Heat storage electric heating configuration determination method and device and electronic equipment

Abstract

The invention discloses a heat storage electric heating configuration determination method and device and electronic equipment. The method comprises the steps that the thermal comfort degree of an object is obtained, and the thermal comfort degree is used for quantifying the comfort degree of the object in a specific thermal environment; determining a thermal load demand based on the thermal comfort; the heat supply power of the target heat storage electric heating equipment is determined; and on the basis of the heat load requirement and the heat supply power, power threshold value configuration and capacity threshold value configuration of the target heat storage electric heating equipment are determined. The technical problem that in the prior art, the power threshold value configuration result and the capacity threshold value configuration result of heat storage electric heating are not ideal is solved.

Description

Technical Field

[0001] The present application relates to the field of power systems, and more particularly, to a method, device, and electronic device for determining the configuration of thermal storage electric heating. Background Art

[0002] With the increasing emphasis on energy conservation and emission reduction, in recent years, building a new low-carbon, safe, and efficient energy system has gradually become an important development direction for power systems. As an important means of electric energy substitution, electric heating has gradually formed a large-scale and high-proportion trend in recent years. Compared with ordinary electric heating equipment, thermal storage electric heating can, to a certain extent, relieve the power supply pressure during the peak heating period in winter of the power grid and improve the safety and stability of power grid operation due to its advantages such as flexible adjustment of power consumption time. Since the power and capacity of thermal storage electric heating configured in the distribution network will affect the safe, stable, and economic operation of the power grid, how to reasonably configure the capacity of thermal storage electric heating in the distribution network has become an urgent problem to be studied.

[0003] Regarding the configuration problem of thermal storage electric heating, the related technologies mainly study the optimization configuration problem of thermal storage electric heating in terms of the economy and flexibility of power grid operation. The configuration results only consider the impacts of heating reliability and comfort, power grid operation economy, and new energy consumption in the configuration of thermal storage electric heating capacity, ignoring the impact of the bearing capacity of the distribution network on the configuration of thermal storage electric heating capacity, resulting in poor safety and stability of power grid operation. There are problems with unsatisfactory configuration results for the power threshold and capacity threshold of thermal storage electric heating.

[0004] For the above problems, no effective solutions have been proposed yet. Summary of the Invention

[0005] Embodiments of the present application provide a method, device, and electronic device for determining the configuration of thermal storage electric heating to at least solve the technical problem of unsatisfactory configuration results for the power threshold and capacity threshold of thermal storage electric heating in the related technologies.

[0006] According to one aspect of the embodiments of the present application, a method for determining the configuration of thermal storage electric heating is provided, including: obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; determining the heat load demand based on the thermal comfort; determining the heating power of a target thermal storage electric heating device; and determining the power threshold configuration and capacity threshold configuration of the target thermal storage electric heating device based on the heat load demand and the heating power.

[0007] Optionally, determining the heat load demand based on the thermal comfort includes: determining the heating area of the target thermal storage electric heating device and the energy metabolism rate of the object; determining a predetermined temperature based on the thermal comfort and the energy metabolism rate; and determining the heat load demand based on the heating area and the predetermined temperature.

[0008] Optionally, the target thermal storage electric heating device includes an electric heating device and a thermal storage device. Determining the heating power of the target thermal storage electric heating device includes: determining the electro-thermal conversion efficiency of the electric heating device; determining the heat release power of the thermal storage device, where the heat release power represents the ability of the thermal storage device to release heat per unit time; and determining the heating power of the target thermal storage electric heating device based on the electro-thermal conversion efficiency of the electric heating device and the heat release power.

[0009] Optionally, based on the heat load demand and the heating power, determining the power threshold configuration and the capacity threshold configuration of the target thermal storage electric heating device includes: based on the load demand and the heating power, determining a harmonic objective function that balances a first objective function and a second objective function, where the first objective function represents the power supply ability of the distribution network for the target thermal storage electric heating device, and the second objective function represents the sum of the construction cost and the operation cost of the target thermal storage electric heating device; and using the harmonic objective function to determine the power threshold configuration and the capacity threshold configuration.

[0010] Optionally, determining the harmonic objective function that balances the first objective function and the second objective function includes: based on the power data of the target thermal storage electric heating device, determining the first type of constraint conditions of the target thermal storage electric heating device; based on the resource demand data of the target thermal storage electric heating device, determining the second type of constraint conditions of the target thermal storage electric heating device; and determining the harmonic objective function based on the first type of constraint conditions, the second type of constraint conditions, the first objective function, and the second objective function.

[0011] Optionally, determining the harmonic objective function that balances the first objective function and the second objective function includes: using the weight values, maximum values, and minimum values respectively corresponding to the first objective function and the second objective function, and performing a merging process on the first objective function and the second objective function in the following manner to determine the harmonic objective function;

[0012]

[0013] where F is the harmonic objective function, ω is the weight value of the first objective function f1, (1 - ω) is the weight value of the second objective function f2, f1 is the first objective function, f2 is the second objective function, f 1,max is the maximum value of the first objective function, f 1,min is the minimum value of the first objective function, f 2,max is the maximum value of the second objective function, f 2,min is the minimum value of the second objective function.

[0014] Optionally, the first type of constraint condition includes at least one of the following: determining a first constraint condition representing the limit of the electric energy provided to a predetermined line based on the transmission power and voltage phase angle of the predetermined line in the target electric heating storage equipment; determining a second constraint condition for making the target electric heating storage equipment meet the predetermined operation standard based on the current value and voltage value of the predetermined line; determining a third constraint condition representing the power threshold limit and capacity threshold limit of the target electric heating storage equipment; determining a fourth constraint condition representing the heat storage power limit, heat storage amount limit and heat release power limit of the heat storage device based on the electro-thermal conversion efficiency, electric power, heat release power, and heat storage amount of the heat storage device included in the target electric heating storage equipment.

[0015] Optionally, the second type of constraint condition includes at least one of the following: determining a fifth constraint condition for maintaining thermal comfort based on the heat load demand; determining a sixth constraint condition for limiting the power deficit of the target electric heating storage equipment to be less than or equal to a predetermined deficit threshold.

[0016] According to another aspect of the embodiments of the present application, there is provided an electric heating storage configuration determination device, including: a thermal comfort determination module for obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; a heat load demand determination module for determining the heat load demand based on the thermal comfort; a heating power determination module for determining the heating power of the target electric heating storage equipment; and a configuration determination module for determining the power threshold configuration and capacity threshold configuration of the target electric heating storage equipment based on the heat load demand and the heating power.

[0017] According to another aspect of the embodiments of the present application, there is provided an electronic device, including: one or more processors and a memory, where the memory is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the electric heating storage configuration determination method of any one of the above.

[0018] In the embodiments of the present application, by obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; determining the heat load demand based on the thermal comfort; determining the heating power of the target electric heating storage equipment; and determining the power threshold configuration and capacity threshold configuration of the target electric heating storage equipment based on the heat load demand and the heating power. The purpose of improving the bearing capacity of the distribution network for electric heating storage while taking into account the impact of the bearing capacity of the distribution network, construction costs, and operating costs on the electric heating storage configuration is achieved, and the technical effect of improving the accuracy and rationality of the power threshold configuration and capacity threshold configuration results of the electric heating storage configuration is realized, thereby solving the technical problem of the unsatisfactory power threshold configuration and capacity threshold configuration results of electric heating storage in the related art. Brief Description of the Drawings

[0019] The drawings described herein are provided to further understand the present application and form a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0020] Figure 1 is a flowchart of an optional method for determining a thermoelectric storage heating configuration according to an embodiment of the present application;

[0021] Figure 2 is a comfort schematic diagram of an optional method for determining a thermoelectric storage heating configuration according to an optional embodiment of the present application;

[0022] Figure 3 is a first schematic diagram of an optional method for determining a thermoelectric storage heating configuration according to an optional embodiment of the present application;

[0023] Figure 4 is a second schematic diagram of an optional method for determining a thermoelectric storage heating configuration according to an optional embodiment of the present application;

[0024] Figure 5 is a third schematic diagram of an optional method for determining a thermoelectric storage heating configuration according to an optional embodiment of the present application;

[0025] Figure 6 is a schematic diagram of an optional device for determining a thermoelectric storage heating configuration according to an embodiment of the present application. Detailed Embodiments

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the present application are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0028] For the convenience of description, some nouns or terms related to the embodiments of the present application are described below:

[0029] PMV (Predicted Mean Vote), which is used to evaluate the satisfaction of the human body with the thermal sensation of the environment. The PMV model calculates a comprehensive evaluation value of human thermal comfort by considering multiple factors, including indoor air temperature, relative humidity, mean radiant temperature, air velocity, human activity metabolic rate, and clothing thermal resistance, so as to ensure the thermal comfort of the indoor environment.

[0030] According to the embodiments of the present application, an embodiment of a method for determining a thermoelectric storage heating configuration is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0031] Figure 1 is a flowchart of an optional method for determining a thermoelectric storage heating configuration provided according to the embodiments of the present application, as Figure 1 shown, the method includes the following steps:

[0032] Step S102, obtaining the thermal comfort of the object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment;

[0033] It can be understood that the thermal comfort of the object is obtained, where the above-mentioned thermal comfort refers to the comfort level of the object with respect to the surrounding thermal environment. By determining the range of the PMV index through this thermal comfort, it can be ensured that the object will not feel an obvious change in comfort within the range of this PMV index. By adjusting the heating power within the elastic range of the thermal comfort, the electric power demand of the thermoelectric storage heating can be reduced during the peak load period, the power supply pressure of the power grid can be relieved, and the bearing capacity of the distribution network for the thermoelectric storage heating can be improved.

[0034] Optionally, Figure 2 is a comfort schematic diagram of an optional method for determining a thermoelectric storage heating configuration provided according to an optional implementation manner of the present application. The relationship between the PMV index and the comfort of the object is as Figure 2 shown. The PMV index corresponds to seven thermal sensations of the human body (i.e., the object) on a seven-level scale. A PMV value of 0 indicates that the human body reaches the optimal thermal comfort state. PMV values of +1, +2, and +3 indicate slightly warm, warm, and hot respectively, and PMV values of -1, -2, and -3 indicate slightly cool, cool, and cold respectively. According to relevant regulations, limiting the PMV value to be between ±1 can meet the thermal comfort requirements of indoor objects in winter.

[0035] Step S104, determine the heat load demand based on thermal comfort;

[0036] It can be understood that according to the thermal comfort of the object, determine the range of PMV values that will not cause obvious changes in the comfort of the object, and then determine the heat load demand. By considering the elasticity of thermal comfort, the thermoelectric storage heating system can reduce the heating power during the peak load period, thereby reducing the power demand from the power grid, improving the flexibility of heating, helping to relieve the power supply pressure of the power grid during the heating peak period, and improving the carrying capacity of the distribution network for thermoelectric storage heating.

[0037] In an optional embodiment, determining the heat load demand based on thermal comfort includes: determining the heating area of the target thermoelectric storage heating device and the energy metabolism rate of the object; determining a predetermined temperature based on thermal comfort and the energy metabolism rate; and determining the heat load demand based on the heating area and the predetermined temperature.

[0038] It can be understood that determine the heating area of the target thermoelectric storage heating device and the energy metabolism rate of the object. According to the thermal comfort of the object and the energy metabolism rate, determine the predetermined temperature, which is the indoor temperature that meets the specific thermal comfort requirements of the human body. Determine the heat load demand according to the heating area and the predetermined temperature. By combining with thermal comfort, the thermoelectric storage heating device can respond more flexibly to the dispatching requirements of the power grid, charge heat during the low electricity consumption period, and release heat during the high electricity consumption period, which not only ensures the comfort of the object but also improves the overall flexibility of the thermoelectric storage heating device and the distribution network.

[0039] Optionally, the PMV user thermal comfort is an evaluation index representing the thermal response of the human body, which is related to factors such as air temperature, humidity, flow rate, human clothing, and activity state that affect human comfort, and the calculation process is relatively complex. To highlight the key points and simplify the calculation, only consider the indoor air temperature, clothing thermal resistance, and human metabolism rate that have a greater impact on the PMV index value, and assume that other parameters except the indoor air temperature are constants. The user thermal comfort is:

[0040]

[0041] where λ PMV,t is the PMV value of indoor users at time t; T0 is the average skin temperature of the human body in a comfortable state, which can be approximately taken as 34 °C; T in,t is the air temperature around the human body in the building at time t (i.e., the preset temperature); M is the human energy metabolism rate, which is related to the activity intensity of the human body. In a residence, it is mostly light activity and can be set to 80 W / m 2 ; I c1 is the thermal resistance of human clothing, which can be taken as 0.11 (m 2 ·°C) / W in winter.

[0042] Optionally, according to the above formula, the indoor temperature T in,t considering thermal comfort can be obtained as:

[0043]

[0044] Optionally, during the heating period in winter, since the PMV index representing human thermal comfort is an interval value, according to the above formula, the preset temperature can also be an interval value. That is, when the preset temperature varies within a certain range, users (i.e., the objects) will not feel an obvious difference. Therefore, the preset temperature can be controlled within the temperature range acceptable to the human body for heating. The heat load model can be expressed as:

[0045] Optionally, according to the formula of the above preset temperature, the formula for the heat load demand can be expressed as:

[0046] H L,t = Sω(T in,t - T out,t ) + CS(T in,t - T in,t-1 )

[0047] where H L,t is the heat load demand of the system at time t; S is the heating area; ω is the heat dissipation coefficient due to the temperature difference between the inside and outside of the building, which can be taken as 1.037×10 5 J / m 2 ·°C; C is the heat capacity per unit heating area, which can be taken as 1.63×10 5 J / m 2 ·°C; T out,t is the outdoor temperature of the building at time t; T in,t-1 is the preset temperature at time t - 1.

[0048] Optionally, determine the heating temperature range through the defined range of the PMV index, obtain the defined interval of the heat load demand according to the heat load model (i.e., the heat load demand formula), and then establish the heat balance condition of the system. Thus, the heat supply balance condition in the optimal configuration of the electric heating with thermal energy storage is transformed from the conventional heat power balance equation into the heat supply balance interval condition considering the elasticity of thermal comfort. Therefore, during the peak load period, by lowering the thermal comfort within the range of the elasticity of thermal comfort, the heat load demand can be reduced to a certain extent, thereby reducing the heating power of the electric heating with thermal energy storage, and further reducing the electric power consumed by the electric heating with thermal energy storage, so as to relieve the power supply pressure of the distribution network during the peak load period and improve the bearing capacity of the distribution network for electric heating to a certain extent.

[0049] Step S106, determine the heating power of the target electric heating with thermal energy storage device;

[0050] It can be understood that determine the heating power of the target electric heating with thermal energy storage device. By determining the heating power of the electric heating with thermal energy storage, the electric energy consumption of the electric heating with thermal energy storage during the peak load period can be reduced by adjusting the co-heating power, on the premise of ensuring the thermal comfort of users, thereby reducing the grid load and improving the bearing capacity of the distribution network.

[0051] In an optional embodiment, the target electric heating with thermal energy storage device includes an electric heating device and a thermal energy storage device. Determining the heating power of the target electric heating with thermal energy storage device includes: determining the electro-thermal conversion efficiency of the electric heating device; determining the heat release power of the thermal energy storage device, where the heat release power represents the ability of the thermal energy storage device to release heat per unit time; based on the electro-thermal conversion efficiency of the electric heating device and the heat release power, determine the heating power of the target electric heating with thermal energy storage device.

[0052] It can be understood that the target electric heating with thermal energy storage device includes an electric heating device and a thermal energy storage device. By determining the electro-thermal conversion efficiency of the electric heating device and the heat release power of the thermal energy storage device, determine the heating power of the target electric heating with thermal energy storage device. Among them, the above-mentioned electro-thermal conversion efficiency represents the efficiency of the electric heating device to convert electric energy into thermal energy, and the above-mentioned heat release power represents the ability of the thermal energy storage device to release heat per unit time. By determining the heating power of the electric heating with thermal energy storage device, the heating power of the electric heating with thermal energy storage device can be optimized, so that during the peak load period, by reasonably scheduling the heat release power of the thermal energy storage device, the start of the electric heating device can be reduced, and the electric energy demand and peak load of the grid during the peak period can be reduced, thereby enhancing the bearing capacity of the distribution network for the electric heating with thermal energy storage device.

[0053] Optionally, the heating power of the target electric heating with thermal energy storage device includes the heating power of direct electric heating for heating and the heat release power of the thermal energy storage device. The formula for the heating power of the target electric heating with thermal energy storage device is:

[0054] H REH,t =η e Pe,t +H r,t

[0055] where H REH,t is the heating power of the target thermoelectric storage heating equipment at time t, P e,t is the power consumption of the target electric heating equipment for direct heating at time t (i.e., the power consumption of the electric heating device), η e is the electro-thermal conversion efficiency of the target electric heating equipment for direct heating (i.e., the electro-thermal conversion efficiency of the electric heating device), H r,t is the heat release power of the thermal energy storage device of the target thermoelectric storage heating equipment at time t.

[0056] Step S108, based on the heat load demand and the heating power, determine the power threshold configuration and the capacity threshold configuration of the target thermoelectric storage heating equipment.

[0057] It can be understood that the power threshold configuration of the target thermoelectric storage heating equipment refers to the maximum electric power determined during the design and installation of the target electric heating equipment, which determines the maximum thermal power that the electric heating equipment can provide. The capacity threshold configuration of the target thermoelectric storage heating equipment refers to the maximum thermal energy that the thermal energy storage device can store. Based on the heat load demand and the heating power, determine the power threshold configuration and the capacity threshold configuration of the target thermoelectric storage heating equipment. By reasonably configuring the power threshold configuration and the capacity threshold configuration of the thermoelectric storage heating equipment, the instantaneous demand for electric energy can be reduced during the peak load period, thereby alleviating the pressure on the power grid and improving the bearing capacity of the power grid. This not only helps the stable operation of the power grid but also avoids equipment overload and power waste caused by excessive load.

[0058] In an alternative embodiment, based on the heat load demand and the heating power, determining the power threshold configuration and the capacity threshold configuration of the target thermoelectric storage heating equipment includes: based on the load demand and the heating power, determining a harmonic objective function that balances the first objective function and the second objective function, where the first objective function represents the power supply capacity of the distribution network for the target thermoelectric storage heating equipment, and the second objective function represents the sum of the construction cost and the operation cost of the target thermoelectric storage heating equipment; using the harmonic objective function to determine the power threshold configuration and the capacity threshold configuration.

[0059] It can be understood that based on the load demand and the heating power, a harmonic objective function that balances the first objective function and the second objective function is determined. Among them, the first objective function is to maximize the bearing capacity of the distribution network that supplies power to the target thermal storage electric heating equipment, and the second objective function is to minimize the sum of the construction cost and the operating cost of the target thermal storage electric heating equipment. By balancing the first objective function and the second objective function, a harmonic objective function can be obtained, and then the power threshold configuration and the capacity threshold configuration can be determined. By establishing the harmonic objective function, the bearing capacity of the distribution network, the construction cost and the operating cost of the thermal storage electric heating equipment are comprehensively considered, and the minimization of the cost is achieved while meeting the heating demand.

[0060] In an alternative embodiment, determining the harmonic objective function that balances the first objective function and the second objective function includes: determining the first type of constraint conditions of the target thermal storage electric heating equipment based on the power data of the target thermal storage electric heating equipment; determining the second type of constraint conditions of the target thermal storage electric heating equipment based on the resource demand data of the target thermal storage electric heating equipment; and determining the harmonic objective function based on the first type of constraint conditions, the second type of constraint conditions, the first objective function, and the second objective function.

[0061] It can be understood that the power data of the target thermal storage electric heating equipment is obtained, and based on this power data, the first type of constraint conditions of the target thermal storage electric heating equipment are determined, such as system power flow constraints, safety constraints, thermal storage electric heating planning constraints, and thermal storage electric heating operation constraints; the resource demand data of the target thermal storage electric heating equipment is obtained, and based on this resource demand data, the second type of constraint conditions of the target thermal storage electric heating equipment are determined, such as the heating balance interval constraint considering the elasticity of thermal comfort and the flexibility supply-demand balance constraint; and the harmonic objective function is determined according to the first type of constraint conditions, the second type of constraint conditions, the first objective function, and the second objective function. By balancing the cost and the bearing capacity of the distribution network, the harmonic objective function promotes the flexibility and stability of the operation of the target thermal storage electric heating equipment, enables the thermal storage electric heating equipment to reduce power consumption during peak load periods and store heat during low load periods, realizes the balance between power grid supply and demand, and improves the overall efficiency and reliability of the power system.

[0062] In an alternative embodiment, determining the harmonic objective function that balances the first objective function and the second objective function includes: using the weight values, maximum values, and minimum values respectively corresponding to the first objective function and the second objective function, and performing a merging process on the first objective function and the second objective function in the following manner to determine the harmonic objective function:

[0063]

[0064] Among them, F is the harmonic objective function, ω is the weight value of the first objective function f1, (1 - ω) is the weight value of the second objective function f2, f1 is the first objective function, f2 is the second objective function, f 1,max is the maximum value of the first objective function, f 1,min is the minimum value of the first objective function, f 2,max is the maximum value of the second objective function, f 2,min is the minimum value of the second objective function.

[0065] It can be understood that the harmonic objective function reflects the overall performance of the target thermal storage electric heating equipment under the condition of considering all objective functions. First, determine the weight values corresponding to the first objective function and the second objective function respectively. These weight values reflect the relative importance of the two objective functions in the comprehensive decision-making. Secondly, determine the maximum and minimum values of the first objective function, and the maximum and minimum values of the first objective function. The maximum and minimum values of the first objective function are used to normalize the first objective function, and the maximum and minimum values of the second objective function are used to normalize the second objective function to eliminate the influence brought by the dimension difference and different orders of magnitude. Based on the weight values corresponding to the first objective function and the second objective function respectively, and the normalized first objective function and second objective function, the first objective function and the second objective function are combined to determine the harmonic objective function.

[0066] Optionally, the above first objective function is to maximize the bearing capacity of the distribution network that supplies power to the target thermal storage electric heating equipment. The first objective function can be the maximum bearing capacity of the distribution network. The bearing capacity of the distribution network for the target thermal storage electric heating equipment can be characterized by the total heating power of the target thermal storage electric heating equipment in this area. The formula of the first objective function is:

[0067]

[0068] Among them, maxf1 is the first objective function, n is the number of nodes in the area, i is the node number, i = 1, 2, 3,..., n, H REH,i is the heating power of the thermal storage electric heating equipment corresponding to node i.

[0069] Optionally, the above second objective function is to minimize the sum of the construction cost and operation cost of the target thermal storage electric heating equipment. The formula of the second objective function is:

[0070] minf2 = C inv + C ope

[0071] Among them, minf2 is the second objective function, C inv is the construction cost of the target thermal storage electric heating equipment, C opeis the grid operation cost (i.e., operation cost) of the target thermal storage electric heating equipment.

[0072] Optionally, the construction cost of the target thermal storage electric heating equipment includes the initial construction cost, equipment operation and maintenance cost, and equipment residual value of the target thermal storage electric heating equipment, C inv The formula is:

[0073] C inv = C f + C m - C r

[0074] Wherein, C f is the initial construction cost of the target thermal storage electric heating equipment; C m is the operation and maintenance cost of the target thermal storage electric heating equipment; C r is the residual value of the target thermal storage electric heating equipment, generally taking 5% of the initial construction cost.

[0075] Optionally, the initial construction cost of the target thermal storage electric heating equipment mainly includes the investment costs of the electric heating device and the heat storage device of the target electric heating equipment. C f The formula is:

[0076]

[0077] Wherein, C f1 (P e ) is the initial construction cost of the electric heating device; C f2 (Q r ) is the initial construction cost of the heat storage device; P e is the configured power of the target electric heating equipment (i.e., power threshold configuration), Q r is the configured capacity of the target electric heating equipment (i.e., capacity threshold configuration); C e is the construction cost required per unit capacity of the electric heating device, C r is the construction cost required per unit capacity of the heat storage device; r e is the discount rate of the electric heating device, r r is the discount rate of the heat storage device; y e is the operation years of the electric heating device, y r is the operation years of the heat storage device.

[0078] Optionally, the operation and maintenance cost of the target electric heating equipment can be determined according to the initial construction cost of the equipment. C m The formula is:

[0079] C m = k m C f

[0080] Among them, k m is the maintenance rate of the target electric heating equipment within the operation years, generally taking 2%.

[0081] Optionally, the operation cost of the target heat storage electric heating equipment includes network loss cost, penalty cost for abandoned wind and light, and compensation cost. The formula for C ope is as follows:

[0082] C ope = C loss + C pun + C b

[0083] Among them, C loss is the network loss cost; C pun is the penalty cost for abandoned wind and light; C b is the compensation cost for reducing the user's thermal comfort.

[0084] Optionally, the formulas for the network loss cost, penalty cost for abandoned wind and light, and compensation cost are as follows:

[0085]

[0086] Among them, f t is the electricity price at the operation time of moment t; T D is the number of typical winter days, the value of which is 90, T is the dispatching period of a typical winter day, the value of which is 24, P loss,t is the network loss power at moment t; f pun,DG,t is the unit penalty cost for abandoned wind and light at moment t, P loss,DG,t is the abandoned wind and light power at moment t, f pun,NL,t is the load shedding power at moment t, P loss,NL,t is the load shedding penalty cost at moment t, k b is the compensation cost coefficient for reducing the user's thermal comfort, H L0,t is the heat load demand corresponding to the PMV index value of 0 at moment t.

[0087] In an optional embodiment, the first type of constraint conditions includes at least one of the following: determining a first constraint condition representing the limitation of the electric energy provided for a predetermined line based on the transmission power and voltage phase angle of the predetermined line in the target heat storage electric heating equipment; determining a second constraint condition for making the target heat storage electric heating equipment meet the predetermined operation standard based on the current value and voltage value of the predetermined line; determining a third constraint condition representing the power threshold limitation and capacity threshold limitation of the target heat storage electric heating equipment; determining a fourth constraint condition representing the heat storage power limitation, heat storage amount limitation and heat release power limitation of the heat storage device based on the electro-thermal conversion efficiency, electric power, heat release power, and heat storage amount of the heat storage device included in the target heat storage electric heating equipment.

[0088] It can be understood that the first type of constraint conditions includes at least one of system power flow constraints, safety constraints, electric storage heating planning constraints, and electric storage heating operation constraints. Among them, the system power flow constraint, that is, the first constraint condition, is determined based on the transmission power and voltage phase angle of a predetermined line in the target electric storage heating equipment, and is used to represent the electric energy limit of the predetermined line; the safety constraint, that is, the second constraint condition, is determined based on the current value and voltage value of the predetermined line, and is used to maintain the operation of the target electric storage heating equipment in line with the predetermined operation standards; the electric storage heating planning constraint, that is, the third constraint condition, is used to represent the power threshold limit and capacity threshold limit of the target electric storage heating equipment; the electric storage heating operation constraint, that is, the fourth constraint condition, is determined based on the electro-thermal conversion efficiency, power consumption, heat release power, and heat storage amount of the heat storage device, and is used to represent the heat storage power limit, heat storage amount limit, and heat release power limit of the heat storage device. By restricting the power, capacity, and operation status of the electric storage heating equipment, it is ensured that the optimal configuration of the electric storage heating equipment can not only improve the bearing capacity of the distribution network, reduce costs, but also enhance the flexibility and stability of the system, ensure the safe operation of the equipment, and promote energy conservation, emission reduction, and the green transformation of the power system.

[0089] Optionally, the system power flow constraint, that is, the first constraint condition, is:

[0090]

[0091] Among them, P ij,max and P ij,min are respectively the upper and lower limits of the transmission power of branch ij; P ij,t is the active power transmitted by branch ij at time t; θ i,max and θ i,min are respectively the upper and lower limits of the voltage phase angle of node i; θ i,t is the voltage phase angle of node i at time t.

[0092] Optionally, the transmission power can be determined by the electric power P REH,t consumed by the target electric storage heating equipment at time t. The electric power consumed by the target electric storage heating equipment includes the electric power for direct heating by electric heating (i.e., the electric power of the electric heating device) and the electric power for heat storage heating (i.e., the electric power of the heat storage device). The formula for P REH，t is:

[0093] P REH,t =(P e,t +P r,t )λ t

[0094] Among them, P e,t is the electric power for direct heating by the target electric heating equipment at time t (i.e., the electric power of the electric heating device), P r,tis the power consumption for heat storage and heating of the electric heating system at time t (i.e., the power consumption of the heat storage device), λ t is the start / stop flag of the target electric heating system with heat storage at time t (taking 1 indicates enabling the target electric heating system with heat storage, and taking 0 indicates disabling the target electric heating system with heat storage).

[0095] Optionally, the start / stop flag λ of the target electric heating system with heat storage at time t t can be obtained by processing conditional variables. Some input parameters such as partial bearing capacity indicators in the configuration model of the target electric heating system with heat storage are conditional variables. For example, the number of heavy / light load periods of the distribution transformer and the number of heavy / light load lines need to be conditionally determined first, and then the variable values are solved.

[0096] Therefore, through conditional variable determination, variable values that meet the conditions are obtained. Taking the solution of the number of heavy load periods of the distribution transformer as an example.

[0097]

[0098] T sub,weight =∑u sub

[0099] where P sub,t is the distribution transformer power at time t; P sub,max is the rated capacity of the distribution transformer; u sub is a 0 / 1 matrix with the same dimension as P sub,t ; M is the maximum value, which can take the value of 10000, and T sub,weight is the heavy load operation time of the distribution transformer.

[0100] Optionally, the safety constraint, i.e., the second constraint condition, is:[[]]

[0101]

[0102] where I ij,max and I ij,min are the upper and lower limits of the current of branch ij respectively, I ij,t is the current of branch ij at time t, V j.min and V j.max are the upper and lower limits of the voltage of node j respectively, and V j,t is the voltage of node j at time t.

[0103] Optionally, restricted by factors such as cost and space, the configured power threshold and capacity threshold of the electric heating system with heat storage should meet the planning constraints of the electric heating system with heat storage, i.e., the third constraint condition is:[[]]

[0104]

[0105] where P e,max and Q r,maxThey are the upper limits of the power threshold configuration and the capacity threshold configuration respectively.

[0106] Optionally, to ensure the normal operation of the electro-thermal storage heating equipment, the heat storage device of the electro-thermal storage heating equipment cannot perform heat storage and heat release simultaneously, and the heat storage and heat release power cannot exceed the rated value. The operating constraints of the electro-thermal storage heating are the four constraint conditions as follows:

[0107] P r,t η r ·H r,t = 0

[0108]

[0109] Among them, and are the upper limits of the heat storage and heat release power of the heat storage device (i.e., the rated value) respectively, Q r,t is the heat storage amount of the heat storage device of the electro-thermal storage heating equipment at time t, and η r is the electro-thermal conversion efficiency of the heat storage device of the electro-thermal storage heating equipment.

[0110] Optionally, the formula for the heat storage amount Q r,t of the heat storage device of the electro-thermal storage heating equipment at time t is:

[0111] Q r,t = (1 - μ)Q r,t-1 + (P r,t η r - H r,t )Δt

[0112] Among them, μ is the heat dissipation loss rate of the heat storage device, Δt is the scheduling time interval, and Q r,t-1 is the heat storage amount of the heat storage device at time t - 1.

[0113] In an alternative embodiment, the second type of constraint conditions includes at least one of the following: a fifth constraint condition for determining to maintain thermal comfort based on the heat load demand; a sixth constraint condition for determining that the power deficit of the target electro-thermal storage heating equipment is limited to be less than or equal to a predetermined deficit threshold.

[0114] It can be understood that the second type of constraint conditions includes at least one of the heating balance interval constraint considering the elasticity of thermal comfort and the flexibility supply-demand balance constraint. The heating balance interval constraint considering the elasticity of thermal comfort, i.e., the fifth constraint condition, is determined based on the load demand and is used to maintain thermal comfort; the flexibility supply-demand balance constraint, i.e., the sixth constraint condition, is determined based on the power deficit of the target thermal storage electric heating equipment and the predetermined deficit threshold, and is used to ensure that the power deficit of the target thermal storage electric heating equipment is less than or equal to the predetermined deficit threshold. By controlling the power deficit and optimizing the power allocation of the thermal storage electric heating equipment, the power demand can be reduced during the peak load period, while the heat storage can be increased during the low load period, balancing the power supply and demand of the power grid and enhancing the flexibility of the system operation.

[0115] Optionally, the heating balance interval constraint considering the elasticity of thermal comfort, i.e., the fifth constraint condition, is:

[0116]

[0117] where H L,t,max and H L,t,min are respectively the upper and lower limits of the heat load demand that meets the user's thermal comfort demand at time t; ε up and ε down are respectively the elasticity coefficients that meet the user's thermal comfort demand, corresponding to the upper and lower limits of the PMV index.

[0118] Optionally, the flexibility supply-demand balance constraint means that the sum of the flexibility resources and the flexibility resource deficit is greater than or equal to the flexibility demand. The flexibility supply-demand balance constraint, i.e., the sixth constraint condition, is:

[0119]

[0120] where and are the upward and downward flexibility resources of the distribution network at time t; and are the upward and downward flexibility resource deficits (i.e., power deficits) of the distribution network at time t; and are the upward and downward flexibility demands of the distribution network at time t, and are the upward and downward flexibility demand deficits (i.e., the predetermined deficit threshold) of the distribution network at time t.

[0121] Through the above step S102, the thermal comfort of the object is obtained, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; step S104, based on the thermal comfort, determine the heat load demand; step S106, determine the heating power of the target storage electric heating equipment; step S108, based on the heat load demand and the heating power, determine the power threshold configuration and capacity threshold configuration of the target storage electric heating equipment. It is possible to achieve the purpose of improving the bearing capacity of the distribution network for storage electric heating while taking into account the influence of the bearing capacity of the distribution network, as well as the construction cost and operation cost on the configuration of storage electric heating, and achieve the technical effect of improving the accuracy and rationality of the power threshold configuration and capacity threshold configuration results of the storage electric heating configuration, thereby solving the technical problem that the power threshold configuration and capacity threshold configuration results of the storage electric heating in the related technology are not ideal.

[0122] Based on the above embodiments and alternative embodiments, the present application proposes an alternative implementation manner, and uses the above embodiments to propose an optimization configuration method for storage electric heating (i.e., the target storage electric heating equipment) considering the bearing capacity of the distribution network. This configuration method aims to maximize the bearing capacity of the distribution network for storage electric heating and minimize the annualized total cost of the system, and optimize the configuration of the storage electric heating capacity to improve the bearing capacity of the distribution network for storage electric heating on the premise of ensuring the economic benefits of the distribution network and the comfort of users. This optimization configuration method mainly includes steps S1, the storage electric heating model; S2, the correlation analysis between the thermal comfort elasticity and the storage electric heating capacity configuration; S3, the optimization configuration model of the storage electric heating capacity.

[0123] S1, the storage electric heating model;

[0124] Storage electric heating is mainly divided into water storage electric heating and solid-state storage electric heating. Since the solid-state storage electric heating uses high-temperature resistant solid heat storage materials inside, its heat storage capacity is greatly improved, and more stable heat energy supply can be achieved, and its application range is wider than that of water electric heating. Therefore, a model of solid-state storage electric heating is established. Solid-state storage electric heating mainly consists of an electric heating (i.e., an electric heating device) and a heat storage device. The heat storage characteristics of the heat storage device can improve its electricity consumption flexibility, so that its electricity consumption power is not restricted by the heating demand to a certain extent. The following specifically describes the storage electric heating model.

[0125] The electric power consumed by the target storage electric heating equipment includes the electric power for direct heating of the electric heating (i.e., the electric power of the electric heating device) and the electric power for heat storage heating (i.e., the electric power of the heat storage device), P REH，t The formula for is:

[0126] P REH,t =(P e,t +P r,t )λt

[0127] Among them, P e,t is the power consumption of the target electric heating equipment for direct heating at time t (i.e., the power consumption of the electric heating device), P r,t is the power consumption of the electric heating for heat storage and heating at time t (i.e., the power consumption of the heat storage device), λ t is the start-stop flag of the target electric heat storage heating equipment at time t (when taking 1, it means the target electric heat storage heating equipment is enabled; when taking 0, it means the target electric heat storage heating equipment is disabled). The start-stop flag λ t of the target electric heat storage heating equipment at time t can be obtained by processing the conditional variable.

[0128] The heating power of the target electric heat storage heating equipment includes the heating power of the electric heating for direct heating and the heat release power of the heat storage device. The formula for the heating power of the target electric heat storage heating equipment is:

[0129] H REH,t = η e P e,t + H r,t

[0130] Among them, H REH,t is the heating power of the target electric heat storage heating equipment at time t, P e,t is the power consumption of the target electric heating equipment for direct heating at time t (i.e., the power consumption of the electric heating device), η e is the electro-thermal conversion efficiency of the target electric heating equipment for direct heating (i.e., the electro-thermal conversion efficiency of the electric heating device), H r,t is the heat release power of the heat storage device of the target electric heat storage heating equipment at time t.

[0131] The heat storage quantity Q r,t of the heat storage device of the electric heat storage heating equipment at time t is calculated by the formula:

[0132] Q r,t = (1 - μ)Q r,t-1 + (P r,t η r - H r,t )Δt

[0133] Among them, μ is the heat dissipation loss rate of the heat storage device, Δt is the scheduling time interval, and Q r,t-1 is the heat storage quantity of the heat storage device at time t - 1.

[0134] S2, Correlation analysis of thermal comfort elasticity and electric heat storage heating capacity configuration;

[0135] The PMV user thermal comfort is an evaluation index representing the human body's thermal response. It is related to factors such as air temperature, humidity, flow rate, human clothing, and activity status that affect human comfort, and the calculation process is relatively complex. To highlight the key points and simplify the calculation, only the indoor air temperature, clothing thermal resistance, and human metabolic rate that have a greater impact on the PMV index value are considered, and it is assumed that other parameters except the indoor air temperature are constants. The user thermal comfort is as follows:

[0136]

[0137] where λ PMV,t is the PMV value of the indoor user at time t; T0 is the average skin temperature of the human body in a comfortable state, which can be approximately taken as 34 °C; T in,t is the air temperature around the human body in the building at time t (i.e., the set temperature); M is the human energy metabolic rate, which is related to the activity intensity of the human body. In a residence, it is mostly light activity and can be set at 80 W / m 2 ; I c1 is the clothing thermal resistance of the human body, and in winter, it can be taken as 0.11 (m 2 ·°C) / W.

[0138] The relationship between the PMV index and the object comfort is as Figure 2 shown. The PMV index corresponds to 7 thermal sensations of the human body (i.e., the object) on a 7-level scale. A PMV value of 0 indicates that the human body reaches the best thermal comfort state. PMV values of +1, +2, and +3 indicate slightly warm, warm, and hot respectively, and PMV values of -1, -2, and -3 indicate slightly cool, cool, and cold respectively. According to relevant regulations, limiting the PMV value within ±1 can meet the thermal comfort requirements of indoor objects in winter.

[0139] According to the above formula, the indoor temperature T in,t considering thermal comfort can be obtained as:

[0140]

[0141] During the heating period in winter, since the PMV index representing human thermal comfort is an interval value, the set temperature can also be obtained as an interval value according to the above formula. That is, when the set temperature changes within a certain range, the user (i.e., the object) will not feel an obvious difference. Therefore, the set temperature can be controlled within the temperature range acceptable to the human body for heating.

[0142] According to the formula of the above set temperature, the formula for the heat load demand can be expressed as:

[0143] H L,t = Sω(T in,t - T out,t ) + CS(T in,t - Tin,t-1 )

[0144] Among them, H L,t is the heat load demand of the system at time t; S is the heating area; ω is the heat dissipation coefficient of the temperature difference between the inside and outside of the building, and its value can be 1.037×10 5 J / m 2 ·°C; C is the heat capacity per unit heating area, and its value can be 1.63×10 5 J / m 2 ·°C; T out,t is the outdoor temperature of the building at time t; T in,t-1 is the preset temperature at time t-1.

[0145] Determine the heating temperature range through the limited range of the PMV index, and obtain the limited interval of the heat load demand according to the heat load model (i.e., the heat load demand formula), and then establish the heat balance condition of the system. Thus, the heating balance condition in the optimized configuration model of the electric heating storage with heat storage is transformed from the conventional thermal power balance equation to the heating balance interval condition considering the elasticity of thermal comfort. Therefore, during the peak load period, by reducing the thermal comfort within the range of the elasticity of thermal comfort, the heat load demand can be reduced to a certain extent, thereby reducing the heating power of the electric heating storage with heat storage, and further reducing the electric power consumed by the electric heating storage with heat storage, so as to relieve the power supply pressure of the distribution network during the peak load period and improve the bearing capacity of the distribution network for electric heating to a certain extent.

[0146] S3. Optimized configuration model of the electric heating storage with heat storage.

[0147] Step S31. Objective function.

[0148] (1) The maximum bearing capacity of the distribution network (i.e., the first objective function).

[0149] The first objective function is to maximize the bearing capacity of the distribution network that supplies power to the target electric heating storage equipment with heat storage, that is, the maximum bearing capacity of the distribution network is taken as the first objective function. The bearing capacity of the distribution network for the target electric heating storage equipment with heat storage can be characterized by the total heating power of the target electric heating storage equipment in this area. The formula of the first objective function is:

[0150]

[0151] Among them, maxf1 is the first objective function, n is the number of nodes in the area, i is the node number, i = 1, 2, 3,..., n, H REH,i is the heating power of the electric heating storage equipment corresponding to node i.

[0152] (2) The lowest cost (i.e., the second objective function).

[0153] The second objective function aims to minimize the sum of the construction cost and operation cost of the target thermal storage electric heating equipment, that is, the lowest cost is taken as the second objective function. The formula of the second objective function is:

[0154] minf2=C inv +C ope

[0155] where minf2 is the second objective function, C inv is the construction cost of the target thermal storage electric heating equipment, and C ope is the grid operation cost (i.e., operation cost) of the target thermal storage electric heating equipment.

[0156] 1) Construction cost: The construction cost of the target thermal storage electric heating equipment includes the initial construction cost, equipment operation and maintenance cost, and equipment residual value of the target thermal storage electric heating equipment. The formula of C inv is:

[0157] C inv =C f +C m -C r

[0158] where C f is the initial construction cost of the target thermal storage electric heating equipment; C m is the operation and maintenance cost of the target thermal storage electric heating equipment; C r is the residual value of the target thermal storage electric heating equipment, generally taking 5% of the initial construction cost.

[0159] The initial construction cost of the target thermal storage electric heating equipment mainly includes the investment costs of the electric heating device and the heat storage device of the target electric heating equipment. The formula of C f is:

[0160]

[0161] where C f1 (P e ) is the initial construction cost of the electric heating device; C f2 (Q r ) is the initial construction cost of the heat storage device; P e is the configured power of the target electric heating equipment (i.e., power threshold configuration), Q r is the configured capacity of the target electric heating equipment (i.e., capacity threshold configuration); C e is the construction cost required per unit capacity of the electric heating device, C r is the construction cost required per unit capacity of the heat storage device; r e is the discount rate of the electric heating device, r r is the discount rate of the heat storage device; y eThe operation life of the electric heating device is y r The operation life of the heat storage device

[0162] The operation and maintenance cost of the target electric heating equipment can be determined according to the initial construction cost of the equipment. C m The formula is as follows:

[0163] C m = k m C f

[0164] Among them, k m Is the maintenance rate of the target electric heating equipment during the operation life, generally taking 2%.

[0165] 2) Operating cost: The operating cost of the target electric heat storage heating equipment includes network loss cost, penalty cost for abandoning wind and light, and compensation cost. C ope The formula is as follows:

[0166] C ope = C loss + C pun + C b

[0167] Among them, C loss Is the network loss cost; C pun Is the penalty cost for abandoning wind and light; C b Is the compensation cost for reducing the user's thermal comfort

[0168] The formulas for network loss cost, penalty cost for abandoning wind and light, and compensation cost are as follows:

[0169]

[0170] Among them, f t Is the electricity price at the operating time of t; T D Is the operating time of a typical winter day, P loss,t Is the network loss power at t; f pun,DG,t Is the unit penalty cost for abandoning wind and light at t, P loss,DG,t Is the power of abandoning wind and light at t, f pun,NL,t Is the load shedding power at t, P loss,NL,t Is the load shedding penalty cost at t, k b Is the compensation cost coefficient for reducing the user's thermal comfort, H L0,t Is the heat load demand corresponding to the PMV index value of 0 at t

[0171] Step S32, constraint conditions

[0172] (1) The system power flow constraint (i.e., the first constraint condition) is:

[0173]

[0174] Among them, P ij,max and P ij,min are respectively the upper limit and the lower limit of the transmission power of branch ij; P ij,t is the active power transmitted by branch ij at time t; θ i,max and θ i,min are respectively the upper limit and the lower limit of the voltage phase angle of node i; θ i,t is the voltage phase angle of node i at time t. The transmission power can be determined by the electric power P REH,t consumed by the target thermal storage electric heating equipment at time t.

[0175] (2) The security constraint (i.e., the second constraint condition) is:

[0176]

[0177] Among them, I ij,max and I ij,min are respectively the upper limit and the lower limit of the current of branch ij, I ij,t is the current of branch ij at time t, V j.min and V j.max are respectively the upper limit and the lower limit of the voltage of node j, V j,t is the voltage of node j at time t.

[0178] (3) The thermal storage electric heating planning constraint (i.e., the third constraint condition).

[0179] Limited by factors such as cost and space, the configured power threshold and capacity threshold of the thermal storage electric heating should meet the thermal storage electric heating planning constraint.

[0180]

[0181] Among them, P e,max and Q r,max are respectively the upper limits of the configured power threshold and capacity threshold.

[0182] (4) The thermal storage electric heating operation constraint (i.e., the fourth constraint condition).

[0183] To ensure the normal operation of the thermal storage electric heating equipment, the heat storage device of the thermal storage electric heating equipment cannot perform heat storage and heat release simultaneously, and the heat storage and heat release power cannot exceed the rated value.

[0184] P r,t η r ·H r,t = 0

[0185]

[0186] Among them, and are respectively the upper limits of the heat storage and heat release powers of the heat storage device (i.e., the rated values), and Q r,t is the heat storage amount of the heat storage device of the electric heating equipment with heat storage at time t, and η r is the electro-thermal conversion efficiency of the heat storage device of the electric heating equipment with heat storage.

[0187] (5) The heat supply balance interval constraint considering the elasticity of thermal comfort (i.e., the fifth constraint condition) is:

[0188]

[0189] where H L,t,max and H L,t,min are respectively the upper and lower limits of the heat load demand that meets the thermal comfort requirements of users at time t; ε up and ε down are respectively the elasticity coefficients that meet the thermal comfort requirements of users, corresponding to the upper and lower limits of the PMV index.

[0190] (6) The flexible supply-demand balance constraint (i.e., the sixth constraint condition) is:

[0191]

[0192] where and are the upward and downward flexibility resources of the distribution network at time t; and are the deficiencies of the upward and downward flexibility resources of the distribution network at time t (i.e., power deficiencies); and are the upward and downward flexibility demands of the distribution network at time t, and are the deficiencies of the upward and downward flexibility demands of the distribution network at time t (i.e., the predetermined deficiency thresholds). The flexible supply-demand balance constraint means that the sum of the flexibility resources and the flexibility resource deficiencies is greater than or equal to the flexibility demand.

[0193] Step S33, model processing.

[0194] (1) Multi-objective normalization.

[0195] The objective functions in S31 include two parts: the maximum bearing capacity of the distribution network and the lowest cost. Since they have different dimensions and orders of magnitude, the two objective functions are normalized and weighted to be combined into a comprehensive objective function (i.e., the harmonic objective function) for convenient solution.

[0196]

[0197] Among them, F is the harmonic objective function, ω is the weight value of the first objective function f1, (1 - ω) is the weight value of the second objective function f2, f1 is the first objective function, f2 is the second objective function, f 1,max is the maximum value of the first objective function, f 1,min is the minimum value of the first objective function, f 2,max is the maximum value of the second objective function, f 2,min is the minimum value of the second objective function.

[0198] (2) Second-order cone relaxation.

[0199] The second-order cone relaxation method includes two aspects: "relaxation" and "tightening". On the one hand, the original non-linear constraints that are difficult to solve are "relaxed" into second-order cone convex constraints that are easy to solve. However, this will cause the feasible region to expand, resulting in the obtained optimal solution may not satisfy the original non-linear constraints. On the other hand, an appropriate optimization objective function must be set to drive the second-order cone relaxation to gradually "tighten" to the optimal solution, so that the optimal solution exactly satisfies the original non-linear constraints.

[0200] The electric-gas power flow model (i.e., the system power flow constraint and the security constraint) contains non-linear terms, and it is relatively difficult to directly solve the mixed-integer non-linear programming problem. Therefore, the non-linear terms in the power flow model are processed using the second-order cone relaxation method and converted into a second-order cone programming model. The specific processing method is as follows.

[0201] Let Substitute it into the non-linear power flow formula to obtain the conical constraint:

[0202]

[0203] Among them, is the square value of the current value of branch ij at time t, V j,t is the square value of the voltage value of node j at time t, Q ij,t is the reactive power transmitted by branch ij at time t.

[0204] (3) Conditional variable processing.

[0205] Some input parameters such as partial bearing capacity indicators in the target storage thermoelectric heating equipment configuration model are conditional variables. For example, the number of heavy and light load periods of the distribution transformer and the number of heavy and light loads of the line need to be conditionally determined first, and then the variable values are solved. Therefore, through conditional variable determination, the variable values that meet the conditions are obtained. Taking the solution of the number of heavy load periods of the distribution transformer as an example.

[0206]

[0207] T sub,weight = ∑u sub

[0208] Among them, P sub,t is the distribution transformer power at time t; P sub,max is the rated capacity of the distribution transformer; u sub is a 0 / 1 matrix with the same dimension as P sub,t ; M is the number of maximum values, which can take the value of 10,000, and T sub,weight is the overload operation time of the distribution transformer.

[0209] To further verify the effectiveness and rationality of the above-mentioned optimization configuration method of thermoelectric storage heating considering the bearing capacity of the distribution network, a predetermined distribution system is used for simulation analysis. The following numerical values are only for examples and are not specifically limited.

[0210] Nodes 9, 18, and 27 are the access nodes of photovoltaic equipment, and their rated capacity is 1000 kW (kilowatts); nodes 13, 25, and 31 are set as the access nodes of wind power, and their rated capacity is 1500 kW; nodes 6, 16, and 33 are set as the access nodes of thermoelectric storage heating equipment, and the maximum configuration capacity of a single electric heating (the same as the above P e,max ) is 3 MW (megawatts), and the maximum configuration capacity of a single heat storage device (the same as the above Q r,max ) is 10 MWh (megawatt-hours). Energy storage devices with a capacity of 1000 kWh (kilowatt-hours) are connected to nodes 6, 15, and 30, and their maximum charge / discharge amount is 500 kW / h (kilowatts per hour). Table 1 is the data table related to the thermoelectric storage heating equipment provided by the optional implementation manner of this application, and Table 2 is the data table related to the energy storage equipment provided by the optional implementation manner of this application. As shown in Table 1 and Table 2, the thermoelectric storage heating equipment and the energy storage equipment include the relevant parameters in the table.

[0211] Table 1

[0212] Physical parameters Numerical value Electro-thermal conversion efficiency 97％ Maximum heat storage state of the heat storage device 90％ Minimum heat storage state of the heat storage device 10％ Maximum charge / discharge rate of the heat storage device 20％ Heat dissipation loss rate of the heat storage device 1％ Investment cost per unit capacity of electric heating 500 yuan / kW Investment cost per unit capacity of the heat storage device 50 yuan / kWh Discount rate 8％ Equipment operation life 20 years

[0213] Table 2

[0214] Physical parameters Numerical value Maximum energy storage capacity 900 kWh Minimum energy storage capacity 0 kWh Maximum charging power 500 kW / h Minimum discharge power 500 kW / h Charge / discharge energy efficiency 0.98 Self-loss rate 0.01 Maximum energy storage capacity 900 kWh Minimum energy storage capacity 0 kWh Maximum charging power 500 kW / h

[0215] Figure 3 is the first schematic diagram of an optional method for determining the configuration of thermoelectric storage heating provided by the optional implementation manner of this application. As Figure 3 shown, it is the predicted curve graph of the wind and light output on a typical winter day of the system. Figure 3 The abscissa represents time, and the ordinate represents power. Among them, the dashed line represents the predicted curve of the fan processing, and the solid line represents the predicted photovoltaic output.

[0216] Figure 4 is the second schematic diagram of an optional method for determining the configuration of thermoelectric storage heating provided by the optional implementation manner of this application. As Figure 4 shown, it is the predicted curve graph of the heat load demand on a typical winter day of the system.Figure 4 The abscissa represents time, and the ordinate represents heat.

[0217] Figure 5 It is the third schematic diagram of an optional method for determining the configuration of a heat storage electric heating system according to an optional implementation manner of the present application. As Figure 5 shown, it is the trading electricity price diagram of the distribution network. Figure 5 The abscissa represents time, and the ordinate represents electricity price. The loss cost generated during the operation of the distribution network is accounted for according to the trading electricity price. Through the trading electricity price diagram as Figure 5 shown, the cost of photovoltaic power generation in the system is 0.35 yuan / kWh, the cost of wind power generation is 0.277 yuan / kWh, and the cost of abandoning wind and light in the system is 0.35 yuan / kWh for compensation.

[0218] To verify the effectiveness of an optimized configuration method for heat storage electric heating considering the bearing capacity of the distribution network, the following three scenarios are set for comparative analysis.

[0219] (1) Scenario 1: Configure the electric heating capacity only according to the heat load demand;

[0220] (2) Scenario 2: Configure the heat storage electric heating capacity only considering the cost;

[0221] (3) Scenario 3: Configure the heat storage electric heating capacity comprehensively considering the bearing capacity and cost of the distribution network, that is, the scenario proposed by an optimized configuration method for heat storage electric heating considering the bearing capacity of the distribution network.

[0222] According to Figure 3 , Figure 4 and Figure 5 , the configuration results of the heat storage electric heating under the above three scenarios can be obtained. Among them, Table 3 is the configuration scenario table provided by the optional implementation manner of the present application. As shown in Table 3, all three scenarios are configured with three electric heating devices and three heat storage devices.

[0223] Table 3

[0224] Configuration scheme Electric heating power / MW Heat storage device capacity / MWh 1 3.5904 0 2 3.1580 11.268 3 3.2802 13.239

[0225] It can be seen from the results in Table 3 that in Scenario 1, the electric heating capacity is configured only according to the heat load demand, without considering the configuration of the heat storage device capacity. To meet the heat load demand, the configured power of the electric heating (i.e., the power threshold configuration) is 3.5904 MW.

[0226] The configured power of the electric heating in Scenario 2 is slightly lower than that in Scenario 1. However, the installed capacity configuration (i.e., the capacity threshold configuration) of the heat storage device with a capacity of 11.268 MWh in Scenario 2 can store heat during the low electricity consumption period and release heat during the peak load period to meet the heating demand of users, reduce the peak-valley difference of the load, and lower the system cost.

[0227] Compared with Scheme 2, Scheme 3 comprehensively considers the carrying capacity and cost of the distribution network. The capacity configurations of the electric heating and heat storage devices (i.e., power threshold configuration and capacity threshold configuration) are increased by 3.87% and 17.49% respectively, and the acceptance rate of electric heating in the distribution network is improved.

[0228] Table 4 is the operation result table of the schemes provided by the optional implementation manners of this application. As shown in Table 4, the system operation results of the three schemes are as follows.

[0229] Table 4

[0230] Operation result Scheme 1 Scheme 2 Scheme 3 Distribution network bearing capacity / kW 3314.28 3486.99 3628.47 Operation cost / 10,000 yuan 613.75 569.91 504.22 Construction cost / 10,000 yuan 17.736 21.166 22.743

[0231] From the results in Table 4, it can be seen that in Scheme 1, since the heat storage device is not considered, the electric heating needs to consume electric energy according to the heat load demand at each moment. The grid load is superimposed with the electric heating load on the basis of the basic power consumption load, resulting in a higher load level and a larger load peak-valley difference, and thus a higher system operation cost.

[0232] Scheme 2 adds a heat storage device on the basis of electric heating. It can convert electric energy into heat energy for storage during the low electricity consumption period and release heat energy during the high electricity consumption period, reducing the load peak-valley difference and thus reducing the system operation cost. At the same time, since the construction cost of the heat storage device is relatively low, the total economic cost of Scheme 2 is reduced by 7.14% compared with Scheme 1.

[0233] Scheme 3 comprehensively considers the carrying capacity and cost of the distribution network on the basis of Scheme 2. Although the increase in the configuration capacity of the heat storage electric heating increases the construction cost to a certain extent, the increase in the configuration capacity of the heat storage electric heating further alleviates the load peak-valley difference, and thus the overall cost of the system is reduced, which is reduced by 11.53% compared with Scheme 2. At the same time, the carrying capacity of the distribution network in Scheme 3 is increased by 4.06% compared with Scheme 2, and the carrying capacity of the distribution network is improved in the electric heating access scenario.

[0234] Through the above comparative analysis, it can be seen that Scheme 3 improves the carrying capacity of the distribution network for electric heating while ensuring the reduction of the system cost by reasonably configuring the capacity of the heat storage electric heating.

[0235] The above optional implementation manners at least achieve the following effects: By considering the influence of the carrying capacity of the distribution network on the capacity planning of the heat storage electric heating, with the goal of maximizing the carrying capacity of the distribution network and minimizing the cost, combined with constraint conditions such as power flow constraints, heat storage electric heating planning constraints, and equipment operation constraints, the capacity configuration of the heat storage electric heating is determined, and the carrying capacity of the distribution network for the heat storage electric heating is improved on the premise of reducing the cost and ensuring user comfort.

[0236] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0237] In this embodiment, a device for determining the configuration of a heat storage electric heating system is also provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated here. As used hereinafter, the terms "module" and "device" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0238] According to an embodiment of the present application, an embodiment of a device for implementing the method for determining the configuration of a heat storage electric heating system is also provided. Figure 6 It is a schematic diagram of an optional device for determining the configuration of a heat storage electric heating system provided according to an embodiment of the present application, as Figure 6 shown. The above-mentioned device for determining the configuration of a heat storage electric heating system includes a thermal comfort determination module 602, a heat load demand determination module 604, a heating power determination module 606, and a configuration determination module 608. The device will be described below.

[0239] The thermal comfort determination module 602 is used to obtain the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment.

[0240] The heat load demand determination module 604 is connected to the thermal comfort determination module 602 and is used to determine the heat load demand based on the thermal comfort.

[0241] The heating power determination module 606 is connected to the heat load demand determination module 604 and is used to determine the heating power of the target heat storage electric heating device.

[0242] The configuration determination module 608 is connected to the heating power determination module 606 and is used to determine the power threshold configuration and capacity threshold configuration of the target heat storage electric heating device based on the heat load demand and the heating power.

[0243] In a device for determining a configuration of a thermal storage electric heating system provided by an embodiment of the present application, by providing a thermal comfort determination module 602 for obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; a heat load demand determination module 604, connected to the thermal comfort determination module 602, for determining a heat load demand based on the thermal comfort; a heating power determination module 606, connected to the heat load demand determination module 604, for determining the heating power of a target thermal storage electric heating device; and a configuration determination module 608, connected to the heating power determination module 606, for determining a power threshold configuration and a capacity threshold configuration of the target thermal storage electric heating device based on the heat load demand and the heating power. It achieves the purpose of improving the carrying capacity of the distribution network for thermal storage electric heating on the premise of considering the influence of the carrying capacity of the distribution network, as well as construction costs and operating costs on the configuration of thermal storage electric heating, and realizes the technical effect of improving the accuracy and rationality of the results of the power threshold configuration and the capacity threshold configuration of the thermal storage electric heating configuration, thereby solving the technical problem that the results of the power threshold configuration and the capacity threshold configuration of thermal storage electric heating in the related art are not ideal.

[0244] It should be noted that the above-mentioned modules can be implemented by software or hardware. For example, for the latter, it can be achieved in the following way: the above-mentioned modules can be located in the same processor; or, the above-mentioned modules can be located in different processors in any combination.

[0245] It should be noted here that the above-mentioned thermal comfort determination module 602, heat load demand determination module 604, heating power determination module 606, and configuration determination module 608 correspond to steps S102 to S108 in the embodiment. The examples and application scenarios implemented by the above-mentioned modules and the corresponding steps are the same, but are not limited to the content disclosed in the above-mentioned embodiment. It should be noted that the above-mentioned modules, as a part of the device, can run in a computer terminal.

[0246] It should be noted that the optional or preferred implementation manners of this embodiment can be referred to the relevant descriptions in the embodiment, and will not be repeated here.

[0247] The above-mentioned device for determining a configuration of a thermal storage electric heating system may further include a processor and a memory. The thermal comfort determination module 602, heat load demand determination module 604, heating power determination module 606, configuration determination module 608, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to implement corresponding functions.

[0248] The processor contains cores, which retrieve corresponding program units from the memory. One or more cores can be set. The memory may include non-permanent memory in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0249] An embodiment of the present application provides a non-volatile storage medium, on which a program is stored, and when the program is executed by a processor, it implements a method for determining a configuration of an electric storage heating system.

[0250] An embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored on the memory and executable on the processor. When the processor executes the program, the following steps are implemented: obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; determining the heat load demand based on the thermal comfort; determining the heating power of a target electric storage heating device; and determining the power threshold configuration and capacity threshold configuration of the target electric storage heating device based on the heat load demand and the heating power. The device herein can be a server, a PC, etc.

[0251] The present application also provides a computer program product, which, when executed on a data processing device, is adapted to execute a program initialized with the following method steps: obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; determining the heat load demand based on the thermal comfort; determining the heating power of a target electric storage heating device; and determining the power threshold configuration and capacity threshold configuration of the target electric storage heating device based on the heat load demand and the heating power.

[0252] 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 take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0253] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (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, and combinations of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce means for implementing the specified functions in one Figure 1 flow or multiple flows and / or blocks Figure 1 or means for implementing the specified functions in one block or multiple blocks.

[0254] 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 operate in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means that implement the specified functions in one Figure 1 flow or multiple flows and / or blocks Figure 1 or means for implementing the specified functions in one block or multiple blocks.

[0255] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in one Figure 1 flow or multiple flows and / or blocks Figure 1 or means for implementing the specified functions in one block or multiple blocks.

[0256] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0257] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0258] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0259] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0260] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0261] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining a thermoelectric energy storage heating configuration, characterized in that, Including: Obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; Determining the heat load demand based on the thermal comfort; Determining the heating power of a target thermoelectric storage heating device; Determining the power threshold configuration and capacity threshold configuration of the target thermoelectric storage heating device based on the heat load demand and the heating power.

2. The method according to claim 1, wherein The determining the heat load demand based on the thermal comfort includes: Determining the heating area of the target thermoelectric storage heating device and the energy metabolic rate of the object; Determining a predetermined temperature based on the thermal comfort and the energy metabolic rate; Determining the heat load demand based on the heating area and the predetermined temperature.

3. The method according to claim 1, wherein The target thermoelectric storage heating device includes an electric heating device and a heat storage device. The determining the heating power of the target thermoelectric storage heating device includes: Determining the electro-thermal conversion efficiency of the electric heating device; Determining the heat release power of the heat storage device, where the heat release power represents the ability of the heat storage device to release heat per unit time; Determining the heating power of the target thermoelectric storage heating device based on the electro-thermal conversion efficiency of the electric heating device and the heat release power.

4. The method according to any one of claims 1 to 3, characterized in that The determining the power threshold configuration and capacity threshold configuration of the target thermoelectric storage heating device based on the heat load demand and the heating power includes: Determining a harmonic objective function that balances a first objective function and a second objective function based on the load demand and the heating power, where the first objective function represents the power supply ability of the distribution network for the target thermoelectric storage heating device, and the second objective function represents the sum of the construction cost and operation cost of the target thermoelectric storage heating device; Using the harmonic objective function to determine the power threshold configuration and the capacity threshold configuration.

5. The method according to claim 4, characterized in that The determining the harmonic objective function that balances the first objective function and the second objective function includes: Determining the first type of constraint conditions of the target thermoelectric storage heating device based on the power data of the target thermoelectric storage heating device; Determining the second type of constraint conditions of the target thermoelectric storage heating device based on the resource demand data of the target thermoelectric storage heating device; Determining the harmonic objective function based on the first type of constraint conditions, the second type of constraint conditions, the first objective function, and the second objective function.

6. The method according to claim 4, characterized in that The determining the harmonic objective function that balances the first objective function and the second objective function includes: Using the weight values, maximum values, and minimum values respectively corresponding to the first objective function and the second objective function, and performing a merging process on the first objective function and the second objective function in the following manner to determine the harmonic objective function; Among them, F is the harmonic objective function, ω is the weight value of the first objective function f1, (1 - ω) is the weight value of the second objective function f2, f1 is the first objective function, f2 is the second objective function, f 1,max is the maximum value of the first objective function, f 1,min is the minimum value of the first objective function, f 2,max is the maximum value of the second objective function, f 2,min is the minimum value of the second objective function.

7. The method according to claim 5, wherein The first type of constraint conditions includes at least one of the following: Determining a first constraint condition representing the limitation of the electric energy provided for the predetermined line based on the transmission power and voltage phase angle of the predetermined line in the target thermoelectric storage heating device; Determining a second constraint condition that enables the target thermoelectric storage heating device to meet the predetermined operation standard based on the current value and voltage value of the predetermined line; Determine a third constraint condition representing the power threshold limit and the capacity threshold limit of the target thermal storage electric heating device; Based on the electro-thermal conversion efficiency, power consumption, heat release power, and heat storage amount of the heat storage device included in the target thermal storage electric heating device, determine a fourth constraint condition representing the heat storage power limit, heat storage amount limit, and heat release power limit of the heat storage device.

8. The method according to claim 5, wherein The second type of constraint condition includes at least one of the following: Based on the heat load demand, determine a fifth constraint condition for maintaining the thermal comfort; Determine a sixth constraint condition that limits the power shortage of the target thermal storage electric heating device to be less than or equal to a predetermined shortage threshold.

9. A device for determining a thermoelectric heating configuration, characterized in that Comprising: A thermal comfort determination module for obtaining the thermal comfort of an object, where the thermal comfort is used to quantify the comfort level of the object in a specific thermal environment; A heat load demand determination module for determining the heat load demand based on the thermal comfort; A heating power determination module for determining the heating power of the target thermal storage electric heating device; A configuration determination module for determining the power threshold configuration and the capacity threshold configuration of the target thermal storage electric heating device based on the heat load demand and the heating power.

10. An electronic device, characterized in that, Comprising: One or more processors and a memory, the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the thermal storage electric heating configuration determination method according to any one of claims 1 to 8.

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