Distributed energy storage peak regulation heat supply control method and related device

Abstract

The invention discloses a peak regulation heat supply control method for distributed energy storage and a related device. The method comprises the following steps: carrying out modular energy storage unit networking; acquiring state information of each energy storage unit; the optimal charging and discharging power of each energy storage unit is predicted according to the state information of each energy storage unit, a heat storage and electricity storage capacity distribution scheme is generated according to the optimal charging and discharging power of each energy storage unit, and a control instruction is generated according to the heat storage and electricity storage capacity distribution scheme; and controlling each energy storage unit to operate according to the control instruction. The method and the related device can solve the problems of response delay and insufficient energy efficiency coupling in the prior art.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed energy storage regulation, and relates to a peak shaving and heating control method for distributed energy storage and related devices. Background Art

[0002] With the transformation of the global energy structure and the rapid development of new energy technologies, distributed energy storage technology, as an important part of the energy transformation process, is gradually receiving wide attention and application. Distributed energy storage technology stores the electric energy generated by green energy such as photovoltaic and wind power and releases it when needed, effectively solving the problems of randomness and volatility of renewable energy power generation, and improving the energy utilization efficiency and reliability. During the winter heating season, due to low temperatures and large heating demands, the power system faces huge peak shaving pressures. Traditional heating methods often rely on fossil fuels, resulting in not only high energy consumption but also the emission of a large amount of pollutants, causing serious impacts on the environment. At the same time, as the proportion of new energy connected to the power grid continues to increase, the demand for energy storage in the power system is also increasing day by day.

[0003] Distributed energy storage technology has shown great potential in peak shaving and heating. By using energy storage devices to store electric energy during low power demand periods and release electric energy during high power demand periods, it can effectively balance the load fluctuations of the power grid and improve the operation efficiency and stability of the power grid. In addition, distributed energy storage technology can also be combined with the heating system to achieve the thermal conversion and storage of electric energy, providing a stable and reliable heat source for heating.

[0004] With the large-scale access of renewable energy and the electrification transformation of the heating system, the existing peak shaving technologies face the following bottlenecks:

[0005] 1. Response lag problem: Traditional centralized energy storage relies on centralized scheduling, and communication delays result in the inability to quickly respond to the power fluctuations of distributed photovoltaic / wind power.

[0006] 2. Insufficient energy efficiency coupling: The heating system and the electricity storage equipment operate independently, resulting in low thermal - electrical conversion efficiency. Summary of the Invention

[0007] The purpose of the present invention is to overcome the above - mentioned disadvantages of the existing technology and provide a peak shaving and heating control method for distributed energy storage and related devices, which can solve the problems of response lag and insufficient energy efficiency coupling in the existing technology.

[0008] To achieve the above - mentioned purpose, the present invention discloses a peak shaving and heating control method for distributed energy storage, including:

[0009] Conduct modular energy storage unit networking;

[0010] Obtain the status information of each energy storage unit;

[0011] Predict the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generate a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, and generate a control instruction according to the heat storage and electricity storage capacity allocation plan;

[0012] Control the operation of each energy storage unit according to the control instruction.

[0013] A further improvement of the peak shaving and heat supply control method for the distributed energy storage according to the present invention lies in:

[0014] Further, the energy storage unit includes a heat storage device, an electricity storage device, an edge controller and a communication module, and the edge controller is connected to the communication module, the heat storage device and the electricity storage device.

[0015] Further, the status information of each energy storage unit includes thermoelectric status data, external environment data and user demand data.

[0016] Further, the predicting the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, and generating a control instruction according to the heat storage and electricity storage capacity allocation plan includes:

[0017] Use the short-term optimization layer to predict the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit by using a model;

[0018] Generate a heat storage and electricity storage capacity allocation plan through the long-term optimization layer according to the prediction result of the short-term optimization layer;

[0019] Generate a control instruction through the real-time control layer according to the heat storage and electricity storage capacity allocation plan, and the control instruction is used to adjust the valve opening of the heat storage device and the output power of the electricity storage device through closed-loop feedback.

[0020] Further, it further includes: when detecting an energy storage unit or communication failure, dynamically switching to an adjacent energy storage unit compensation mode or a local autonomy strategy.

[0021] Further, the process of the local autonomy strategy is:

[0022] Calculate the compensation amount P comp,k ; Compensate the faulty energy storage unit with the compensation amount P comp,k where the compensation amount P comp,k is:

[0023]

[0024] where m is the total number of online units participating in the compensation; is the distance between the faulty unit and the online unit i, adjusted by the attenuation factor n; is the distance between the faulty unit and the compensation unit k, adjusted by the attenuation factor n; P loss is the power lost by the faulty unit.

[0025] Furthermore, it also includes: recording the peak shaving contribution data of each energy storage unit through the blockchain; dynamically allocating peak shaving benefits based on the contribution weight, and the weight is:

[0026]

[0027] where W i is the peak shaving benefit weight of the energy storage unit i; α is the weight coefficient of the power regulation amount; ΔP i is the power regulation amount of the energy storage unit i; β is the weight coefficient of the response time; γ is the attenuation coefficient of the response time; t response,i is the response time of the energy storage unit i.

[0028] The present invention discloses a peak shaving and heat supply control system for distributed energy storage, including:

[0029] A networking module for networking modular energy storage units;

[0030] An acquisition module for acquiring the status information of each energy storage unit;

[0031] A generation module for predicting the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, and generating a control instruction according to the heat storage and electricity storage capacity allocation plan;

[0032] A control module for controlling the operation of each energy storage unit according to the control instruction.

[0033] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the peak shaving and heat supply control method for distributed energy storage are implemented.

[0034] The present invention discloses a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the peak shaving and heat supply control method for distributed energy storage are implemented.

[0035] The present invention has the following beneficial effects:

[0036] When the peak shaving and heat supply control method and related devices of the distributed energy storage described in the present invention are specifically operated, they adopt a distributed approach to form a modular energy storage unit network. Statistical calculations are performed based on the status information of each energy storage unit to generate control instructions, and then separate controls are carried out to solve the problems of response hysteresis and insufficient energy efficiency coupling in the prior art.

[0037] Furthermore, the present invention significantly improves the performance of the distributed energy storage peak shaving and heat supply system through modular energy storage units, hierarchical collaborative optimization control, and blockchain trusted recording mechanism. First, edge computing and FPGA acceleration shorten the response speed, with a significant improvement compared to traditional centralized control. Second, the thermoelectric coupling model increases the comprehensive energy efficiency utilization rate, reduces the peak-valley difference, and the blockchain technology ensures the transparency of the contribution degree and improves the user participation rate. In addition, the fault self-healing mechanism restores heat supply within 30 seconds, improving the system reliability. Compared with the prior art, the present invention has achieved breakthroughs in dynamic response, multi-energy collaboration, and fault tolerance, providing an efficient solution for the high-proportion grid connection of renewable energy. Brief Description of the Drawings

[0038] The specification drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0039] Figure 1 It is the flowchart of the method of the present invention. Detailed Embodiments

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0041] In the description of the present invention, it should be understood that the terms "include" and "comprise" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0042] It should also be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification and claims of the present invention, unless the context clearly indicates otherwise, the singular forms of "a", "an", and "the" are intended to include the plural forms.

[0043] It should be further understood that the term "and / or" as used in the specification and appended claims of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. For example, A and / or B can represent three cases: A exists alone, A and B exist simultaneously, and B exists alone. Additionally, in the present invention, the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0044] It should be understood that although terms such as first, second, third, etc. may be used to describe preset ranges in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range can also be referred to as the second preset range, and similarly, the second preset range can also be referred to as the first preset range.

[0045] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)".

[0046] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0047] Various structural schematic diagrams according to the disclosed embodiments of the present invention are shown in the drawings. These figures are not drawn to scale, where for the purpose of clear expression, some details are enlarged and some details may be omitted. The shapes of various regions and layers shown in the figures and their relative sizes and positional relationships are only exemplary. In practice, there may be deviations due to manufacturing tolerances or technical limitations, and those skilled in the art can design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0048] Embodiment 1

[0049] Reference Figure 1 , the peak shaving and heat supply control method of the distributed energy storage described in the present invention includes the following steps:

[0050] 1) Networking of modular energy storage units;

[0051] Deploy a number of distributed energy storage units, each energy storage unit includes a heat storage device, an electricity storage device, an edge controller and a communication module, and the edge controller is connected to the communication module, the heat storage device and the electricity storage device through a standardized interface.

[0052] 2) Dynamic acquisition of multi-source data;

[0053] Real-time collect the status information of each energy storage unit, the status information includes thermoelectric status data, external environment data and user demand data, and perform data fusion processing on the data.

[0054] 3) Hierarchical collaborative optimization control;

[0055] It includes a long-term optimization layer, a short-term optimization layer and a real-time control layer. Among them, the short-term optimization layer is used to use the model to predict the optimal charge and discharge power of each energy storage unit according to the collected data; the long-term optimization layer is used to generate a heat storage and electricity storage capacity allocation plan according to the prediction results of the short-term optimization layer, and the real-time control layer is used to adjust the valve opening of the heat storage device and the output power of the electricity storage device through closed-loop feedback according to the heat storage and electricity storage capacity allocation plan.

[0056] 4) Decentralized scheduling execution:

[0057] Send the control instructions output by the real-time control layer to the edge controller for execution, and at the same time record the peak shaving contribution data of each energy storage unit to the blockchain.

[0058] 5) Fault self-healing processing;

[0059] When detecting an energy storage unit or communication failure, dynamically switch to the adjacent energy storage unit compensation mode or the local autonomous strategy.

[0060] In step 1), it also includes: after the energy storage unit is powered on, it automatically registers its identity in the blockchain network; establish a data channel with adjacent energy storage units and the regional coordination server through the wireless communication module.

[0061] The data fusion processing in step 2) includes: performing unit standardization on the thermal power data and the electric power data to generate a unified energy efficiency index; using a filtering algorithm to eliminate sensor noise; smoothing data fluctuations through the time window sliding average method.

[0062] In step 3), in the long-term optimization layer, with the goal of minimizing the energy consumption cost and the heat storage temperature range and the SOC limit of the electrical energy storage as the constraint conditions, a heat storage and electrical energy storage capacity allocation scheme is generated; in the short-term optimization layer, a thermal-electric coupling conversion coefficient is introduced in the model predictive control to achieve the coordinated scheduling of multiple energy flows.

[0063] In step 4), the blockchain records the peak shaving contribution data of each energy storage unit. The peak shaving contribution data includes automatically calculating the peak shaving amount and the response speed index of each unit by designing a smart contract; it also includes dynamically allocating the peak shaving income based on the contribution weight. The weight calculation formula is:

[0064]

[0065] where W i is the peak shaving income weight of unit i; α is the weight coefficient of the power regulation amount, reflecting the impact of power change on the income; ΔP i is the power regulation amount of unit i, used to represent the magnitude of the actual power change; β is the weight coefficient of the response time, used to reflect the impact of the response speed on the income; γ is the decay coefficient of the response time, used to control the sensitivity of the impact of the response time on the income; t response,i is the response time of unit i, used to represent the time from receiving the peak shaving signal to the actual response.

[0066] Among them, the process of the fault self-healing process in step 5) includes: when it is detected that a unit is offline, the compensation power is allocated based on the geographical proximity relationship. Among them, the compensation amount is:

[0067]

[0068] where P comp,k is the power allocated to the compensation unit k; m is the total number of online units participating in the compensation; is the distance between the faulty unit and the online unit i, adjusted by the attenuation factor n; is the distance between the faulty unit and the compensation unit k, adjusted by the attenuation factor n; P loss is the power lost by the faulty unit.

[0069] Among them, the fault self-healing process also includes: when the communication is interrupted, switch to the pre-stored constant heat storage temperature mode and the constant voltage output mode of the electrical energy storage.

[0070] Through a peak shaving and heat supply control method for distributed energy storage designed by the present invention, in actual application, the test results are shown in Table 1 as follows:

[0071] Table 1

[0072]

[0073]

[0074] In summary, through the modular energy storage unit, hierarchical collaborative optimization control, and blockchain trusted recording mechanism, the present invention significantly improves the performance of the distributed energy storage peak shaving and heat supply system. First, edge computing and FPGA acceleration shorten the response time, which is a significant improvement compared to traditional centralized control. Second, the thermoelectric coupling model increases the comprehensive energy efficiency utilization rate and reduces the peak-valley difference. The blockchain technology ensures the transparency of contributions. In addition, the fault self-healing mechanism restores heat supply within 30 seconds, improving the system reliability. Compared with the prior art, the present invention has achieved breakthroughs in dynamic response, multi-energy collaboration, and fault tolerance, providing an efficient solution for the grid connection of a high proportion of renewable energy.

[0075] Embodiment 2

[0076] The peak shaving and heat supply control system of the distributed energy storage described in the present invention includes:

[0077] A networking module for networking modular energy storage units;

[0078] An acquisition module for acquiring the status information of each energy storage unit;

[0079] A generation module for predicting the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation scheme according to the optimal charge and discharge power of each energy storage unit, and generating a control instruction according to the heat storage and electricity storage capacity allocation scheme;

[0080] A control module for controlling the operation of each energy storage unit according to the control instruction.

[0081] The division of modules in the embodiments of the present application is illustrative, merely a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of the present application, each functional module may be integrated in a processor, may exist independently physically, or two or more modules may be integrated in one module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0082] Embodiment 3

[0083] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the peak shaving and heat supply control method for distributed energy storage are implemented. For example, it includes: networking modular energy storage units; obtaining the status information of each energy storage unit; predicting the optimal charge and discharge power of each energy storage unit based on the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, generating a control instruction according to the heat storage and electricity storage capacity allocation plan; and controlling the operation of each energy storage unit according to the control instruction. Among them, the memory may include internal memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk memory, etc.; the processor, network interface, and memory are interconnected through an internal bus, and this internal bus can be an Industry Standard Architecture bus, a Peripheral Component Interconnect standard bus, an Extended Industry Standard Architecture bus, etc., and the bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include internal memory and non-volatile memory, and provide instructions and data to the processor.

[0084] Embodiment 4

[0085] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the peak shaving and heat supply control method for distributed energy storage are implemented. For example, it includes: networking modular energy storage units; obtaining the status information of each energy storage unit; predicting the optimal charge and discharge power of each energy storage unit based on the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, generating a control instruction according to the heat storage and electricity storage capacity allocation plan; and controlling the operation of each energy storage unit according to the control instruction. Specifically, the computer-readable storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. The volatile memory can include random access memory and / or cache memory, etc. The non-volatile memory can include read-only memory, hard disk, flash memory, optical disc, magnetic disk, etc.

[0086] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0087] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, as well as the combination of flows and / or blocks in the flowchart and / or block diagram. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in the process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0088] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the functions specified in the process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0089] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0090] Those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and the disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include well-known common general knowledge or conventional technical means in the technical field not disclosed in the present invention. The specification and the embodiments are only regarded as exemplary, and the true scope and spirit of the present invention are pointed out by the following claims.

[0091] It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

[0092] The above are only the preferred embodiments of the present invention, and do not impose any limitations on the present invention. Any simple modifications, changes, and equivalent structural changes made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A peak shaving and heat supply control method for distributed energy storage, characterized in that, Including: Conduct modular energy storage unit networking; Obtain the status information of each energy storage unit; Predict the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generate a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, and generate a control instruction according to the heat storage and electricity storage capacity allocation plan; Control the operation of each energy storage unit according to the control instruction.

2. The peak shaving and heat supply control method for distributed energy storage according to claim 1, characterized in that, The energy storage unit includes a heat storage device, an electricity storage device, an edge controller and a communication module, and the edge controller is connected to the communication module, the heat storage device and the electricity storage device.

3. The peak shaving and heat supply control method for distributed energy storage according to claim 1, wherein The status information of each energy storage unit includes thermoelectric status data, external environment data and user demand data.

4. The peak shaving and heat supply control method for distributed energy storage according to claim 2, wherein, The predicting the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, and generating a control instruction according to the heat storage and electricity storage capacity allocation plan includes: Through the short-term optimization layer, according to the status information of each energy storage unit, use the model to predict the optimal charge and discharge power of each energy storage unit; Through the long-term optimization layer, generate a heat storage and electricity storage capacity allocation plan according to the prediction results of the short-term optimization layer; Through the real-time control layer, generate a control instruction according to the heat storage and electricity storage capacity allocation plan, and the control instruction is used to adjust the valve opening of the heat storage device and the output power of the electricity storage device through closed-loop feedback.

5. The peak shaving and heat supply control method for distributed energy storage according to claim 1, wherein It also includes: When detecting an energy storage unit or communication failure, dynamically switch to the adjacent energy storage unit compensation mode or the local autonomy strategy.

6. The peak shaving and heat supply control method for distributed energy storage according to claim 5, characterized in that, The process of the local autonomy strategy is: Calculate the compensation amount P comp,k ; Compensate the faulty energy storage unit with the compensation amount P comp,k , where the compensation amount P comp,k is: Where m is the total number of online units participating in compensation; is the distance between the faulty unit and the online unit i, adjusted by the attenuation factor n; is the distance between the faulty unit and the compensation unit k, adjusted by the attenuation factor n; P loss is the power lost by the faulty unit.

7. The peak shaving and heat supply control method for distributed energy storage according to claim 2, wherein It also includes: Record the peak shaving contribution data of each energy storage unit through the blockchain; dynamically allocate the peak shaving income based on the contribution degree weight, and the weight is: Among them, W i is the peak shaving revenue weight of energy storage unit i; α is the weight coefficient of the power regulation amount; ΔP i is the power regulation amount of energy storage unit i; β is the weight coefficient of the response time; γ is the decay coefficient of the response time; t response,i is the response time of energy storage unit i.

8. A peak shaving and heat supply control system for distributed energy storage, characterized in that, Including: A networking module for conducting modular energy storage unit networking; An acquisition module for obtaining the status information of each energy storage unit; A generation module for predicting the optimal charge and discharge power of each energy storage unit according to the status information of each energy storage unit, generating a heat storage and electricity storage capacity allocation plan according to the optimal charge and discharge power of each energy storage unit, and generating a control instruction according to the heat storage and electricity storage capacity allocation plan; A control module for controlling the operation of each energy storage unit according to the control instruction.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it realizes the steps of the peak shaving and heat supply control method of the distributed energy storage as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it realizes the steps of the peak shaving and heat supply control method of the distributed energy storage as described in any one of claims 1-7.

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