Demand response regulation and control system and method based on intelligent measurement terminal

Abstract

The invention discloses a demand response regulation and control system and method based on an intelligent measurement terminal, and belongs to the technical field of demand response regulation and control. The system comprises a master station, an intelligent measurement terminal, a terminal device interface and a source load device. The method comprises the steps that a comprehensive energy system model is established, a demand response scheduling model with the optimal system operation cost is established, a master station obtains collection information reported by an intelligent measurement terminal and third-party platform data to generate an optimal demand response scheduling strategy and issues the optimal demand response scheduling strategy to the intelligent measurement terminal, and controlled equipment is regulated and controlled through a terminal equipment interface. According to the invention, the energy demand of the energy consumption end and the output condition of the energy supply end are collected in real time through the intelligent measurement terminal, the demand response scheduling strategy with the optimal operation cost of the integrated energy system is generated in combination with the third-party platform data, and the operation states of the distributed energy and the flexible load are cooperatively controlled through the intelligent measurement terminal. And an economic, energy-saving and environment-friendly optimal energy utilization plan is formulated and implemented.

Description

Technical Field

[0001] The present invention belongs to the technical field of demand response regulation, and particularly relates to a demand response regulation system and method based on an intelligent measurement terminal. Background Art

[0002] With the development of the economy, the demand for fossil energy is increasing day by day, and the problems of energy crisis and environmental pollution are becoming increasingly serious. Therefore, promoting the use of renewable new energy has become an urgent energy goal that countries need to advance. With the development of new energy technologies, the energy structure has been continuously enriched, and building a new integrated energy system suitable for the high proportion of new energy access and realizing a low-carbon, clean, diversified, and intelligent measurement energy structure system has become the focus. Integrated energy management integrates advanced intelligent energy technologies and combines Internet technologies to coordinately control the operation of large-scale energy sources, integrated energy networks, and load ends in large regions, achieving the adjustment of the energy structure from traditional non-renewable fossil energy to renewable clean energy.

[0003] Nowadays, the demand response regulation of integrated energy systems is mostly in the theoretical stage. There is no unified data interface for the operation states and operation data of different devices in the system, and there is no specific implementation plan for the execution of regulation strategies. Therefore, it is necessary to invent a demand response system and method based on an intelligent measurement terminal, which can generate an energy optimization scheduling strategy by real-time collecting the energy demand of the user side, the real-time electricity price of the power supply side, and the output of distributed energy, and coordinately control the operation states of distributed energy and flexible loads, and formulate the most economical, energy-saving, and environmentally friendly optimal energy consumption plan. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a demand response regulation system and method based on an intelligent measurement terminal, which can coordinately control the operation states of distributed energy and flexible loads based on the intelligent measurement terminal.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A demand response regulation system and method based on an intelligent measurement terminal. The system includes a master station, an intelligent measurement terminal, a terminal device interface, and source-load devices. The master station establishes a connection with the intelligent measurement terminal. The master station obtains the operation data of the source-load devices through the intelligent measurement terminal, and obtains weather data, real-time electricity price data, and demand response index data by accessing a third-party platform. The master station generates a demand response regulation strategy and issues it to the intelligent measurement terminal. The intelligent measurement terminal is connected to the terminal device interface and the master station. The intelligent measurement terminal receives the operation data of the source-load devices collected by the terminal device interface and uploads it to the master station. The intelligent measurement terminal receives the demand response regulation strategy issued by the master station and controls the operation status of the source-load devices through the terminal device interface according to the regulation strategy. The terminal device interface is connected to the intelligent measurement terminal and the source-load devices. The terminal device interface provides a standardized interface. The source-load devices are connected to the intelligent measurement terminal through the terminal device interface. The terminal device interface collects data and controls the operation status of the source-load devices. The source-load devices include source-side devices and load-side devices, which are energy supply devices and load energy-consuming devices respectively.

[0007] A demand response regulation system and method based on an intelligent measurement terminal. The method includes the following steps:

[0008] Step 1: Establish a comprehensive energy system model that couples distributed energy devices and flexible load energy-consuming devices.

[0009] Step 2: Based on Step 1, establish a demand response scheduling model with the optimal operation cost of the comprehensive energy system.

[0010] The demand response scheduling model includes a multi-objective optimization function consisting of the minimum operation cost M oc 、the minimum carbon emission cost M ce 、the minimum flexible load response demand subsidy cost M DR and constraint conditions.

[0011] The multi-objective optimization function is expressed as:

[0012]

[0013]

[0014]

[0015] Among them, is the electricity purchase volume, is the electricity purchase price, is the electricity sales volume, is the electricity sales price, is the gas purchase volume, is the gas purchase price, C op is the equipment maintenance cost, ε is the carbon treatment cost, β e and βg are the equivalent emission coefficients for electricity and gas purchases respectively, σ1 and σ2 are the basic compensation costs and comfort compensation costs for transferable loads respectively, and T max is the maximum transferable time interval, and p(t, t′) is the load quantity transferred from time t to time t′. is the interrupted load quantity of the interruptible load, is the compensation price for the interrupted load.

[0016] The multi-objective optimization problem is transformed into a single-objective optimization problem using the linear weighted method:

[0017] F = min(k1M oc + k2M ce + k3M DR )

[0018] where k1, k2, and k3 are the weight coefficients of the operating cost, carbon emission cost, and flexible load response demand subsidy cost respectively.

[0019] The constraint conditions include: energy flow supply-demand balance constraint, distributed energy output constraint, energy storage device constraint, and flexible load constraint.

[0020] The energy flow supply-demand balance constraint includes: electricity supply-demand balance constraint, heat supply-demand balance constraint, and cooling supply-demand balance constraint.

[0021] The flexible load constraint includes transferable load constraint and shiftable load constraint.

[0022] Step 3: The intelligent metering terminal collects the output data of energy supply devices and the energy consumption data of load energy-consuming devices through the intelligent metering terminal device interface, and reports them to the master station. The master station obtains real-time weather data, electricity price data, and demand response index data through a third-party platform.

[0023] Step 4: Input the real-time data obtained in Step 3 into the integrated energy system model established in Step 1, calculate the predicted output of distributed energy devices and the predicted data of the adjustable margin of flexible loads, and the master station solves the optimal solution of the demand response scheduling model established in Step 2 according to the predicted data. According to the optimal solution, generate a demand response regulation strategy and send the regulation strategy to the intelligent metering terminal;

[0024] Step 5: The intelligent metering terminal regulates the source-load devices according to the demand response regulation strategy sent by the master station.

[0025] The intelligent metering terminal further decomposes the demand response regulation strategy sent by the master station into optimization regulation parameters for the output of distributed energy devices in energy supply devices and the working time and working state of flexible loads in load energy-consuming devices, and sends control instructions to the terminal device interface to control the operating states of the corresponding devices respectively.

[0026] Adopting the above technical solution, compared with the prior art, it has the following beneficial effects:

[0027] In the present invention, the intelligent measurement terminal is used to collect the energy demand of the energy consumption side and the output of the energy supply side in real time, generate a demand response scheduling strategy with the optimal operation cost of the integrated energy system by combining the data of the third-party platform, and coordinate and control the operation states of distributed energy and flexible loads through the intelligent measurement terminal, so as to formulate and implement the optimal energy consumption plan that is economical, energy-saving and environmentally friendly. Description of the Drawings

[0028] Figure 1 is the framework of the demand response regulation system based on the intelligent measurement terminal of the present invention;

[0029] Figure 2 is the flow of the demand response regulation method based on the intelligent measurement terminal of the present invention. Specific Embodiments

[0030] The method of the present invention is a demand response regulation system and method based on an intelligent measurement terminal proposed on the basis of collaborative regulation based on the intelligent measurement terminal. The present invention will be described in detail below in conjunction with the drawings and through specific embodiments. The following embodiments are explanations of the present invention, and the present invention is not limited to the following embodiments.

[0031] Embodiment 1

[0032] As Figure 1 shown, this embodiment provides a demand response regulation system based on an intelligent measurement terminal, including a master station, an intelligent measurement terminal, a terminal device interface, and source-load devices.

[0033] The master station is connected to the intelligent measurement terminal. The master station obtains the operation data of the source-load devices through the intelligent measurement terminal, obtains weather data, real-time electricity price data, and demand response index data by accessing a third-party platform, and generates a demand response regulation strategy and sends it to the intelligent measurement terminal.

[0034] The intelligent measurement terminal is connected to the terminal device interface and the master station. The intelligent measurement terminal receives the operation data of the source-load devices collected by the terminal device interface and uploads it to the master station, and receives the demand response regulation strategy sent by the master station and controls the operation state of the source-load devices through the terminal device interface according to the regulation strategy.

[0035] The terminal device interface is connected to the intelligent measurement terminal and the source-load devices. The terminal device interface provides a standardized interface. The source-load devices are connected to the intelligent measurement terminal through the terminal device interface. The terminal device interface collects data and controls the operation state of the source-load devices.

[0036] The source-load equipment includes natural gas networks, power grids, CCHP, photovoltaic, wind energy, energy storage, electric vehicles, water heaters, and air conditioning equipment.

[0037] Embodiment 2

[0038] As Figure 2 shown, this embodiment provides a demand response regulation method based on an intelligent measurement terminal, including the following steps.

[0039] S1. Establish an integrated energy system model:

[0040] Establish an integrated energy system model that couples distributed energy equipment such as CCHP, photovoltaic, wind energy, and energy storage, and flexible load energy-using equipment such as electric vehicles, water heaters, and air conditioners.

[0041] S2. Establish an optimal demand response scheduling model for system operation costs:

[0042] The demand response scheduling model includes a multi-objective optimization function and constraint conditions consisting of the minimum operating cost M oc , the minimum carbon emission cost M ce , and the minimum flexible load response demand subsidy cost M DR .

[0043] The multi-objective optimization function is expressed as:

[0044]

[0045]

[0046]

[0047] Among them, is the electricity purchase volume, is the electricity purchase price, is the electricity sales volume, is the electricity sales price, is the gas purchase volume, is the gas purchase price, C op is the equipment maintenance cost, ε is the carbon treatment cost, β e and β g are the equivalent emission coefficients for electricity purchase and gas purchase respectively, σ1 and σ2 are the basic compensation cost and comfort compensation cost for transferable loads respectively, T max is the maximum transferable time interval, p(t,t′) is the load volume transferred from time t to time t′, is the interruptible load volume, is the interrupt load compensation price.

[0048] Use the linear weighted method to convert the multi-objective optimization problem into a single-objective optimization problem:

[0049] F = min(k1M oc + k2M ce + k3M DR )

[0050] where k1, k2, and k3 are the weight coefficients of the operating cost, carbon emission cost, and flexible load response demand subsidy cost respectively.

[0051] The constraint conditions include: energy flow supply - demand balance constraint, distributed energy output constraint, energy storage device constraint, and flexible load constraint.

[0052] The energy flow supply - demand balance constraint includes: electricity supply - demand balance constraint, heat supply - demand balance constraint, and cooling supply - demand balance constraint.

[0053] The distributed energy output constraint includes the output limit constraints of photovoltaic power generation, wind power generation, CCHP, and energy storage device constraints.

[0054] The flexible load constraint includes the charging and discharging constraints of electric vehicles, water heater constraints, and air - conditioner constraints.

[0055] S3. The master station obtains the collected information reported by the intelligent measurement terminal and the data of the third - party platform:

[0056] The intelligent measurement terminal collects the output data of energy supply equipment and the energy consumption data of load - using equipment through the intelligent measurement terminal device interface and reports them to the master station. The master station obtains real - time weather data, electricity price data, and demand response index data through the third - party platform.

[0057] S4. The master station generates a demand response scheduling strategy and sends it to the intelligent measurement terminal:

[0058] Input the real - time data obtained in S3 into the integrated energy system model established in S1, calculate the predicted output of distributed energy equipment and the predicted adjustable margin of flexible load. The master station solves the optimal solution of the demand response scheduling model established in S2 according to the predicted data. According to the optimal solution, generate a demand response regulation strategy and send the regulation strategy to the intelligent measurement terminal.

[0059] S5. The intelligent measurement terminal regulates the controlled equipment through the terminal device interface:

[0060] The intelligent measurement terminal further decomposes the demand response regulation strategy sent by the master station into the optimization regulation parameters of the working time and working state of CCHP, photovoltaic, wind energy, energy storage equipment in energy supply equipment and electric vehicles, water heaters, and air - conditioner equipment in load - using equipment, and sends control commands to the terminal device interface to control the operating states of the corresponding equipment respectively.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A demand response regulation system and method based on an intelligent measurement terminal, characterized in that, Including: Master station, intelligent measurement terminal, terminal device interface, source and load equipment; The master station establishes a connection with the intelligent measurement terminal. The master station obtains the operation data of the source and load equipment through the intelligent measurement terminal, generates a demand response regulation strategy and issues it to the intelligent measurement terminal. The intelligent measurement terminal is connected to the terminal device interface and the master station. The intelligent measurement terminal receives the operation data of the source and load equipment collected by the terminal device interface and uploads it to the master station. The intelligent measurement terminal receives the demand response regulation strategy issued by the master station and controls the operation status of the source and load equipment through the terminal device interface according to the regulation strategy. The terminal device interface is connected to the intelligent measurement terminal and the source and load equipment. The terminal device interface provides a standardized interface. The source and load equipment accesses the intelligent measurement terminal through the terminal device interface. The terminal device interface collects data and controls the operation status of the source and load equipment. The source and load equipment includes a source-side device and a load-side device, which are an energy supply device and a load energy consumption device respectively.

2. A demand response regulation system and method based on an intelligent measurement terminal, characterized in that, Including the following steps: Step 1, establish a comprehensive energy system model that couples distributed energy equipment and flexible load energy consumption equipment; Step 2, based on Step 1, establish a demand response scheduling model with the optimal operation cost of the comprehensive energy system; Step 3, the intelligent measurement terminal collects the output data of the energy supply equipment and the energy consumption data of the load energy consumption equipment through the terminal device interface and reports them to the master station. The master station obtains real-time weather data, electricity price data and demand response index data through a third-party platform; Step 4, input the real-time data obtained in Step 3 into the comprehensive energy system model established in Step 1, calculate the predicted output data of the distributed energy equipment and the predicted adjustable margin data of the flexible load, and the master station solves the optimal solution of the demand response scheduling model established in Step 2 according to the prediction data. According to the optimal solution, generate a demand response regulation strategy and issue the regulation strategy to the intelligent measurement terminal; Step 5, the intelligent measurement terminal regulates the source and load equipment according to the demand response regulation strategy issued by the master station.

3. The demand response regulation system and method based on an intelligent measurement terminal according to claim 2, wherein, The demand response scheduling model described in Step 2 includes a multi-objective optimization function and constraint conditions consisting of the minimum operating cost \(M\) oc , the minimum carbon emission cost \(M\) ce , and the minimum flexible load response demand subsidy cost \(M\) DR ; Multi-objective optimization function, expressed as: Among them, is the electricity purchase quantity, is the electricity purchase price, is the electricity sales quantity, is the electricity sales price, is the gas purchase quantity, is the gas purchase price, C op is the equipment maintenance cost, ε is the carbon treatment cost, β e and β g are the equivalent emission coefficients for electricity purchase and gas purchase respectively, σ1 and σ2 are the basic compensation cost and comfort compensation cost for the transferable load respectively, T max is the maximum transferable time interval, p(t, t′) is the load quantity transferred from time t to time t′, is the interruptible load quantity of the interruptible load, is the compensation price for the interruptible load; Use the linear weighted method to convert the multi-objective optimization problem into a single-objective optimization problem: F = min(k1M oc + k2M ce + k3M DR ) Where k1, k2, and k3 are the weight coefficients of the operation cost, carbon emission cost, and flexible load response demand subsidy cost respectively; The constraint conditions include: energy flow supply-demand balance constraint, distributed energy output constraint, energy storage device constraint, flexible load constraint; The energy flow supply-demand balance constraint includes: electricity supply-demand balance constraint, heat supply-demand balance constraint, cooling supply-demand balance constraint; The distributed energy output constraint includes: renewable energy output constraint, energy storage device constraint; The flexible load constraint includes shiftable load constraint and shiftable load constraint.

4. The demand response regulation system and method based on an intelligent measurement terminal according to claim 2, wherein In Step 5, the regulation of the source and load equipment is further decomposed by the intelligent measurement terminal according to the demand response regulation strategy issued by the master station, decomposed into the optimization regulation parameters of the output of the distributed energy equipment in the energy supply equipment and the working time and working state of the flexible load in the load energy consumption equipment, and control instructions are issued to the terminal device interface to control the operation status of the corresponding equipment respectively.

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