CN113091124A - Regional energy supply capacity-based electric-heat complementary heating system partition regulation and control method - Google Patents

Regional energy supply capacity-based electric-heat complementary heating system partition regulation and control method Download PDF

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CN113091124A
CN113091124A CN202110522261.XA CN202110522261A CN113091124A CN 113091124 A CN113091124 A CN 113091124A CN 202110522261 A CN202110522261 A CN 202110522261A CN 113091124 A CN113091124 A CN 113091124A
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CN113091124B (en
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钟崴
张浩然
林小杰
封恩程
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Zhejiang University ZJU
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
    • F24D19/00—Details
    • F24D19/10—Arrangement or mounting of control or safety devices
    • F24D19/1096—Arrangement or mounting of control or safety devices for electric heating systems
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
    • F24D2200/00—Heat sources or energy sources
    • F24D2200/08—Electric heater
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E20/00—Combustion technologies with mitigation potential
    • Y02E20/14—Combined heat and power generation [CHP]

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Abstract

The invention discloses a regional energy supply capacity-based partitioned regulation and control method for an electric-heat complementary heating system, which comprises the following steps of: s1, establishing a power supply capacity model of the power distribution system and a mechanism simulation model of the thermodynamic system; s2, dividing the wide area energy system into a plurality of sub-areas, and determining basic information of the electric power system and the thermodynamic system of each sub-area; s3, establishing an electric heating load prediction model of each sub-region, and calculating to obtain the electric load and the heat load of each sub-region; s4, based on the electric heating load prediction model and the power supply capacity model, evaluating to obtain the power supply load which can be used for electric heating of the power distribution system in each sub-area; s5, determining the constraint conditions of the electric heating complementary heating system, and calculating the optimal heating load of the heating power station in each sub-area under different load requirements. The technical scheme of the invention can be used for searching the optimal heat supply setting of the thermodynamic system in a large-scale electric heating complementary system, and improving the overall flexibility and the energy saving rate of the electric heating complementary process.

Description

Regional energy supply capacity-based electric-heat complementary heating system partition regulation and control method
Technical Field
The invention belongs to the technical field of clean low-carbon heating, and relates to a regional energy supply capacity-based electric heating complementary heating system regional regulation and control method.
Background
With the continuous development of the central heating system in China, the heating pattern mainly based on coal burning has brought about a serious problem of air pollution. In order to improve the cleanness of heat supply production, a part of cities in the north of China starts to widely popularize the key civil engineering of 'changing coal into electricity', but the load of a power grid is increased sharply due to the large access of electric heating, and the safe and stable operation of the power grid is greatly influenced. A plurality of technologies are provided for domestic and foreign researchers to improve the impact problem of electric heating on a power grid, such as a demand side response technology based on electricity price excitation, a technology of adopting other renewable energy sources and electric power complementary heating and the like, but the technologies are both temporary and permanent, and the problem that the electric heating cannot be applied in a large scale in a northern area with a large load demand is still difficult to solve. The invention provides a novel subarea regulation and control method aiming at a mode of combining centralized heat supply and distributed heat supply (namely an electric heat complementary heat supply system). The system adopts basic load of a hot water centralized heating belt for regulation and control, the electric heating belt bears peak load and individualized demand load, and hot water centralized heating basic load values are set in a subarea mode based on regional energy supply capacity, so that the problem of overhigh load of a power grid caused by electric heating is avoided. The invention relieves the impact of the connection of electric heating on the safe and stable operation of the existing power grid, avoids the problem of secondary investment of the power supply increment and the matching power grid, simultaneously reduces the reduction of the comprehensive performance caused by the connection of clean energy heating to the traditional heating system, and greatly improves the feasibility and the flexibility of heating regulation and control of the electric-heat complementary heating system.
Disclosure of Invention
In order to solve the problem of impact of large-scale access of electric heating on the load of a power grid, the invention provides a regional energy supply capacity-based partitioned regulation and control method for an electric-heat complementary heating system, so that the impact of the access of the electric heating on the safe and stable operation of the conventional power grid is relieved, and in addition, the problem of secondary investment of a power supply increment matched with the power grid can be avoided.
In order to achieve the purpose, the invention adopts the following technical scheme:
a regional energy supply capacity-based electric-heat complementary heating system partitioned regulation and control method comprises the following specific steps:
step S1, establishing a power supply capacity model of a power distribution system and a mechanism simulation model of a thermodynamic system;
step S2, dividing the wide area energy system into a plurality of sub-areas, and determining the basic information of the electric power system and the thermodynamic system of each sub-area;
step S3, establishing an electric heating load prediction model of each sub-area, and calculating to obtain the electric load and the heat load of each sub-area;
step S4, based on the electric heating load prediction model and the power supply capacity model, evaluating to obtain the power supply load which can be used for electric heating of the power distribution system in each sub-area;
and step S5, determining the constraint conditions of the electric heating complementary heating system in calculation, and calculating the optimal heating load of the heating power station in each sub-area under different load requirements.
Further, in step S1, the power distribution system power supply capability model is:
max ATSC＝∑Riψi
Figure BDA0003064504020000031
in the formula: a. theTSCThe maximum power supply capacity of the power distribution system is achieved; riThe rated capacity of a main transformer i is obtained; t isiIs the existing load factor of transformer i; psiiThe load factor of a main transformer i is obtained; n is a radical of∑The number of main transformers in the system; l isi,jShowing the communication relationship between the ith main transformer and the jth main transformer, when there is a relationship, Li,j1, otherwise Li,j＝0；Bi,jTransferring the load to a main transformer j when the main transformer i fails; rjRated capacity, R 'of main transformer j'jThe maximum allowable capacity of the main transformer j in a short time; ci,jThe limit capacity of the communication between the main transformer i and the main transformer j is obtained; psiminAnd psimaxRespectively the minimum sum of main transformer iA maximum load rate; d is a given load of the region; z is the set of all main transformers in the area. Voltage constraints are ignored in this model due to the distribution network line angles in each region.
Further, the thermodynamic system mechanism simulation model is as follows:
modeling a heat supply system based on graph theory, abstracting the connection position of equipment into connection nodes, abstracting lines between the two nodes into edges, simplifying each equipment in the system into a physical model according to actual system data, and establishing a topological structure of the heat supply system.
The method specifically comprises the following steps:
Figure BDA0003064504020000032
the above equation is a system of equations consisting of a mass conservation equation and an energy conservation equation, wherein: a is a node-branch incidence matrix of (n-1) x m, where n represents the number of nodes and m represents the number of branches; g is a branch flow vector; d is a node incoming and outgoing flow vector, the incoming flow is positive, and the outgoing flow is negative; a. theTIs a transposed matrix of the A matrix; p is a node head vector; the delta H is a pipe network water head descending vector; s is an n-order pipeline resistance loss diagonal matrix; | G | is a diagonal matrix of the absolute value of the flow of the n-stage pipe section; DH is the water pump lift vector of the pipeline section, if do not contain the water pump, the water pump lift is marked as 0.
Figure BDA0003064504020000041
The above equation is the heat transfer equation of the heating system, in which: q0Heat supply for the heat source; w and V are respectively a heat exchange station and a primary pipe network set; miAnd QjHeat dissipating capacity of the heat exchange station and the first-stage pipe network respectively; c. CpiThe specific heat capacity of the hot water at the side of the primary pipe network; m isiIs the flow rate of the heat exchange station; t isisAnd TirThe water supply temperature and the water return temperature of the primary network are respectively.
Further, in step S2, the wide area energy system partitioning method includes:
step S201, selecting an electricity-heat comprehensive energy system partition evaluation index, determining each evaluation index weight by an analytic hierarchy process, and further obtaining a comprehensive evaluation index value (generally, the comprehensive evaluation index value can be obtained by adopting the sum of each evaluation index);
step S202, according to different regional functions, combining geographic information such as bridges and roads, and preliminarily dividing the urban wide area energy system into different functional regions such as residential areas, commercial areas, public areas and industrial areas;
step S203 is based on the wide area energy system function partition, m function areas are preliminarily selected as core plots, surrounding areas are further merged, the whole city is divided into m areas, and the comprehensive evaluation index value of the electricity-heat comprehensive energy system of each area is calculated.
And S204, continuously repeating the step S203, and obtaining the value of m and the selection of the functional area by taking the optimal comprehensive evaluation index of the electric-thermal comprehensive energy system partition as a target.
Further, the evaluation indexes of the electric-thermal comprehensive energy system are as follows:
selecting inter-partition electrical connection intensity ICCI, intra-partition electrical connection intensity CECI and demand side response DSR (consisting of response willingness, response cost and response capacity) as electrical load evaluation indexes; and selecting the personnel density PD, the heat transfer coefficient lambda of the enclosure structure and the energy-saving consciousness ESC as heat load evaluation indexes.
The calculation method of each index comprises the following steps:
Figure BDA0003064504020000051
Figure BDA0003064504020000052
in the formula: a. b represents the number of any two nodes in the power grid; n is the total number of nodes; maA system partition set to which the node a belongs; dabIs the electrical distance between nodes a, b.
And (4) the other index demand side responses DSR, the personnel density PD, the enclosure structure heat transfer coefficient lambda and the energy-saving consciousness ESC all adopt a field investigation mode, and are respectively subjected to ten-tenth grading, so that the index values of the indexes are obtained.
Further, in step S2, the basic information of the power system and the thermal system of each sub-area includes:
the method comprises the following steps that (1) the topological structure of a power system, the capacity and the number of transformers of a transformer substation, the capacity and the length of a line, the active power and the reactive power of a load node and the load type are adopted, and historical electricity utilization data and electrical equipment information of users in a region are obtained;
the system comprises a thermodynamic system topological structure, the number of thermodynamic stations, the capacity of a pipe network and other thermodynamic equipment information, and historical heat consumption and building performance data of users in an area.
Further, in step S3, if the electric heating load prediction model adopts a sequence prediction method, the prediction model can be abstractly expressed as:
y＝f(X,S,t)
in the formula: y is the amount to be predicted; x is a vector formed by related influence factors, k related influence factors are provided, and X is (X)1,x2,...,xk) (ii) a S is a parameter vector of the prediction model, m parameters are provided, and S is equal to (S)1,s2,...,sm) (ii) a t is a time sequence number.
Further, in step S4, the method for calculating the power supply load available for each sub-area to supply heat includes:
Figure BDA0003064504020000061
in the formula: a. theASCTo a power supply capacity available for heating; a'TSCMaximum power supply capacity for the area; l isdThe electric loads used by the power distribution system in the area comprise loads of all electric equipment except the electric heaters; a. theTSCThe power supply capacity of the local transformer substation is provided; a. theNTCThe power supply amount is transferred for each area network, and the power supply amount is negative when the area network is transferred out and positive when the area network is transferred in.
Further, in step S5, the constraints of the electric-heating complementary heating system include:
power supply amount constraint conditions in the region:
Q(t)-Qh(t)≥ηAASC(t)
other constraints are as follows:
Figure BDA0003064504020000062
in the formula: q (t) represents the heat load demand vector of each area user at the time t; qh(t) represents a heat load vector provided by each heating power station provided by hot water central heating at the time t; eta represents the electrothermal conversion rate of the electric heating device; a. theASC(t) represents a power supply load vector available for heat supply at time t; p represents the running power of each device in the system; t represents the operating temperature of each device in the system; i represents the flow of the heating medium of each hot water pipeline; y represents each plant operating pressure.
Further, in step S5, the method for optimizing the optimal heat supply of each district heating power station includes:
the optimization objective function f (x) is:
Figure BDA0003064504020000071
wherein:
x1＝ψpZp+ψhZh
x2＝f(t,p,δ,ε)
Figure BDA0003064504020000072
in the formula: x is the number of1Is an economic index; x is the number of2Is a safety index; x is the number of3Is an environmental protection index; psip、ψhRespectively representing the prices of purchasing electric power and hot water for central heating; zp、ZhRespectively representing the quantity of purchased electric power and the quantity of heating by heating; t represents the device runtime; p represents the device operating power; δ represents a device reliability coefficient; epsilon is set toA reliability correction coefficient is prepared and is influenced by external environment factors; l ish、LaRespectively the quantities of solid pollutant emissions and gaseous pollutant emissions in the system operation process; q represents the total heat generated by the system.
Obtaining the weight index of each objective function as w by adopting an expert system1、w2、w3Then solving the model by adopting a particle swarm optimization algorithm to obtain an optimal solution set f (w)1x1,w2x2,w3x3) At this time:
Figure BDA0003064504020000073
in the formula:
Figure BDA0003064504020000074
the heat supply load of each regional heating power station in the regulation and control process is integrated; m is the hot water flow passing through the heat exchanger of the heating power station; t is tg、thRespectively the water supply temperature and the water return temperature; w is the number of thermal stations in each zone, and the superscripts 1, 2 … … w indicate the corresponding thermal stations.
The invention has the beneficial effects that:
the invention provides a novel subarea regulation and control method aiming at a mode of combining centralized heat supply and distributed heat supply (namely an electric-heat complementary heat supply system), on one hand, the impact of the access of large-range electric heating equipment on the safe and stable operation of the conventional power grid is relieved, the secondary investment caused by the power supply increment matching power grid is reduced, on the other hand, the impact of a clean fluctuating heat source on the conventional heat supply system is reduced through sub-area-level electric-heat complementary, and the overall flexibility of the electric-heat complementary process is improved.
Drawings
FIG. 1 is the main steps of the process of the present invention;
FIG. 2 is a schematic diagram of an indoor thermal dynamic model of a single thermal user;
FIG. 3 is a diagram of wide area energy system partitioning method steps;
FIG. 4 is a schematic diagram of the energy system partitioning results;
Detailed Description
The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. The technical scope of the present invention is not limited to the contents of the specification, and the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments, and thus the technical scope thereof must be determined according to the scope of the claims.
As shown in fig. 1, the zonal regulation and control method of the electric-heat complementary heating system based on the regional energy supply capacity mainly comprises the following steps:
step S1, a power distribution system power supply capacity model and a thermodynamic system mechanism simulation model are established, and the specific method comprises the following steps:
firstly, considering N-1 safety criteria, establishing a power supply capacity model of a power distribution system:
max ATSC＝∑Riψi
Figure BDA0003064504020000091
in the formula: a. theTSCThe maximum power supply capacity of the power distribution system is achieved; riThe rated capacity of a main transformer i is obtained; t isiIs the existing load factor of transformer i; psiiThe load factor of a main transformer i is obtained; n is a radical of∑The number of main transformers in the system; l isi,jShowing the communication relationship between the ith main transformer and the jth main transformer, when there is a relationship, Li,j1, otherwise Li,j＝0；Bi,jTransferring the load to a main transformer j when the main transformer i fails; rjRated capacity, R 'of main transformer j'jThe maximum allowable capacity of the main transformer j in a short time; ci,jThe limit capacity of the communication between the main transformer i and the main transformer j is obtained; psiminAnd psimaxRespectively the minimum load rate and the maximum load rate of a main transformer i; d is a given load of the region; z is the set of all main transformers in the area. Voltage constraints are ignored in this model due to the distribution network line angles in each region.
Then, establishing a thermodynamic system mechanism simulation model by adopting a graph theory method:
modeling a heat supply system based on graph theory, abstracting the connection position of equipment into connection nodes, abstracting lines between the two nodes into edges, simplifying each equipment in the system into a physical model according to actual system data, and establishing a topological structure of the heat supply system.
The method specifically comprises the following steps:
Figure BDA0003064504020000092
the above equation is a system of equations consisting of a mass conservation equation and an energy conservation equation, wherein: a is a node-branch incidence matrix of (n-1) x m, where n represents the number of nodes and m represents the number of branches; g is a branch flow vector; d is a node incoming and outgoing flow vector, the incoming flow is positive, and the outgoing flow is negative; a. theTIs a transposed matrix of the A matrix; p is a node head vector; the delta H is a pipe network water head descending vector; s is an n-stage pipe section resistance loss diagonal matrix; | G | is an n-stage pipe segment absolute flow diagonal matrix; DH is the water pump lift vector of the pipeline section, if do not contain the water pump, the water pump lift is marked as 0.
Figure BDA0003064504020000101
The above equation is the heat transfer equation of the heating system, in which: q0Heat supply for the heat source; w and V are respectively a heat exchange station and a primary pipe network set; miAnd QjHeat dissipating capacity of the heat exchange station and the first-stage pipe network respectively; c. CpiThe specific heat capacity of the hot water at the side of the primary pipe network; m isiIs the flow rate of the heat exchange station; t isisAnd TirThe water supply temperature and the water return temperature of the primary network are respectively.
Meanwhile, as shown in fig. 2, the power grid and the heat supply network are coupled at the end heat consumer, and the indoor thermal dynamic model of the single heat consumer is:
Figure BDA0003064504020000102
Figure BDA0003064504020000103
in the formula: t isin、Tout、Tm、TstoAnd ThRespectively the temperatures of indoor air, outdoor solid, indoor solid, electric heater and hot water central heating heat exchanger; c. Ca、cstoEquivalent heat capacities of indoor air and an electric heater are respectively set; rsto、Rh、RaAnd RmRespectively equal thermal resistances between indoor air-electric heater, indoor air-hot water central heating heat exchanger, indoor air-outdoor air and indoor air-indoor solid; phElectric power for heating equipment; eta is the electric-heat conversion efficiency of the electric heater.
Next, as shown in fig. 3, step S2 is to divide the wide area energy system into a plurality of sub-areas, and determine basic information of the power system and the thermal system of each sub-area, where the specific method is as follows:
firstly, selecting a power-heat comprehensive energy system partition evaluation index, determining each evaluation index weight by an analytic hierarchy process, and further obtaining a comprehensive evaluation index value, wherein the specific method comprises the following steps:
selecting inter-partition electrical connection intensity ICCI, intra-partition electrical connection intensity CECI and demand side response DSR (consisting of response willingness, response cost and response capacity) as electrical load evaluation indexes; and selecting the personnel density PD, the heat transfer coefficient lambda of the enclosure structure and the energy-saving consciousness ESC as heat load evaluation indexes.
Meanwhile, the calculation method of each index comprises the following steps:
Figure BDA0003064504020000111
Figure BDA0003064504020000112
in the formula: a. b represents the number of any two nodes in the power grid; n is the total number of nodes; maPartitioning the system to which the node a belongsGathering; dabIs the electrical distance between nodes a, b.
And (4) the other index demand side responses DSR, the personnel density PD, the enclosure structure heat transfer coefficient lambda and the energy-saving consciousness ESC all adopt a field investigation mode, and are respectively subjected to ten-tenth grading, so that the index values of the indexes are obtained.
Secondly, according to different regional functions, combining geographical information such as bridges and roads, preliminarily dividing the urban wide area energy system into different functional regions such as residential areas, business areas, public areas and industrial areas;
then, based on the wide area energy system function partition, preliminarily selecting m function areas as core plots, further merging surrounding areas, dividing the whole city into m areas, and calculating the comprehensive evaluation index value of the electricity-heat comprehensive energy system of each area (in the example, the comprehensive evaluation index value is obtained by adding all indexes).
And finally, continuously repeating the steps, and taking the optimal comprehensive evaluation index of the electric-thermal comprehensive energy system partition as a target (namely the evaluation index value is highest) to obtain the value of m and the selection of the functional area.
As shown in fig. 4, the power grid of the whole wide-area energy system is divided into A, B, C, D four areas, wherein each power grid partition contains a plurality of thermal power stations, and the thermal power grid is also divided into A, B, C, D four areas.
And then establishing an electric heating load prediction model:
y＝f(X,S,t)
in the formula: y is the amount to be predicted; x is a vector formed by related influence factors, k related influence factors are provided, and X is (X)1,x2,...,xk) (ii) a S is a parameter vector of the prediction model, m parameters are provided, and S is equal to (S)1,s2,...,sm) (ii) a t is a time sequence number.
Then, calculating the power supply load which can be used for heat supply of each sub-area based on an electric heat load prediction model, a power supply capacity model of a power distribution system and a thermodynamic system mechanism simulation model:
Figure BDA0003064504020000121
in the formula: a. theASCTo a power supply capacity available for heating; a'TSCMaximum power supply capacity for the area; l isdThe electric loads used by the power distribution system in the area comprise loads of all electric equipment except the electric heaters; a. theTSCThe power supply capacity of the local transformer substation is provided; a. theNTCThe power supply amount is transferred for each area network, and the power supply amount is negative when the area network is transferred out and positive when the area network is transferred in.
And then, starting to optimize the optimal heat supply distribution of the electric heating complementary heat supply system, wherein the power supply constraint conditions in the region are as follows:
Q(t)-Qh(t)≥ηAASC(t)
other constraints are as follows:
Figure BDA0003064504020000131
in the formula: q (t) represents the heat load demand vector of each area user at the time t; qh(t) represents a heat load vector provided by each heating power station provided by hot water central heating at the time t; eta represents the electrothermal conversion rate of the electric heating device; a. theASC(t) represents a power supply load vector available for heat supply at time t; p represents the running power of each device in the system; t represents the operating temperature of each device in the system; i represents the flow of the heating medium of each hot water pipeline; y represents each plant operating pressure.
The optimization objective function f (x) is:
Figure BDA0003064504020000132
wherein:
x1＝ψpZp+ψhZh
x2＝f(t,p,δ,ε)
Figure BDA0003064504020000133
in the formula: x is the number of1Is an economic index; x is the number of2Is a safety index; x is the number of3Is an environmental protection index; psip、ψhRespectively representing the prices of purchasing electric power and hot water for central heating; zp、ZhRespectively representing the quantity of purchased electric power and the quantity of heating by heating; t represents the device runtime; p represents the device operating power; δ represents a device reliability coefficient; epsilon is a device reliability correction coefficient and is influenced by external environmental factors; l ish、LaRespectively the quantities of solid pollutant emissions and gaseous pollutant emissions in the system operation process; q represents the total heat generated by the system.
Obtaining the weight index of each objective function as w by adopting an expert system1、w2、w3Then solving the model by adopting a particle swarm optimization algorithm to obtain an optimal solution set f (w)1x1,w2x2,w3x3) At this time:
Figure BDA0003064504020000141
in the formula:
Figure BDA0003064504020000142
the heat supply load of each regional heating power station in the regulation and control process is integrated; m is the hot water flow passing through the heat exchanger of the heating power station; t is tg、thRespectively the water supply temperature and the water return temperature; and w is the number of the heat station in each area.
Finally, verification proves that the regional energy supply capability-based electric-heat complementary heating system partitioned regulation and control method provided by the invention has a good effect in the system regulation and control process, can determine the optimal heating load setting of a thermodynamic system in a large-scale electric-heat complementary system, and can effectively improve the overall flexibility and energy saving rate of the electric-heat complementary process.

Claims (9)

1. A regional energy supply capacity-based electric heating complementary heating system partition regulation and control method is characterized by comprising the following steps:
step S1, establishing a power supply capacity model of a power distribution system and a mechanism simulation model of a thermodynamic system;
step S2, dividing the wide area energy system into a plurality of sub-areas, and determining the basic information of the electric power system and the thermodynamic system of each sub-area;
step S3, establishing an electric heating load prediction model of each sub-area, and calculating to obtain the electric load and the heat load of each sub-area;
step S4, based on the electric heating load prediction model and the power supply capacity model, evaluating to obtain the power supply load which can be used for electric heating of the power distribution system in each sub-area;
and step S5, determining the constraint conditions of the electric heating complementary heating system, and calculating the optimal heating load of the heating power station in each sub-area under different load requirements.
2. The zonal regulation and control method of electric-thermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S1,
the power distribution system power supply capacity model is as follows:
max ATSC＝∑Riψi
Figure FDA0003064504010000011
in the formula: a. theTSCThe maximum power supply capacity of the power distribution system is achieved; riThe rated capacity of a main transformer i is obtained; t isiIs the existing load factor of transformer i; psiiThe load factor of a main transformer i is obtained; n is a radical of∑The number of main transformers in the system; l isi,jShowing the communication relationship between the ith main transformer and the jth main transformer, when there is a relationship, Li,j1, otherwise Li,j＝0；Bi,jTransferring the load to a main transformer j when the main transformer i fails; rjRated capacity, R 'of main transformer j'jThe maximum allowable capacity of the main transformer j in a short time; ci,jThe limit capacity of the communication between the main transformer i and the main transformer j is obtained; psiminAnd psimaxRespectively the minimum sum of main transformer iA maximum load rate; d is a given load of the region; z is the set of all main transformers in the area;
the thermodynamic system mechanism simulation model is as follows:
modeling a heat supply system based on graph theory, abstracting the connection position of equipment into connection nodes, abstracting lines between the two nodes into edges, simplifying each equipment in the system into a physical model according to actual system data, and establishing a topological structure of the heat supply system;
the method specifically comprises the following steps:
Figure FDA0003064504010000021
the above equation is a system of equations consisting of a mass conservation equation and an energy conservation equation, wherein: a is a node-branch incidence matrix of (n-1) x m, where n represents the number of nodes and m represents the number of branches; g is a branch flow vector; d is a node incoming and outgoing flow vector, the incoming flow is positive, and the outgoing flow is negative; a. theTIs a transposed matrix of the A matrix; p is a node head vector; the delta H is a pipe network water head descending vector; s is an n-order pipeline resistance loss diagonal matrix; | G | is a diagonal matrix of the absolute value of the flow of the n-stage pipe section; DH is the water pump lift vector of the pipeline section, if do not contain the water pump, the water pump lift is marked as 0;
Figure FDA0003064504010000022
the above equation is the heat transfer equation of the heating system, in which: q0Heat supply for the heat source; w and V are respectively a heat exchange station and a primary pipe network set; miAnd QjHeat dissipating capacity of the heat exchange station and the first-stage pipe network respectively; c. CpiThe specific heat capacity of the hot water at the side of the primary pipe network; m isiIs the flow rate of the heat exchange station; t isisAnd TirThe water supply temperature and the water return temperature of the primary network are respectively.
3. The zonal regulation and control method of an electric-thermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S2, the zonal regulation and control method of the wide-area energy system is as follows:
step S201, selecting a power-heat comprehensive energy system partition evaluation index, determining each evaluation index weight by an analytic hierarchy process, and further obtaining a comprehensive evaluation index value;
step S202, according to different regional functions, combining geographic information, preliminarily dividing the urban wide area energy system into different functional regions, wherein the functional regions comprise residential areas, commercial areas, public areas and industrial areas;
step S203, based on the wide area energy system function partition, preliminarily selecting m function areas as core plots, further combining surrounding areas, dividing the whole city into m areas, and calculating the comprehensive evaluation index value of the electricity-heat comprehensive energy system of each area;
and S204, continuously repeating the step S203, and obtaining the value of m and the selection of the functional area by taking the optimal comprehensive evaluation index of the electric-thermal comprehensive energy system partition as a target.
4. The zonal regulation and control method of electric-heat complementary heating system based on regional energy supply capacity of claim 3,
wherein the evaluation indexes of the electric-thermal comprehensive energy system are as follows:
selecting inter-partition electrical connection intensity ICCI, intra-partition electrical connection intensity CECI and demand side response DSR (consisting of response willingness, response cost and response capacity) as electrical load evaluation indexes; selecting the personnel density PD, the heat transfer coefficient lambda of the enclosure structure and the energy-saving consciousness ESC as heat load evaluation indexes;
the calculation method of each index comprises the following steps:
Figure FDA0003064504010000041
Figure FDA0003064504010000042
in the formula: a. b denotes in the gridNumbering any two nodes; n is the total number of nodes; maA system partition set to which the node a belongs; dabIs the electrical distance between the nodes a and b;
and (4) the other index demand side responses DSR, the personnel density PD, the enclosure structure heat transfer coefficient lambda and the energy-saving consciousness ESC all adopt a field investigation mode, and are respectively subjected to ten-tenth grading, so that the index values of the indexes are obtained.
5. The zonal regulation and control method of an electrothermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S2, the basic information of the electric power system and the thermodynamic system of each subregion includes:
the method comprises the following steps that (1) the topological structure of a power system, the capacity and the number of transformers of a transformer substation, the capacity and the length of a line, the active power and the reactive power of a load node and the load type are adopted, and historical electricity utilization data and electrical equipment information of users in a region are obtained;
the system comprises a thermodynamic system topological structure, the number of thermodynamic stations, the capacity of a pipe network and other thermodynamic equipment information, and historical heat consumption and building performance data of users in an area.
6. The zonal regulation and control method of electric-thermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S3,
the electric heating load prediction model adopts a sequence prediction method, and the prediction model is abstractly expressed as:
y＝f(X,S,t)
in the formula: y is the amount to be predicted; x is a vector formed by related influence factors, k related influence factors are provided, and X is (X)1,x2,...,xk) (ii) a S is a parameter vector of the prediction model, m parameters are provided, and S is equal to (S)1,s2,...,sm) (ii) a t is a time sequence number.
7. The zonal regulation and control method of electric-thermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S4,
the power supply load calculation method for the power distribution system in each sub-area for electric heating comprises the following steps:
Figure FDA0003064504010000051
in the formula: a. theASCTo a power supply capacity available for heating; a'TSCMaximum power supply capacity for the area; l isdThe electric loads used by the power distribution system in the area comprise loads of all electric equipment except the electric heaters; a. theTSCThe power supply capacity of the local transformer substation is provided; a. theNTCThe power supply amount is transferred for each area network, and the power supply amount is negative when the area network is transferred out and positive when the area network is transferred in.
8. The zonal regulation and control method of an electrothermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S5, the constraint conditions of the electrothermal complementary heating system include:
power supply amount constraint conditions in the region:
Q(t)-Qh(t)≥ηAASC(t)
other constraints are as follows:
Figure FDA0003064504010000052
in the formula: q (t) represents the heat load demand vector of each area user at the time t; qh(t) represents a heat load vector provided by each heating power station provided by hot water central heating at the time t; eta represents the electrothermal conversion rate of the electric heating device; a. theASC(t) represents a power supply load vector available for heat supply at time t; p represents the running power of each device in the system; t represents the operating temperature of each device in the system; i represents the flow of the heating medium of each hot water pipeline; y represents each plant operating pressure.
9. The zonal regulation and control method of an electrothermal complementary heating system based on regional energy supply capacity of claim 1, wherein in step S5, the optimal heating load optimization method for the thermal power stations in each sub-region comprises:
the optimization objective function f (x) is:
Figure FDA0003064504010000061
wherein:
x1＝ψpZp+ψhZh
x2＝f(t,p,δ,ε)
Figure FDA0003064504010000062
in the formula: x is the number of1Is an economic index; x is the number of2Is a safety index; x is the number of3Is an environmental protection index; psip、ψhRespectively representing the prices of purchasing electric power and hot water for central heating; zp、ZhRespectively representing the quantity of purchased electric power and the quantity of heating by heating; t represents the device runtime; p represents the device operating power; δ represents a device reliability coefficient; epsilon is a device reliability correction coefficient and is influenced by external environmental factors; l ish、LaRespectively the quantities of solid pollutant emissions and gaseous pollutant emissions in the system operation process; q represents the total heat generated by the system;
obtaining the weight index of each objective function as w by adopting an expert system1、w2、w3Then solving the model by adopting a particle swarm optimization algorithm to obtain an optimal solution set f (w)1x1,w2x2,w3x3) At this time:
Figure FDA0003064504010000071
in the formula:
Figure FDA0003064504010000072
the heat supply load of each regional heating power station in the regulation and control process is integrated; m is the hot water flow passing through the heat exchanger of the heating power station; t is tg、thRespectively the water supply temperature and the water return temperature; and w is the number of the heat station in each area.
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