltaic producer-consumer. This represents the transferable load value of the k-th controllable electrical device within the h-th time period.

[0022] Preferably, the transferable load constraint is:

[0023] If h∈[α] h ,β h ],but

[0024] like but

[0025] as well as

[0026]

[0027] In the formula: [α] h ,β h [This refers to any selectable translation interval of the transferable load;]

[0028] Let be the portable load of the i-th photovoltaic power consumer in the h-th time period;

[0029] These are the minimum and maximum values ​​of the load that the i-th photovoltaic power consumer can transfer in the h-th time period, respectively.

[0030] L i The total portable load of photovoltaic power consumers i across all time periods;

[0031] H represents the total number of time periods in a day.

[0032] Preferably, the electricity consumption efficiency model is as follows:

[0033]

[0034] In the formula: The electricity consumption efficiency of photovoltaic power generation and consumption;

[0035] ζ i Let i be the electricity preference coefficient for photovoltaic power consumer i.

[0036] f i h Let be the fixed load of the i-th photovoltaic power consumer in the h-th time period;

[0037] Let be the transferable load of the i-th photovoltaic producer-consumer in the h-th time period.

[0038] Preferably, the step of considering dynamic carbon emission intensity and the dynamic roles of producers and consumers, and combining the fixed load model and the shiftable load model to construct a comprehensive energy purchase cost model for photovoltaic producers and consumers includes:

[0039] Based on the different dynamic roles of producers and consumers, the comprehensive energy purchase cost models are established as follows:

[0040] like Then, the i-th photovoltaic producer-consumer is a buyer in the h-th time period, and the comprehensive energy purchase cost model is as follows:

[0041]

[0042] like Then, the i-th photovoltaic producer-consumer is a seller in the h-th time period, and the comprehensive energy purchase cost model is as follows:

[0043]

[0044] In the formula: Let be the total energy purchase cost for the i-th photovoltaic producer-consumer in the h-th time period;

[0045] Let be the net load of the i-th photovoltaic power consumer in the h-th time period;

[0046] PE h The time-of-use electricity price for the grid in the h-th time period;

[0047] f i h Let be the fixed load of the i-th photovoltaic power consumer in the h-th time period;

[0048] Let be the portable load of the i-th photovoltaic power consumer in the h-th time period;

[0049] Let be the predicted active power output of the photovoltaic power source for the i-th photovoltaic producer-consumer;

[0050] ρ c δ represents the carbon price; δ represents the carbon emission share per unit of electricity generated.

[0051] The dynamic carbon emission intensity of the electricity purchased by the i-th photovoltaic producer-consumer in the h-th time period;

[0052] Let be the amount of electricity purchased from the grid by the i-th photovoltaic power consumer in the h-th time period;

[0053] ft h Let be the on-grid electricity price for the h-th time period.

[0054] Preferably, the net load of the i-th photovoltaic power consumer in the h-th time period is:

[0055]

[0056] In the formula: n is the number of photovoltaic producers and consumers in the photovoltaic producer-consumer cluster.

[0057] Preferably, the formula for calculating the dynamic carbon emission intensity of the electricity purchased by the i-th photovoltaic producer-consumer in the h-th time period is:

[0058]

[0059] In the formula: Let M be the carbon emission intensity of the region where the i-th photovoltaic producer-consumer is located during the h-th time period; M is the set of nodes contained in the region where the i-th photovoltaic producer-consumer is located, where each node contains several photovoltaic producers-consumers; Let node m be the load during the h-th time period; Let m be the carbon potential at node m.

[0060] Preferably, the peak-shaving response comprehensive cost model is as follows:

[0061] like but

[0062] like but

[0063] In the formula: Let $\frac{i}{i}$ be the total cost of peak shaving response for the i-th photovoltaic power consumer in the $h$ time period in the electro-carbon coupling process.

[0064] PE h The time-of-use electricity price for the grid in the h-th time period;

[0065] The electricity consumption efficiency of photovoltaic power generation and consumption;

[0066] ζ i Let i be the electricity preference coefficient for photovoltaic power consumer i.

[0067] Let be the peak shaving compensation price for the i-th photovoltaic producer / consumer in the h-th time period.

[0068] Preferably, the photovoltaic producer-consumer cluster peak-shaving demand response model is as follows:

[0069]

[0070] In the formula: Let $\frac{i}{i}$ be the total cost of peak shaving response for the i-th photovoltaic power consumer in the $h$ time period in the electro-carbon coupling process.

[0071] [α h ,β h [This refers to any selectable translation interval of the transferable load;]

[0072] Let be the portable load of the i-th photovoltaic power consumer in the h-th time period;

[0073] These are the minimum and maximum values ​​of the load that the i-th photovoltaic power consumer can transfer in the h-th time period, respectively.

[0074] L i This represents the total portable load of photovoltaic power consumers (i) across all time periods.

[0075] Preferably, the process of solving for the peak-shaving demand response strategy of the photovoltaic producer-consumer cluster under the distributed peak-shaving interaction strategy based on electro-carbon coupling includes:

[0076] (1) ESP sends grid electricity price, carbon price, and dynamic carbon emission intensity information to the EMS of all photovoltaic producers and consumers;

[0077] (2) Each photovoltaic producer-consumer EMS performs local optimization to solve the peak-shaving demand response model of the photovoltaic producer-consumer cluster and obtain the movable load of the photovoltaic producer-consumer.

[0078] (3) The shiftable loads of each photovoltaic producer and consumer constitute the peak-shaving demand response strategy of the photovoltaic producer and consumer cluster.

[0079] A photovoltaic producer-consumer cluster peak-shaving demand response system based on electro-carbon coupling includes:

[0080] The management framework and operation mode construction module is used to establish an energy management framework and peak shaving response operation mode for photovoltaic producer-consumer clusters with electricity-carbon coupling.

[0081] The basic model building module is used to establish a basic model of a photovoltaic producer-consumer cluster, including a fixed load model, a movable load model, and movable load constraints and electricity consumption efficiency models.

[0082] The integrated energy purchase cost model construction module is used to consider dynamic carbon emission intensity and dynamic roles of producers and consumers, and to construct a photovoltaic producer-consumer integrated energy purchase cost model in combination with the fixed load model and the shiftable load model.

[0083] The peak shaving response comprehensive cost model module is used to construct an electricity-carbon coupled photovoltaic producer-consumer peak shaving response comprehensive cost model based on the electricity utility model and the comprehensive energy purchase cost model.

[0084] The demand response module is used to construct a photovoltaic producer-consumer cluster peak shaving demand response model based on the shiftable load constraint and peak shaving response comprehensive cost model. Under the distributed peak shaving interaction strategy of photovoltaic producer-consumer cluster based on electricity-carbon coupling, the peak shaving demand response strategy of photovoltaic producer-consumer cluster is solved to realize the peak shaving demand response of photovoltaic producer-consumer cluster.

[0085] A terminal includes a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0086] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method.

[0087] The beneficial effects of this invention are compared with those of the prior art:

[0088] This invention is based on electric-carbon coupling, incorporating shiftable loads into the optimization of photovoltaic producer-consumer clusters, and considering factors such as dynamic carbon emission intensity, peak shaving response, and electricity consumption efficiency to carry out low-carbon optimization of photovoltaic producer-consumer clusters. The model is also more accurate and practical, promoting energy-carbon interaction and the formation of low-carbon mechanisms, which helps to achieve energy conservation and carbon reduction and build a clean and low-carbon system.

[0089] This invention integrates a large number of photovoltaic prosumers with different capacities to form a photovoltaic prosumer cluster, which can significantly reduce the number of market players and reduce the total operating costs of market transactions and operation and maintenance management.

[0090] This invention introduces dynamic carbon emission intensity, which allows photovoltaic producers and consumers to effectively perceive the peak-valley difference in carbon emission intensity and guides them to actively reduce carbon emissions, thereby achieving distributed peak shaving interaction among photovoltaic producers and consumers and reducing the overall carbon emissions of the system.

[0091] This invention proposes a distributed peak-shaving interaction strategy for photovoltaic producer-consumer clusters, which further taps the carbon reduction potential of photovoltaic producer-consumers, promotes the consumption of renewable energy, and effectively reduces the carbon emissions of the system.

[0092] This invention develops a peak-shaving demand response strategy for photovoltaic producer-consumer clusters, which can be applied to actual industrial parks to achieve energy-carbon balance. Attached Figure Description

[0093] Figure 1 This is a flowchart of the photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling of the present invention.

[0094] Figure 2 This invention describes the implementation process of a distributed peak-shaving interaction strategy for photovoltaic producer-consumer clusters. Detailed Implementation

[0095] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention. Figure 1 As shown, Embodiment 1 of the present invention provides a photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling. In a preferred but non-limiting embodiment of the present invention, the method includes the following steps:

[0096] S1: Establish an energy management framework for photovoltaic producer-consumer clusters with electro-carbon coupling and a peak-shaving response operation mode;

[0097] The main components of the photovoltaic (PV) prosumer cluster energy management framework, which is coupled with carbon energy, include an Energy Sharing Provider (ESP) and the PV prosumer cluster. The ESP coordinates energy sharing within the PV prosumers. Each PV prosumer contains PV installations, and its electricity demand is primarily met by the output of these PV devices. If the PV output within the cluster is insufficient, electricity is purchased from the external grid; if there is excess PV output, the surplus electricity is fed into the grid. Each prosumer's power load includes movable loads and has automatic demand-side response capabilities. The PV prosumer's User Energy Management System (UEMS) is responsible for local optimization tasks and can decide on movable load arrangements for each prosumer. All users joining the alliance must register and be represented by an ESP to ensure efficient optimization.

[0098] Peak Shaving Response (ESP) Operation Mode: Photovoltaic power is the preferred power source for each photovoltaic (PV) prosumer. When PV power cannot meet electricity demand, PV prosumers will purchase electricity through the ESP. Conversely, when electricity demand is less than PV power output, surplus PV output will be shared with other smart buildings or fed back to the grid through the ESP. The ESP acts as an agent for all PV prosumers in the cluster and also as the EMS executor, ensuring collaborative cooperation among all components. The ESP is responsible for purchasing electricity from the grid and selling it to PV prosumers within the park. Furthermore, the ESP must ensure maximum utilization of PV within the prosumer cluster. The power system incentivizes users to change their shiftable load arrangements to transfer load from peak to off-peak periods. Each prosumer's electricity load includes shiftable load, and their electricity consumption decisions are based on grid electricity prices, dynamic carbon emission factors, and peak shaving compensation.

[0099] S2: Establish a basic model for photovoltaic producer-consumer clusters, including a fixed load model, a movable load model, and a movable load constraint and electricity utility model;

[0100] 1) Fixed load model

[0101] The fixed loads of photovoltaic (PV) power consumers (such as lights, televisions, refrigerators, and elevators) have non-adjustable power consumption times and high reliability requirements; therefore, they do not participate in demand response. In the event of a distribution network failure, priority should be given to ensuring power supply to fixed loads. The set / model of fixed loads for the i-th PV power consumer within a specific time period is as follows:

[0102] fi =[f i 1 ,…,f i h ,…,f i H ], i∈[1,2,…,n] (1)

[0103] In the formula: f i 1 f i h f i H Let be the fixed load of the i-th photovoltaic power consumer in the 1st, hth, and Hth time periods;

[0104] n represents the number of photovoltaic producers and consumers in the photovoltaic producer-consumer cluster.

[0105] 2) Transferable load model

[0106] The shiftable load consumption time of photovoltaic (PV) power consumers is adjustable, ensuring a continuous supply of power to the load within a certain time period. This is used for the temporal redistribution of power load within smart buildings for each PV power consumer. The set / model of the shiftable load for the i-th PV power consumer within a specific time period is:

[0107]

[0108] In the formula: Let be the transferable load of the i-th photovoltaic power consumer in the 1st, hth, and Hth time periods.

[0109] Assume the i-th photovoltaic producer-consumer owns K i For each controllable electrical device, the transferable load value of the i-th photovoltaic power consumer in the h-th time period is equal to the sum of the transferable load values ​​of all controllable electrical devices:

[0110]

[0111] 3) Transferable load constraints

[0112] The movable load for each time period should meet the following requirements:

[0113] If h∈[α] h ,β h ], must meet the following conditions:

[0114] like Must meet

[0115] In addition:

[0116]

[0117] In the formula: [α] h ,β h [This refers to any selectable transfer interval of the transferable load, i.e., any time period during which it can be transferred;]

[0118] These are the minimum and maximum values ​​of the load that the i-th photovoltaic power consumer can transfer in the h-th time period, respectively.

[0119] L i Let be the total portable load of the i-th photovoltaic producer-consumer across all time periods.

[0120] Among them, the transferable load is a variable, and the constraint is... Ensure that the total amount of load that can be moved for each user i remains constant throughout the day.

[0121] 4) Electricity Utility Model

[0122] Each photovoltaic (PV) producer-consumer has the ability to flexibly shift electrical loads. The demand response model, i.e., the electricity utility model, of the i-th PV producer-consumer can be expressed as:

[0123]

[0124] In the formula: ζ i The electricity preference coefficient for the i-th photovoltaic producer-consumer is set by the photovoltaic producer-consumer.

[0125] For the utility of the i-th photovoltaic producer-consumer;

[0126] Where, ζ i The larger the size, the higher the energy efficiency.

[0127] S3: Considering dynamic carbon emission intensity and the dynamic role of producers and consumers, and combining the fixed load model and the shiftable load model, construct a comprehensive energy purchase cost model for photovoltaic producers and consumers;

[0128] 1) Analysis of carbon trading mechanisms

[0129] Considering that a certain percentage of carbon allowances will be allocated to enterprises free of charge, and that enterprises can purchase more from the carbon trading market when they are short of allowances, and sell the excess allowances for profit when they have surplus allowances, this invention uses a baseline method to allocate initial carbon allowances free of charge, with the allowances obtained by the photovoltaic producer-consumer cluster related to its electricity purchases from the grid.

[0130] Photovoltaic producers and consumers receive free carbon emission allowances from purchasing electricity from the grid:

[0131]

[0132] In the formula: E i,gLδ represents the free carbon emission allowance obtained by the i-th photovoltaic power consumer from purchasing electricity from the grid in the h-th time period; δ is the carbon emission share per unit of electricity generated. Let be the amount of electricity purchased from the grid by the i-th photovoltaic power consumer in the h-th time period;

[0133] Actual carbon emissions from purchasing electricity from the grid:

[0134]

[0135] In the formula: Let be the carbon emissions of the i-th photovoltaic power consumer purchasing electricity from the grid in the h-th time period; Let represent the dynamic carbon emission intensity of the electricity purchased by the i-th photovoltaic producer-consumer during the h-th time period.

[0136] The dynamic carbon emission intensity calculation method for electricity purchases is as follows:

[0137]

[0138] In the formula: Let M be the carbon emission intensity of the region where the i-th photovoltaic producer-consumer is located during the h-th time period; M is the set of nodes contained in the region where the i-th photovoltaic producer-consumer is located, where each node contains several photovoltaic producers-consumers; Let node m be the load during the h-th time period; Let m be the carbon potential at node m.

[0139] 2) Establish a comprehensive energy purchase cost model that considers dynamic carbon emission intensity.

[0140] 2.1) Photovoltaic producer-consumer carbon cost considering dynamic carbon emission intensity:

[0141] Based on the aforementioned carbon trading mechanism, if a photovoltaic producer-consumer cluster purchases electricity from the grid, its corresponding carbon cost is:

[0142]

[0143] In the formula: The carbon cost of purchasing electricity from the grid during the h-th time period; ρ c This refers to the carbon price.

[0144] 2.2) Net photovoltaic power generation and consumption based on fixed load model and shiftable load model:

[0145] All PV devices in the park system adopt maximum power point tracking (MPPT) control. The predicted active power output of the ith photovoltaic power producer / consumer is... Treating the photovoltaic (PV) prosumer cluster as a whole, its system net load in time period h is the sum of the net loads of all PV prosumers. The net load of each ith PV prosumer in time period h is the difference between its total electrical load and PV output. A value greater than 0 indicates that PV output cannot meet the prosumer's load demand, requiring the purchase of electricity; a value less than 0 indicates that PV output can meet the prosumer's demand, requiring the sale of electricity to the grid. The net load of the ith PV prosumer in time period h is... for:

[0146]

[0147] 2.3) A photovoltaic producer-consumer integrated energy purchase cost model based on the aforementioned carbon cost and net load:

[0148] If the h-th time period That is, the i-th photovoltaic producer-consumer acts as a buyer during this period, and the overall energy purchase cost is... The overall energy purchase cost, taking into account dynamic carbon emission intensity, is:

[0149]

[0150] In the formula: Let be the total energy purchase cost for the i-th photovoltaic producer-consumer in the h-th time period; pe h Let be the time-of-use electricity price (i.e., the price at which electricity is purchased from the grid) for the h-th time period.

[0151] like That is, the i-th photovoltaic producer-consumer acts as a seller during this period, considering the overall energy purchase cost. For electricity sales revenue:

[0152]

[0153] In the formula: ft h This refers to the feed-in tariff (the price at which electricity is sold to the grid) for the h-th time period.

[0154] S4: Based on the electricity consumption efficiency model and the comprehensive energy purchase cost model, construct a photovoltaic producer-consumer peak shaving response comprehensive cost model that is coupled with carbon emissions.

[0155] This invention proposes a distributed peak-shaving interaction strategy for photovoltaic producer-consumer clusters to achieve peak-shaving response of photovoltaic producer-consumer clusters with electricity-carbon coupling:

[0156] To incentivize photovoltaic (PV) producers and consumers to participate in peak shaving response, the economic penalty for the i-th PV producer and consumer exceeding the limit during the h-th time period is... for:

[0157]

[0158] In the formula: Let be the peak shaving compensation price (yuan / kWh) for the i-th photovoltaic producer-consumer in the h-th time period.

[0159] Based on the coupling of electricity and carbon emissions, a comprehensive cost model for photovoltaic producer-consumer peak shaving response is established, taking into account factors such as electricity price, dynamic carbon emission intensity, electricity utility, and economic penalties.

[0160] 1) If the time period is h but:

[0161]

[0162] 2) If the time period is h but:

[0163]

[0164] Furthermore, each photovoltaic producer-consumer prioritizes internal energy sharing before engaging in electricity trading with the main power grid. Based on formulas (14) and (15), the objective function of the photovoltaic producer-consumer cluster, with the goal of minimizing system costs, can be obtained as follows:

[0165]

[0166] Where: TPRO h Let be the cost function of the photovoltaic producer-consumer cluster in the h-th time period.

[0167] S5: Based on the shiftable load constraint and the comprehensive cost model for peak shaving response, construct a photovoltaic (PV) producer-consumer (PCC) cluster peak shaving demand response model. Under the distributed peak shaving interaction strategy of the PCC cluster based on electricity-carbon coupling, solve for the PCC cluster peak shaving demand response strategy to achieve PCC cluster peak shaving demand response. This step is implemented based on the distributed peak shaving interaction strategy of the PCC cluster.

[0168] In practical applications, energy sharing service providers (ESPs) cannot directly control the electrical equipment of photovoltaic (PV) prosumers (SPs), and the privacy and security of each SP's information must be protected. Therefore, this invention proposes a distributed peak-shaving interaction strategy for PV SP clusters based on electro-carbon coupling. In the optimization process, the ESP and the energy management systems (EMS) of all PV SPs collaborate with each other. For example... Figure 2 As shown, the specific process includes the following steps:

[0169] (1) ESP sends grid electricity price, carbon price, dynamic carbon emission intensity and related parameter information to the EMS of all photovoltaic producers and consumers;

[0170] (2) Based on the electricity-carbon coupling, a local optimization is established for each photovoltaic producer-consumer EMS, taking into account electricity price, dynamic carbon emission intensity, peak shaving compensation, and electricity consumption utility, to obtain the desired result. In this step, photovoltaic producer-consumer i needs to solve the following optimization model (photovoltaic producer-consumer cluster peak-shaving demand response model):

[0171]

[0172] Each photovoltaic power consumer's EMS can then perform local optimization based on the models in formulas (14) and (15) to solve formula (17). In this way, the electricity consumption privacy information of other photovoltaic power consumers can be protected.

[0173] (3) Based on the movable load of the i-th photovoltaic producer-consumer obtained in step (2) The shiftable loads of each photovoltaic producer and consumer constitute the peak-shaving demand response strategy of the photovoltaic producer and consumer cluster.

[0174] (4) Further, based on the results obtained in step (2) In addition to the fixed load and photovoltaic output information of the i-th photovoltaic power consumer, EMS can calculate based on formula (10) And send it to ESP;

[0175] (5) ESP receives the net load of the i-th photovoltaic producer-consumer in the h-th time period. And calculate in:

[0176] (6) Combining with formula (10), it can be seen that the result obtained in step (5) Substituting into equation (16), the total operating cost of the photovoltaic producer-consumer cluster system can be calculated using equation (16). TPRO h ;

[0177] (7) The amount of electricity purchased from the power grid, the electricity price, and the carbon emission intensity are different before and after optimization. Based on formula (7), the carbon emissions before and after optimization are calculated respectively, and the carbon emission reduction of the system can be obtained by subtracting them.

[0178] Based on the above (4)-(7), it can be seen that the present invention obtains the product from each The peak-shaving demand response strategy of the photovoltaic producer-consumer cluster integrates a large number of producers and consumers with different capacities to form a photovoltaic producer-consumer cluster. This can significantly reduce the number of market players, reduce the total operating costs of market transactions and operation and maintenance management, and promote the consumption of renewable energy by introducing dynamic carbon emission intensity. Each photovoltaic producer-consumer can effectively perceive the peak-valley difference of carbon emission intensity and actively adjust its electricity consumption arrangements to improve the net load curve and reduce the system's carbon emissions.

[0179] In summary, the present invention provides a photovoltaic producer-consumer cluster peak shaving demand response method based on electricity-carbon coupling. First, it proposes an energy management framework and peak shaving response operation mode for photovoltaic producer-consumer clusters based on electricity-carbon coupling. Second, based on electricity-carbon coupling, it establishes a low-carbon optimization model for photovoltaic producer-consumer clusters that considers dynamic carbon emission intensity (Equation (8)), peak shaving response (Equation (13)), and electricity utility (Equation (5)). Dynamic carbon emission intensity is introduced into the peak shaving response mechanism to allow photovoltaic producer-consumers to effectively perceive the peak-valley difference in carbon emission intensity and guide them to actively reduce carbon emissions. Finally, through distributed peak shaving interaction of photovoltaic producer-consumer clusters, the system's carbon emissions are effectively reduced.

[0180] Embodiment 2 of the present invention provides a photovoltaic producer-consumer cluster peak-shaving demand response system based on electro-carbon coupling, comprising:

[0181] The management framework and operation mode construction module is used to establish an energy management framework and peak shaving response operation mode for photovoltaic producer-consumer clusters with electricity-carbon coupling.

[0182] The basic model building module is used to establish a basic model of a photovoltaic producer-consumer cluster, including a fixed load model, a movable load model, and movable load constraints and electricity consumption efficiency models.

[0183] The integrated energy purchase cost model construction module is used to consider dynamic carbon emission intensity and dynamic roles of producers and consumers, and to construct a photovoltaic producer-consumer integrated energy purchase cost model in combination with the fixed load model and the shiftable load model.

[0184] The peak shaving response comprehensive cost model module is used to construct an electricity-carbon coupled photovoltaic producer-consumer peak shaving response comprehensive cost model based on the electricity utility model and the comprehensive energy purchase cost model.

[0185] The demand response module is used to construct a photovoltaic producer-consumer cluster peak shaving demand response model based on the shiftable load constraint and peak shaving response comprehensive cost model. Under the distributed peak shaving interaction strategy of photovoltaic producer-consumer cluster based on electricity-carbon coupling, the peak shaving demand response strategy of photovoltaic producer-consumer cluster is solved to realize the peak shaving demand response of photovoltaic producer-consumer cluster.

[0186] Embodiment 3 of the present invention also provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0187] Embodiment 4 of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0188] The beneficial effects of this invention are compared with those of the prior art:

[0189] This invention is based on electric-carbon coupling, incorporating shiftable loads into the optimization of photovoltaic producer-consumer clusters, and considering factors such as dynamic carbon emission intensity, peak shaving response, and electricity consumption efficiency to carry out low-carbon optimization of photovoltaic producer-consumer clusters. The model is also more accurate and practical, promoting energy-carbon interaction and the formation of low-carbon mechanisms, which helps to achieve energy conservation and carbon reduction and build a clean and low-carbon system.

[0190] This invention integrates a large number of photovoltaic prosumers with different capacities to form a photovoltaic prosumer cluster, which can significantly reduce the number of market players and reduce the total operating costs of market transactions and operation and maintenance management.

[0191] This invention introduces dynamic carbon emission intensity, which allows photovoltaic producers and consumers to effectively perceive the peak-valley difference in carbon emission intensity and guides them to actively reduce carbon emissions, thereby achieving distributed peak shaving interaction among photovoltaic producers and consumers and reducing the overall carbon emissions of the system.

[0192] This invention proposes a distributed peak-shaving interaction strategy for photovoltaic producer-consumer clusters, which further taps the carbon reduction potential of photovoltaic producer-consumers, promotes the consumption of renewable energy, and effectively reduces the carbon emissions of the system.

[0193] This invention develops a peak-shaving demand response strategy for photovoltaic producer-consumer clusters, which can be applied in actual industrial parks to achieve energy-carbon balance, promote the realization of dual carbon emissions, and facilitate the clean and low-carbon transformation of the energy system.

[0194] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0195] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0196] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0197] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do 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 photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling, characterized in that, The method includes: Establish an energy management framework for photovoltaic producer-consumer clusters with electro-carbon coupling and a peak-shaving response operation mode; Based on the aforementioned photovoltaic producer-consumer cluster energy management framework and peak-shaving response operation mode with electro-carbon coupling, a basic model of photovoltaic producer-consumer cluster is established, including a fixed load model, a shiftable load model, and a shiftable load constraint and electricity utility model. Considering dynamic carbon emission intensity and the dynamic role of producers and consumers, and combining the fixed load model and the shiftable load model, a comprehensive energy purchase cost model for photovoltaic producers and consumers is constructed. Based on the electricity utility model and the comprehensive energy purchase cost model, a photovoltaic producer-consumer peak shaving response comprehensive cost model coupled with carbon emissions is constructed. Based on the shiftable load constraint and the peak shaving response comprehensive cost model, a photovoltaic producer-consumer cluster peak shaving demand response model is constructed. Under the distributed peak shaving interaction strategy of photovoltaic producer-consumer cluster based on electricity-carbon coupling, the peak shaving demand response strategy of photovoltaic producer-consumer cluster is solved to realize the peak shaving demand response of photovoltaic producer-consumer cluster.

2. The photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1, characterized in that: The energy management framework for the electro-carbon coupled photovoltaic producer-consumer cluster includes an energy-sharing service provider (ESP) and a photovoltaic producer-consumer cluster, where the ESP coordinates energy sharing among photovoltaic producer-consumers within the park. The peak shaving response operation mode is as follows: the power demand of photovoltaic producers and consumers is first met by the output of photovoltaic devices. If the output is insufficient, energy is purchased from the grid through ESP. If the output is excessive, the excess power is shared through ESP. The power load of each photovoltaic producer and consumer includes shiftable loads and has the ability to automatically respond to demand. Based on the peak shaving demand, the local optimization of producers and consumers is realized through EMS, and the shiftable load arrangement of each producer and consumer is decided.

3. The photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1, characterized in that: The fixed load model is as follows: In the formula: Let H be the fixed load of the i-th photovoltaic power consumer in the 1st, hth, and Hth time periods, where H is the total number of time periods in a day; n represents the number of photovoltaic producers and consumers in the photovoltaic producer-consumer cluster; The transferable load model is as follows: In the formula: Let be the transferable load of the i-th photovoltaic power consumer in the 1st and Hth time periods; Let K be the portable load of the i-th photovoltaic power consumer in the h-th time period, where K i Let be the total number of controllable electrical devices owned by the i-th photovoltaic producer-consumer. This represents the transferable load value of the k-th controllable electrical device within the h-th time period.

4. A photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1 or 3, characterized in that: The transferable load constraint is: If h∈[α] h ,β h ],but like but as well as In the formula: [α] h ,β h [This refers to any selectable translation interval of the transferable load;] Let be the portable load of the i-th photovoltaic power consumer in the h-th time period; These are the minimum and maximum values ​​of the load that the i-th photovoltaic power consumer can transfer in the h-th time period, respectively. L i The total portable load of photovoltaic power consumers i across all time periods; H represents the total number of time periods in a day.

5. A photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1 or 3, characterized in that: The electricity consumption efficiency model is as follows: In the formula: The electricity consumption efficiency of photovoltaic power generation and consumption; ζ i Let i be the electricity preference coefficient for photovoltaic power consumer i. Let be the fixed load of the i-th photovoltaic power consumer in the h-th time period; Let be the transferable load of the i-th photovoltaic producer-consumer in the h-th time period.

6. The photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1, characterized in that: The aforementioned model, which considers dynamic carbon emission intensity and the dynamic roles of producers and consumers, and combines the fixed load model and the shiftable load model, constructs a comprehensive energy purchase cost model for photovoltaic producers and consumers, including: Based on the different dynamic roles of producers and consumers, the comprehensive energy purchase cost models are established as follows: like Then, the i-th photovoltaic producer-consumer is a buyer in the h-th time period, and the comprehensive energy purchase cost model is as follows: like Then, the i-th photovoltaic producer-consumer is a seller in the h-th time period, and the comprehensive energy purchase cost model is as follows: In the formula: Let be the total energy purchase cost for the i-th photovoltaic producer-consumer in the h-th time period; Let be the net load of the i-th photovoltaic power consumer in the h-th time period; PE h The time-of-use electricity price for the grid in the h-th time period; Let be the fixed load of the i-th photovoltaic power consumer in the h-th time period; Let be the portable load of the i-th photovoltaic power consumer in the h-th time period; Let be the predicted active power output of the photovoltaic power source for the i-th photovoltaic producer-consumer; ρ c δ represents the carbon price; δ represents the carbon emission share per unit of electricity generated. The dynamic carbon emission intensity of the electricity purchased by the i-th photovoltaic producer-consumer in the h-th time period; Let be the amount of electricity purchased from the grid by the i-th photovoltaic power consumer in the h-th time period; ft h Let be the on-grid electricity price for the h-th time period.

7. The photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 6, characterized in that: The net load of the i-th photovoltaic producer-consumer in the h-th time period is: In the formula: n is the number of photovoltaic producers and consumers in the photovoltaic producer-consumer cluster.

8. A photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 6 or 7, characterized in that: The formula for calculating the dynamic carbon emission intensity of the electricity purchased by the i-th photovoltaic producer-consumer in the h-th time period is: In the formula: Let M be the carbon emission intensity of the region where the i-th photovoltaic producer-consumer is located during the h-th time period; M is the set of nodes contained in the region where the i-th photovoltaic producer-consumer is located, where each node contains several photovoltaic producers-consumers; Let m be the load of node m in the h-th time period; Let m be the carbon potential at node m.

9. A photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 6, characterized in that: The comprehensive cost model for peak shaving response is as follows: like but like but In the formula: Let $\frac{i}{i}$ be the total cost of peak shaving response for the i-th photovoltaic power consumer in the $h$ time period in the electro-carbon coupling process. PE h The time-of-use electricity price for the grid in the h-th time period; The electricity consumption efficiency of photovoltaic power generation and consumption; ζ i Let i be the electricity preference coefficient for photovoltaic power consumer i. Let be the peak shaving compensation price for the i-th photovoltaic producer / consumer in the h-th time period.

10. A photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1, characterized in that: The photovoltaic producer-consumer cluster peak-shaving demand response model is as follows: In the formula: Let $\frac{i}{i}$ be the total cost of peak shaving response for the i-th photovoltaic power consumer in the $h$ time period in the electro-carbon coupling process. [α h ,β h [This refers to any selectable translation interval of the transferable load;] Let be the portable load of the i-th photovoltaic power consumer in the h-th time period; These are the minimum and maximum values ​​of the load that the i-th photovoltaic power consumer can transfer in the h-th time period, respectively. L i This represents the total portable load of photovoltaic power consumers (i) across all time periods.

11. The photovoltaic producer-consumer cluster peak-shaving demand response method based on electro-carbon coupling according to claim 1, characterized in that: The process of solving for the peak-shaving demand response strategy of the photovoltaic producer-consumer cluster under the distributed peak-shaving interaction strategy based on electro-carbon coupling includes: (1) ESP sends grid electricity price, carbon price, and dynamic carbon emission intensity information to the EMS of all photovoltaic producers and consumers; (2) Each photovoltaic producer-consumer EMS performs local optimization to solve the peak-shaving demand response model of the photovoltaic producer-consumer cluster and obtain the movable load of the photovoltaic producer-consumer. (3) The shiftable loads of each photovoltaic producer and consumer constitute the peak-shaving demand response strategy of the photovoltaic producer and consumer cluster.

12. A photovoltaic producer-consumer cluster peak-shaving demand response system based on electro-carbon coupling, utilizing the method described in any one of claims 1-11, characterized in that, The system includes: The management framework and operation mode construction module is used to establish an energy management framework and peak shaving response operation mode for photovoltaic producer-consumer clusters with electricity-carbon coupling. The basic model building module is used to establish a basic model of a photovoltaic producer-consumer cluster, including a fixed load model, a movable load model, and movable load constraints and electricity consumption efficiency models. The integrated energy purchase cost model construction module is used to consider dynamic carbon emission intensity and dynamic roles of producers and consumers, and to construct a photovoltaic producer-consumer integrated energy purchase cost model by combining the fixed load model and the movable load model. The peak shaving response comprehensive cost model module is used to construct an electricity-carbon coupled photovoltaic producer-consumer peak shaving response comprehensive cost model based on the electricity utility model and the comprehensive energy purchase cost model. The demand response module is used to construct a photovoltaic producer-consumer cluster peak shaving demand response model based on the shiftable load constraint and the peak shaving response comprehensive cost model. Under the distributed peak shaving interaction strategy of photovoltaic producer-consumer cluster based on electricity-carbon coupling, the peak shaving demand response strategy of photovoltaic producer-consumer cluster is solved to realize the peak shaving demand response of photovoltaic producer-consumer cluster.

13. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-11.

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