CN113191638A

CN113191638A - Electric heating coordination scheduling method and device considering heat transmission dynamic characteristics of heat supply network

Info

Publication number: CN113191638A
Application number: CN202110481506.9A
Authority: CN
Inventors: 徐飞; 郝玲; 闵勇; 陈群; 陈磊
Original assignee: Tsinghua University; Metering Center of State Grid Jibei Electric Power Co Ltd
Current assignee: Tsinghua University; Metering Center of State Grid Jibei Electric Power Co Ltd
Priority date: 2021-04-30
Filing date: 2021-04-30
Publication date: 2021-07-30
Anticipated expiration: 2041-04-30

Abstract

The invention provides an electric heating coordination scheduling method and device considering heat transmission dynamic characteristics of a heat supply network, wherein the method comprises the following steps: establishing an electric heating coordination scheduling model; establishing constraint conditions based on the heat transmission dynamic characteristics of a heat supply network and a multi-stage heat exchange process; obtaining the current value of a decision variable, and calculating through an electric heating coordinated scheduling model according to the current value of the decision variable and a constraint condition to obtain the current value of a target variable; determining a target interval of a target variable based on the set scheduling condition; feeding back and adjusting decision variables according to the relative relation between the current value of the target variable and the target interval, thereby realizing electric heating coordination scheduling; the influence of the transmission characteristics of the heat supply network on the target variable is definitely considered; according to the invention, heat transmission constraint is established based on a multistage heat exchange process, consideration factors of an electric heat coordination scheduling model are refined, and the model optimization result is more reliable and the model compatibility is better.

Description

Electric heating coordination scheduling method and device considering heat transmission dynamic characteristics of heat supply network

Technical Field

The invention relates to the technical field of electric heating coordination, in particular to an electric heating coordination scheduling method and device considering heat transmission dynamic characteristics of a heat supply network.

Background

The centralized heating network in the electric heating comprehensive energy system has passive heat storage capacity due to thermal inertia and can provide regulation capacity for the power system. In order to quantitatively evaluate the passive heat storage performance of the heat supply network and improve the consumption effect of renewable energy, an electric heating coordination optimization scheduling model containing the heat transmission dynamic characteristic of the heat supply network needs to be established. Taking the wind power consumption problem in the northeast China as an example, a transmission dynamic characteristic model of a pipe network is brought into an electric heating coordination optimization model, so that a relatively accurate heat supply network transmission delay rule can be obtained, a heat source is quantitatively and optimally controlled, the heat load of a user at the moment is provided in advance before delay, and the heat load of the user at the moment with heavy wind power generation and high heat load at night is also provided for a period of time in advance. Compared with the situation without considering the transmission delay, the method has the advantages that the heat supply amount and the output of the thermoelectric generator set are lower in the night time with large wind power generation and high heat load, and larger space is provided for wind power grid-connected consumption. For example, the heat load is highest and the wind power output is maximum at 3 am, if the transmission delay of a pipe network is not considered, the heat supply amount (namely, the heat output of the cogeneration unit) is highest at 3 am, the power output of the thermoelectric unit is maximum, and the wind power grid-connected space is possibly insufficient, so that the maximum wind abandon is achieved; if the transmission delay is considered, the maximum heat supply amount needs to be arranged in advance (for example, 2 am) by the heat source, so that the peak time of 3 am with the maximum wind power can be staggered, and the wind abandon amount of 3 am is reduced.

According to the method, the temperature dynamic distribution rule of each node of the pipe network can be obtained only by solving the heat transmission dynamic characteristic of the heat supply network, so that the real-time quantitative relation between the heat supply temperature of the heat source and the hot water temperature reaching a user is determined, the time of the heat supply network supplying heat in advance is determined, and accurate constraint is provided for electric heat coordination optimization.

Three problems exist in the existing electric heating coordination optimization considering the passive heat storage of a pipe network. First, a dynamic model of a heat supply network with both accuracy and compatibility with the power system is lacking. The traditional thermodynamic model cannot be directly substituted into electric heating coordination optimization, and the compatibility is poor. Second, many documents do not adequately consider the operational characteristics of components that are closely related to the operational characteristics of the heat supply network, based on the inaccuracy of the heat supply network model. The Jiangxianbao of Zhejiang university considers the time delay characteristic of the heat supply network and the variable flow variable temperature regulation into electric heat coordination optimization, but the adopted heat supply network model simplifies the temperature into the average heat supply temperature at the inlet and the outlet, does not consider the logarithmic average temperature difference in the heat exchange constraint, and cannot reflect the heat transmission and conversion process of each node in the thermodynamic system. Thirdly, heat exchange constraints among the primary network, the secondary network and the heat consumers are not considered, real-time change of indoor temperature is not obtained, or only heat exchange balance is considered and a logarithmic mean temperature difference equation is ignored, so that the obtained theoretical heat supply amount is inconsistent with the reality, and accurate constraints can not be provided for making heat supply and power supply plans.

In the above-mentioned problem of the electric heat coordination optimization model considering the dynamic characteristics of the heat supply network, the heat supply network model determines the real-time mapping relationship between the heat supply temperature of the heat source and the temperature of the heat medium reaching the user. The change rule of the primary network and the secondary network in the thermodynamic system, the change rule of the secondary network and the indoor temperature of the user also greatly depends on the precision of the heat supply network dynamic model. Therefore, analysis of the heat transmission dynamic characteristics of the pipe network is the basis for realizing dynamic adjustment and electric heat coordination optimization of the heating system. Only a heat transmission dynamic model which is good in precision and compatible with an electric power system algorithm is established, a pipe network thermal dynamic topological model can be established, and the heat exchanger and the operation characteristics of heat users are further combined, so that the dynamic response relation between a heat source and each user in a complex pipe network is accurately mastered, the purpose of quantitatively adjusting heat supply and generator set operation parameters according to a renewable energy consumption target is realized, and a theoretical basis is provided for exploring and utilizing the natural adjustment potential of the pipe network in an electric heating comprehensive energy system.

In summary, the method and the device for electric heat coordination scheduling considering the heat transmission dynamic characteristics of the heat supply network are provided, based on the calculation of the multi-stage heat exchange process, the problems that in the prior art, the compatibility/precision is insufficient, the heat transmission and conversion process of each node in the thermodynamic system cannot be reflected, and the heat exchange constraint between the primary network/the secondary network/the heat users is not considered can be solved, and the method and the device have high practical value and significance.

Disclosure of Invention

Aiming at the problems in the prior art, the invention provides an electric heating coordination scheduling method and device considering the heat transmission dynamic characteristics of a heat supply network.

The invention provides an electric heating coordination scheduling method considering heat transmission dynamic characteristics of a heat supply network, which comprises the following steps:

establishing an electric heating coordination scheduling model;

establishing heat supply network constraint based on the heat supply network heat transmission dynamic characteristic and the multistage heat exchange process as constraint conditions;

obtaining the current value of a decision variable, and calculating through an electric heating coordinated scheduling model according to the current value of the decision variable and a constraint condition to obtain the current value of a target variable;

determining a target interval of a target variable or a target value of the target variable based on the set scheduling condition;

feeding back and adjusting the decision variable according to the relative relation between the current value of the target variable and the target interval or according to the difference value between the current value of the target variable and the target value, thereby realizing electric heating coordinated scheduling;

the electric heating coordination scheduling model is a model for adjusting a target variable through a decision variable under a set constraint condition;

the decision variables comprise any one or any combination of more of hourly heat source heat supply temperature, heat supply pipe network initial temperature, heat supply quantity of the thermoelectric unit, electric output, thermal power unit output and hourly wind power output;

the target variable comprises any one or any combination of more of air abandonment amount, heat deviation amount, heat supply amount, heat loss, user heat gain amount, user indoor temperature and wind power consumption amount;

the multistage heat exchange process comprises a heat transmission process and/or a heat exchange process of a heat supply pipe network; the heat transmission process of the heat supply pipe network comprises a heat transmission process of a heat medium supply pipeline and/or a heat transmission process of a heat medium recovery pipeline; the heat exchange process comprises any one or any combination of a heat exchange process between a primary network and a secondary network, a heat exchange process between the secondary network and a user, and a heat exchange process between the user and an outdoor environment.

According to the electric heat coordination scheduling method considering the heat transmission dynamic characteristics of the heat supply network, the heat supply network constraint comprises a first function corresponding to a heat exchange process:

in the formula:

T_c，in，tthe inlet temperature of the heat medium of the secondary network at the time t; t is_outdoor，tIs the outdoor atmospheric temperature at time t; t is_h，in，tThe inlet temperature of the heat medium of the primary network at the time t;

T_h，out，tthe outlet temperature of the primary network heat medium at the moment t; g_cMass flow of the secondary network heat medium; g_hMass flow rate of the primary net heat medium;

T_user，tthe indoor temperature of the user at the moment t;

s_h，c、s_evl、s_c，user、s_12hare respectively:

wherein e is the base of the natural logarithm; k is a radical of_h，cThe heat exchange coefficient of the primary network heat exchanger and the secondary network heat exchanger is obtained; a. the_h，cThe heat exchange area of the primary net and the secondary net heat exchanger is shown; c is the specific heat capacity of the heat medium; k is a radical of_evlAverage heat exchange coefficient of the building envelope for the user; a. the_evlAverage heat exchange area of the building envelope for the user; k is a radical of_c，userThe heat exchange coefficient of the radiator between the secondary network and the user is shown; a. the_c，userThe heat exchange area of the radiator between the secondary network and the user.

According to the electric heating coordinated scheduling method considering the heat transmission dynamic characteristics of the heat supply network, the heat supply network constraint comprises a second function corresponding to the heat transmission process of the heat supply network:

in the formula, phi_m，nThe outlet excess temperature is the outlet excess temperature with a space node of m and a time node of n; i. j is a space node serial number and a time node serial number respectively; the surplus temperature refers to the difference between the temperature of the heat medium and the temperature of the soil;

parameter A_n、B_nAnd A'_nSatisfies the following conditions:

wherein, C is a permutation and combination operator;

the parameters a and r satisfy:

in the formula, rho and c are respectively the density of the heat medium and the specific heat capacity of the heat medium; A. d is the cross-sectional area and the diameter of the pipeline respectively; v is the fluid flow rate; k is the heat leakage coefficient between the fluid in the pipeline and the soil; x and tau are respectively a space variable and a time variable.

According to the electric heat coordination scheduling method considering the heat transmission dynamic characteristic of the heat supply network, the constraint condition further comprises the constraint of a cogeneration unit;

the constraint of the cogeneration unit comprises a thermoelectric ratio constraint, a climbing constraint, a unit limit output constraint, a heat source water supply temperature constraint and a scheduling period constraint;

the thermoelectric ratio constraints are:

in the formula, epsilon is a set thermoelectric ratio of the cogeneration unit; q_CHP，tThe thermal output of the cogeneration unit at the moment t; p_CHP，tThe electric output of the cogeneration unit at the moment t;

the climbing restriction is as follows:

in the formula, P_CHP，up、P_CHP，downRespectively restricting the upward and downward climbing of the set cogeneration unit; p_CHP，t-1The power output of the cogeneration unit at the time of t-1; p_thp，up、 P_thp，downRespectively performing upward and downward climbing constraints on the set thermal power cogeneration unit; p_thp，t、 P_thp，t-1The thermal power cogeneration unit power output at the time t and the time t-1 respectively; wherein the t-1 moment is the last moment of the t moment;

the unit ultimate output restriction package is as follows:

in the formula, P_CHP，max、P_CHP，minThe maximum power output and the minimum power output of the cogeneration unit are respectively; p_thp，max、P_thp，minRespectively the maximum and minimum power output of the thermal power cogeneration unit;

the heat source water supply temperature constraint is as follows:

40℃≤T_source，t≤90℃

in the formula, T_source，tThe temperature of the heat source water supply at the time t;

the scheduling period constraint means that the thermal scheduling period is adjusted based on a set power scheduling period value, so that the electric heating coordination scheduling period, the thermal scheduling period and the power scheduling period are consistent and are set power scheduling period values.

According to the electric heating coordination scheduling method considering the heat transmission dynamic characteristic of the heat supply network, the constraint condition further comprises the constraint of the power grid and the wind generating set;

the power grid and wind power generator set constraints comprise power grid power balance constraints, wind power limit output constraints and line capacity constraints;

the power balance constraint of the power grid is as follows:

P_CHP，t+P_wind，t＝P_user，t+P_pump，t

in the formula, P_CHP，tThe electric output of the cogeneration unit at the moment t; p_wind，tThe actual wind power output at the moment t is obtained; p_user，tThe load is the residential electricity load at the moment t; p_pump，tThe power consumption of the circulating pump at the time t;

the wind power limit output constraint is as follows:

P_wind，t≤P_{wind，max，t}

in the formula, P_{wind，max，t}The wind power limit output at the time t is obtained;

the line capacity constraints are:

P_tr，min≤P_tr，t≤P_tr，max

in the formula, P_tr，tThe transmission capacity of the power grid at the moment t; p_tr，min、P_tr，maxThe minimum and maximum transmission capacities of the power grid at the moment t are respectively.

According to the electric heating coordination scheduling method considering the heat transmission dynamic characteristic of the heat supply network, the scheduling condition is that the air abandoning amount at all times in the whole day is minimum; the target variable corresponding to the scheduling condition with the minimum air abandon amount at all times in the whole day is the sum of the air abandon amounts, and the corresponding target value is 0.

According to the electric heat coordination scheduling method considering the heat transmission dynamic characteristics of the heat supply network, the scheduling condition is that the absolute value of the total heat deviation of the whole day is minimum, the target variable corresponding to the scheduling condition with the minimum absolute value of the total heat deviation of the whole day is the sum of the absolute values of the heat deviations, and the corresponding target value is 0.

The invention also provides an electric heating coordination scheduling device considering the heat transmission dynamic characteristics of the heat supply network, which comprises a model establishing module, a constraint condition setting module, a calculating module, a scheduling module and a feedback adjusting module;

the model establishing module can establish an electric heating coordination scheduling model;

the constraint condition setting module can establish heat transmission constraint based on a multi-stage heat exchange process to serve as a constraint condition;

the calculation module can obtain the current value of the decision variable, and according to the current value of the decision variable and the constraint condition, the current value of the target variable is calculated and obtained through an electric heating coordination scheduling model;

the scheduling module can determine a target interval of a target variable or a target value of the target variable based on a set scheduling condition;

the feedback regulation can feed back and regulate decision variables according to the relative relation between the current value of the target variable and the target interval or according to the difference value between the current value of the target variable and the target value, so that the electric heating coordinated dispatching is realized;

The invention further provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein when the processor executes the program, the steps of the electric heating coordination scheduling method considering the dynamic characteristics of heat transmission of the heat supply network are realized.

The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the steps of the method for coordinated electric and heat scheduling taking into account the thermal transfer dynamics of a heat network as described in any of the above.

According to the electric heating coordination scheduling method and device considering the heat transmission dynamic characteristics of the heat supply network, the heat transmission constraint is established based on the multi-stage heat exchange process, the heat transmission and conversion process of each node in a thermodynamic system is reflected, and the heat exchange constraint between a primary network/a secondary network/a heat user is established, so that the consideration factors of an electric heating coordination scheduling model are refined, the model optimization result is more reliable, and the model compatibility is better.

Drawings

In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

FIG. 1 is a schematic flow chart of an electric heat coordination scheduling method taking account of heat transmission dynamic characteristics of a heat supply network provided by the present invention;

FIG. 2 is a schematic diagram of a heat exchange process of multiple loops of a heat supply pipe network according to an embodiment of the present invention;

FIG. 3 is a schematic view of a buried pipe provided by an embodiment of the present invention;

FIG. 4 is a schematic diagram of a preliminary thermoelectric comparison of a heat supply network according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of an equivalent thermal circuit of a heat supply network provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of an electric heating integrated energy system for a certain area according to an embodiment of the present invention;

fig. 7 is a schematic diagram of a time-by-time electrical load and wind power limit output curve of a single user node case provided in the embodiment of the present invention;

FIG. 8 is a schematic diagram of a time-by-time outdoor temperature curve for a single user node case according to an embodiment of the present invention

FIG. 9 is a schematic view of a time-lapse heating temperature curve of various comparative examples provided in the examples of the present invention;

FIG. 10 is a schematic graph of a time-lapse indoor temperature profile for various comparative examples provided by examples of the present invention;

FIG. 11 is a schematic view of a time-wise wind abandon curve of different comparative examples provided by the embodiment of the present invention;

fig. 12 is a schematic structural diagram of an electronic device provided in the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The method and apparatus for coordinating and scheduling electric heating taking into account the thermal transmission dynamic characteristics of the heat supply network according to the present invention will be described with reference to fig. 1-11.

The definition of 'taking account of the multi-stage heat exchange process' in the subject matters of the invention and the embodiments refers to that in the modeling process of the electric heating coordination scheduling model and the electric heating coordination scheduling process, the multi-stage heat exchange process of the heat supply pipe network part is considered, namely an equation is established on the basis of the multi-stage heat exchange process to restrict the electric heating coordination scheduling.

As shown in fig. 1, an embodiment of the present invention provides an electric heating coordination scheduling method considering heat transfer dynamic characteristics of a heat supply network, including:

step 1, establishing an electric heating coordination scheduling model;

step 2, establishing heat supply network constraint based on the heat supply network heat transmission dynamic characteristic and the multi-stage heat exchange process as constraint conditions;

step 3, obtaining the current value of the decision variable, and calculating to obtain the current value of the target variable through an electric heating coordination scheduling model according to the current value of the decision variable and the constraint condition;

step 4, determining a target interval of a target variable or a target value of the target variable based on the set scheduling condition;

step 5, feeding back and adjusting decision variables according to the relative relation between the current value of the target variable and the target interval or according to the difference value between the current value of the target variable and the target value, thereby realizing electric heating coordination scheduling;

The beneficial effect of this embodiment lies in:

the heat transmission constraint is established based on the multi-stage heat exchange process, the heat transmission and conversion process of each node in the thermodynamic system is reflected, and the heat exchange constraint between the primary network/the secondary network/the heat users is established, so that the consideration factors of the electric heat coordination scheduling model are refined, the model optimization result is more reliable, and the model compatibility is better.

According to the above embodiment, in the present embodiment:

the heat grid constraints include a first function corresponding to a heat exchange process:

in the formula:

T_user，tthe indoor temperature of the user at the moment t;

s_h，c、s_evl、s_c，user、s_12hare respectively:

The derivation of the first function is as follows.

As shown in fig. 2, the heat transfer from the primary network heat medium to the user involves three layers of heat exchange processes, namely, a primary network and a secondary network, a secondary network heat medium and a heat user, and a heat user and the external environment; the heat exchange equations of the three heat exchange loops are listed in sequence according to the schematic diagram of the heat exchange process of the multiple loops of the heat supply network shown in fig. 2.

(1) Heat exchange process between primary net and secondary net

The formula (1a), the formula (1b), the formula (1c) and the formula (1d) are respectively a heat exchange quantity equation, a logarithmic mean temperature difference equation, a heat balance equation of a primary network heat medium and a heat balance equation of a secondary network heat medium between the primary network and the secondary network. The heat exchanger is arranged in a countercurrent mode, the four modes are combined, and the expression of the outlet temperature of the primary network and the outlet temperature of the secondary network with respect to the inlet temperature of the primary network and the secondary network can be solved.

Q_h，c，t＝k_h，cA_h，cΔT_{m，h，c，t} (1a)

Q_h，c，t＝cG_h(T_h，in，t-T_h，out，t) (1c)

Q_h，c，t＝cG_c(T_c，out，t-T_c，in，t) (1d)

In the formula, Q_h，c，tIs the heat exchange amount between the primary and secondary nets, k_h，cIs the heat exchange coefficient of the heat exchanger between the primary and secondary networks, A_h，cIs the heat exchange area, delta T, of the primary and secondary internetwork heat exchangers_{m，h，c，t}Is the logarithmic mean temperature difference, G, of the heat exchanger between the primary and secondary networks_h、G_cRespectively represents the mass flow rate, T, of the primary network heat medium water and the secondary network heat medium water_h，in，t、T_h，out，tInlet and outlet temperatures, T, of primary network heating medium water respectively_c，in，t、T_c，out，tThe inlet temperature and the outlet temperature of the secondary network heating medium water are respectively.

(2) Heat exchange process between secondary network and heat consumer

And (2) analyzing the heat exchange process of the heat user as a research object, namely the heat release amount of the secondary network to the user is equal to the heat release amount of the user and the outdoor, wherein the formulas (1e), (1f), (1g) and (1h) are a heat exchange amount equation, a logarithmic mean temperature difference equation, a secondary network heat medium water-heat balance equation and a user and external heat exchange balance equation between the secondary network and the user respectively.

Q_c，user，t＝k_c，userA_c，userΔT_{m，c，user，t} (1e)

Q_c，user，t＝cG_c(T_cs，t-T_cr，t) (1g)

Q_c，user，t＝k_evlA_evl(T_user，t-T_outdoor，t) (1h)

Wherein Q is_c，user，tIndicates the heat exchange amount between the secondary network heat medium water and the user, k_c，user、A_c，userRespectively represents the heat exchange coefficient and the heat exchange area, delta T, of the radiator between the heat medium water of the secondary network and the user_{m，c，user，t}Is the logarithmic mean temperature difference, T, of the heat exchanger between the primary and secondary networks_cs，t、T_cr，tThe temperature of the secondary network heat medium water supply and the return water at the time t are respectively; k is a radical of_evlRepresents the average heat exchange coefficient of the building envelope, A_evlRepresenting the average heat exchange area of the building envelope; t is_user，tFor the user's indoor temperature, T_outdoor，tIs the outdoor atmospheric temperature.

(3) Primary network, secondary network and user heat exchange process simultaneous solving method

For the multi-loop heat exchange process, many intermediate parameters exist in calculation, such as the temperature of a heat medium water inlet and outlet of an intermediate loop. Taking the heat exchange process shown in fig. 2 as an example, the supply and return water temperature of the secondary network is determined by both the primary network heat exchange equation and the user heat exchange equation. Therefore, the relation between the primary network water supply temperature and the indoor temperature and other parameters is solved through the joint formula (1a) to the formula (1 h).

Supply temperature T of hot media water at user side_cs，tNamely the outlet temperature T of the secondary network heating medium water of the heating plant_c，out，tReturn temperature T of heat medium water at user side_cr，tNamely the inlet temperature T of the secondary network heat medium water of the heat supply station_c，in，tAs shown in formula (1 i).

Therefore, the inlet and outlet temperature difference (T) of the secondary network heat medium water at the heating station side_c，out，t-T_c，in，t) Temperature difference (T) of water supply and return of secondary network at user side_cs，t-T_cr，t) Expressed as shown in formula (1 j):

T_c，out，t-T_c，in，t＝T_cs，t-T_cr，t (1j)

will T_c，in，tSubstituting to obtain the indoor temperature T_user，tAbout the temperature T of a heat medium water inlet of a primary network of a heat exchange station_h，in，tOutdoor atmospheric temperature T_outdoor，tAnd the relation with the heat exchange parameters of the heat exchanger of the heat exchange station, the heat exchange parameters of the radiator and the heat exchange parameters of the user enclosure structure is shown as a formula (1 k).

The dynamically changed parameter in the formula (1k) is only the temperature T of the heat exchange station primary network heat medium water inlet_h，in，tAnd outdoor atmospheric temperature T_outdoor，tAnd the variable intermediate variable related to the secondary network is not contained, so that the variable intermediate variable can be directly used in an electric heating coordination optimization model.

Further simplifying the equation (1k) and establishing the equation (1L).

The formula (1k) can be rewritten as the formula (1.1), the formula (1.2) and the formula (1.3)

The beneficial effect of this embodiment lies in:

the heat transmission and heat exchange process in the pipe network comprises five processes: the heat transmission process comprises heat transmission of a water supply pipeline, heat exchange of a primary network and a secondary network, heat exchange of the secondary network and a user, heat exchange of the user and an outdoor environment and heat transmission of a water return pipeline. In the embodiment, a step-by-step heat exchange equation is established for each node, and a pipe network thermodynamic dynamic model considering pipe network heat transmission is established, so that in the prior art, even if heat exchange constraint is considered in electric heat coordination optimization considering a pipe network, a secondary network is not considered generally, but only a simple heat exchange process between a primary network and the secondary network is considered, for example, heat exchange between heat medium water of the secondary network and users is ignored, and the like. In the embodiment, a three-layer heat exchange process is considered comprehensively, a heat balance and heat exchange model containing three-layer heat exchange is established aiming at the problem of multi-loop heat exchange, and an expression of indoor temperature about primary network heat supply temperature and outdoor temperature is directly obtained.

According to any of the embodiments described above, in this embodiment:

the heat supply network constraints include a second function corresponding to a heat transfer process of the heat supply network:

parameter A_n、B_nAnd A'_nSatisfies the following conditions:

wherein, C is a permutation and combination operator;

the parameters a and r satisfy:

Specifically, the derivation process of the second function is as follows.

Referring to the directly-buried pipe shown in fig. 3, under a set equivalent thermal circuit condition, for a fluid infinitesimal with a length dx in a heat supply pipe network pipeline in a soil environment, considering the change of water temperature along with the extension direction x and time τ of the pipeline, a one-dimensional energy conservation equation is established and is expressed as formula (2 a):

in the formula (2a), rho and c are respectively the density of the heat medium and the specific heat capacity of the heat medium; a. D is the cross-sectional area and the diameter of the pipeline respectively; t is the temperature of the fluid infinitesimal; v is the fluid flow rate; k is the heat leakage coefficient between the fluid in the pipeline and the soil; t is_soilIs the soil temperature; x and tau are respectively a space variable and a time variable;

the equivalent thermal circuit conditions comprise constant soil temperature, same fluid temperature on the same cross section and positive direction taking the extending direction of the heat supply pipe network pipeline as an x axis;

for each term on the left side of the medium number in the formula (2a), integrating in the pipeline extending direction x and time τ, and applying a step difference format, a first-order windward difference format and an implicit difference format to the first term, the second term and the third term on the left side of the medium number in the formula (2a) respectively to obtain a formula (2 b):

in the formula (2b), T_i，jRepresenting the temperature of the ith pipeline space node in the numerical calculation at the jth moment;

referring to the preliminary thermoelectric analogy diagram of the heat supply network shown in fig. 4, based on equation (2b), a linear equivalent thermal circuit is established:

regarding each fluid micro element as an equivalent thermoelectric node in an equivalent thermal circuit, and marking the equivalent thermoelectric nodes which are not end points and are positioned at the ith space node and the jth time node as T'_i，jThen T'_i，jThe equivalent thermal circuit is connected with other parts of the equivalent thermal circuit in at least four directions, and the directions are respectively marked as a first direction, a second direction, a third direction and a fourth direction;

let equivalent thermoelectric node T'_i，jTemperature of itself is T_i，j，T′_i，jThe self internal energy of the corresponding fluid infinitesimal element can be equivalent to one end and T'_i，jCapacitor C connected and grounded at one end_i，jThen the first direction is from T'_i，jWarp C_i，jThe direction of grounding;

T′_i，jthe heat convection between the corresponding fluid micro-element and the immediately adjacent fluid micro-element can be equivalent to one end and T'_i，jConnected, one end of which is connected with T'_i-1，jConnected power supply E_i，jThen the second direction is from T'_i，jWarp E_i，jGet T'_i-1，jThe direction of (a);

temperature T of soil_soilCan be equivalent to a constant potential point T_s，T′_i，jThe thermal resistance of the heat exchange between the corresponding fluid micro element and the soil can be equivalent to one end and T'_i，jConnection, one end and constant potential point T_sConnected resistor R_i，jThen the third direction is from T'_i，jWarp R_i，jConnect T_SThe direction of (a);

T′_i，jthe thermal convection between the corresponding fluid infinitesimal and the next adjacent fluid infinitesimal can be equivalent to one end and T'_i，jConnected, one end of which is connected with T'_i+1，_jConnected power supply E_i+1，jThen the fourth direction is from T'_i，jWarp E_i+1，jGet T'_i+1，jThe direction of (a);

referring to fig. 5, a linear equivalent thermal circuit is simplified:

prepared from T'_i，jThe self internal energy of the corresponding fluid element is recorded as a vector q in the first direction₁(ii) a Prepared from T'_i，jThe thermal convection between the corresponding fluid infinitesimal and the immediately preceding adjacent fluid infinitesimal is denoted as a vector q in the second direction₂(ii) a Prepared from T'_i，j+1 Heat loss between the corresponding fluid infinitesimal element and the soil is recorded as the third partyUpward vector q₃；

Q is to be₂Decomposed into vectors q_2aAnd vector q_2bAnd let q be_2bAnd q is₁Equal in size and opposite in direction, the simplified T_i，j+1Is T_i-1，jThe function of (a) is recorded as the recursion relation of the equivalent thermal circuit;

eliminating the temperature measurement of the intermediate node through the recursive relationship of the equivalent thermal circuit, establishing an equivalent thermal circuit equation and recording as a second function;

the second function includes equations (2.1) and (2.2):

the beneficial effect of this embodiment lies in:

a piecewise function of the outlet excess temperature (excess temperature, i.e., the difference between the fluid temperature and the soil temperature) is established with time, inlet temperature, and initial temperature as arguments. Due to A_n、B_nThe model is a linear equation and can be directly used for electric heating coordination optimization. The problem of pipeline export temperature equation and electric heat coordination system incompatible in the prior art is solved.

According to any of the embodiments described above, in this embodiment:

the constraint condition further comprises a cogeneration unit constraint;

the thermoelectric ratio constraints are:

the climbing restriction is as follows:

the unit ultimate output restriction package is as follows:

the heat source water supply temperature constraint is as follows:

40℃≤t_source，t≤90℃

The beneficial effect of this embodiment lies in:

the embodiment is different from the prior art, the optimization of the power system is not taken as a main body, the operation characteristics and the evaluation indexes of the thermodynamic system are comprehensively considered, and the compatibility of the electric heating coordination scheduling method considering the heat transmission dynamic characteristics of the heat supply network can be further improved.

According to any of the embodiments described above, in this embodiment:

the constraint conditions also comprise the constraints of a power grid and a wind generating set;

the power balance constraint of the power grid is as follows:

P_CHP，t+P_wind，t＝P_user，t+P_pump，t

the wind power limit output constraint is as follows:

P_wind，t≤P_{wind，max，t}

the line capacity constraints are:

P_tr，min≤P_tr，t≤P_tr，max

The beneficial effect of this embodiment lies in:

According to any of the embodiments described above, in this embodiment:

the scheduling condition is that the air abandoning amount at all the time in the whole day is minimum; the target variable corresponding to the scheduling condition with the minimum air abandon amount at all times in the whole day is the sum of the air abandon amounts, and the corresponding target value is 0.

The beneficial effect of this embodiment lies in:

electric heating coordination scheduling is carried out aiming at the abandoned wind quantity, and wind power consumption is maximized on the aspect of an electric power system.

According to any of the embodiments described above, in this embodiment:

the scheduling condition is that the absolute value of the total thermal deviation of the whole day is minimum, the target variable corresponding to the scheduling condition with the minimum absolute value of the total thermal deviation of the whole day is the sum of the absolute values of the thermal deviations, and the corresponding target value is 0.

The beneficial effect of this embodiment lies in:

and electric heat coordination scheduling is carried out according to the heat deviation, so that the overall thermal comfort of a user is promoted on the aspect of a thermodynamic system.

According to any of the embodiments described above, in this embodiment:

in order to quantitatively evaluate the heat storage performance of the heat supply network in the electric heating integrated energy system and improve the effect of renewable energy consumption, an electric heating coordination optimization scheduling model considering the heat transmission dynamic characteristics of the heat supply network needs to be established.

At present, a common semi-theoretical semi-empirical model of a heat supply network in an electric heating coordination optimization model cannot accurately calculate the dynamic temperature change rule of the heat supply network and cannot obtain the accurate mapping relation between the heat supply temperature of a heat source and the indoor temperature of a heat user; it is difficult to provide accurate constraints for the heating plan and the power supply plan, and large deviation is brought to quantitative evaluation of the effect of improving renewable energy sources of the heat supply network.

In view of the above problems, the present embodiment provides an electric heating coordination optimization scheduling model considering dynamic characteristics of a heat supply network based on an existing heat supply network linearization matrix model. The optimization model comprehensively considers the operation characteristics of a heat supply network, a heat exchanger closely related to the operation of the heat supply network, a heat user and the like, comprehensively considers the operation evaluation indexes of an electric power system and a thermodynamic system by taking the maximum optimal thermal comfort and wind power consumption as a two-stage optimization target, and provides a basis for analyzing and evaluating the influence of the thermal inertia of the heat supply network on the electric heat coordination optimization operation effect.

Finally, a typical change example and a comparative example are selected, a heat supply plan and a power generation plan of the electric heating comprehensive energy system are optimized in real time and quantitatively according to heat transmission characteristics of a heat supply network, and a conclusion that influences of dynamic characteristics of heat transmission of the heat supply network on wind power consumption and thermal comfort are taken into consideration is obtained.

Specifically, the embodiment provides a linearization model considering the heat transfer dynamic characteristic of the heat supply network on the basis of the existing heat supply network linearization model, and has the requirements of precision and compatibility; and physical characteristic models of thermodynamic system components closely related to the operation of a water supply network, such as a primary network and a secondary network, a secondary network and a heat consumer, a heat consumer and a three-level heat exchange model of an outdoor environment and the like, are established. On the basis, an electric heating coordination optimization scheduling model considering a heat transmission dynamic model of a heat supply network and a heat exchange process is constructed, the hourly heat supply temperature of a heat source is taken as a decision variable, and the maximum optimal thermal comfort and wind power consumption is an optimal target. And finally, selecting a typical variation example and a comparative example, and quantitatively researching the influence of the operation characteristics of the heat supply network on the electric heating coordination optimization operation effect.

The heat transmission and heat exchange process in the pipe network comprises five processes: the heat transmission process comprises heat transmission of a water supply pipeline, heat exchange of a primary network and a secondary network, heat exchange of the secondary network and a user, heat exchange of the user and an outdoor environment and heat transmission of a water return pipeline. In the embodiment, a step-by-step heat exchange equation is mainly established for each node, and a pipeline heat transmission-based pipeline network thermodynamic dynamic model is established.

The calculation process of the thermodynamic dynamic model of the whole pipe network comprises the following steps:

writing all pipe sections as an expression of the outlet temperature with respect to the inlet temperature and the heat transfer contribution matrix; then listing a heat balance equation of the pipe sections connected end to end at the intersection node and a mixed temperature equation of the mixed node column; finally, a heat transmission equation of each pipe section is combined with a heat balance and mixing temperature equation, and the inlet temperature (namely the heat supply temperature of a heat source) of the pipe network and the flow rate of the heat medium water are given; the thermodynamic characteristics such as the temperature dynamic change rule of each user node, the pipeline section along the way and the like can be obtained, and the expression of the characteristics is shown in an expression (2.1) and an expression (2.2).

The heat is transferred from the primary network heat medium water to the users, which relates to three heat exchange processes, namely, a primary network and a secondary network, a secondary network heat medium water and heat users, and a heat user and an external environment (neglecting the heat exchange process of the secondary network and the environment). The heat balance and heat exchange model comprising three layers of heat exchange is established aiming at the problem of multi-loop heat exchange by comprehensively considering the three-layer heat exchange process in the chapter, and the expression of the indoor temperature about the primary network heat supply temperature and the outdoor temperature is directly obtained.

According to the schematic diagram of the multi-loop heat exchange process shown in FIG. 2, the heat exchange equations of three heat exchange loops, i.e., the equations (1a) to (1h), are listed in sequence.

After the solutions of the joint vertical type (1a) to the formula (1h) are solved and simplified, the indoor temperature T can be obtained_user，tAbout the temperature T of a heat medium water inlet of a primary network of a heat exchange station_h，in，tOutdoor atmospheric temperature T_outdoor，tThe relationship with the heat exchange parameters of the heat exchanger of the heat exchange station, the heat exchange parameters of the radiator and the heat exchange parameters of the user enclosure structure is shown in the formula (1.1), the formula (1.2) and the formula (1.3)

Electric heating coordination optimization modeling considering the overall operation of the pipe network and the system is performed below.

By taking the problem of wind abandonment in wind power consumption in winter in northeast China as a background, a regional electric heating comprehensive energy system comprising a centralized heating system, a wind power plant, a thermal power generating unit and a cogeneration unit is taken as an example, and an electric heating coordination optimization model considering the overall operation of a pipe network and a system is established. The optimization scheduling model does not only take power system optimization as a main body, but comprehensively considers the operating characteristics and evaluation indexes of the thermodynamic system.

Firstly, the regional electric heating integrated energy system and the electric heating coordination optimization model are summarized as follows.

Fig. 6 is a structure of a regional electric heating integrated energy system case in a certain area, which mainly comprises a generator set, a power grid, a heat supply pipe network, a heat exchanger, an electric user, a heat user and the like, wherein the generator set comprises a gas turbine cogeneration unit, a thermal power unit and a wind power unit, and the sum of the electric power output is equal to the electric load of the user at any moment so as to ensure the power balance of the power system. The thermal load of the residents is provided by the cogeneration unit.

The electric heating coordination optimization model is mainly composed of three elements of operation constraint, optimization target and decision variable. Because the power system and the heating system are coupled together through the cogeneration unit, the operation constraint and decision variable elements are divided into three types, namely a power system, a heating system and an electric-heating coupling. The operation constraint is composed of operation constraints of a power grid, a thermal power generating unit, a wind power generating unit and the like in the power system, pipe network heat transmission constraints, heat exchange constraints and cogeneration unit constraints in the heat supply system, and the decision variables comprise hourly heat source heat supply temperature, thermoelectric unit heat output, thermoelectric unit output, thermal power generating unit output and wind power output. The constraint and decision variables of the cogeneration unit belong to both an electric power system and a heat supply system, and are an electric-thermal coupling part. The optimization target is a two-stage optimization target considering the minimum wind power curtailment amount all day long and the best user thermal comfort.

The system operation constraints of the present embodiment will be further explained below.

The electric heat comprehensive energy system comprises a gas turbine cogeneration unit, a wind power plant, a centralized heating system, a power grid and the like, and the operation constraint of each part is specifically described as follows.

The constraint conditions comprise the constraint of a cogeneration unit, the constraint of a power grid and a wind generating unit besides the heat transmission constraint, namely a first function and a second function;

in the embodiment, the power dispatching system regulates the output of each power plant unit every 15 minutes, while the thermal power pipe network regulation period in the prior art is longer than the power dispatching period, and usually the temperature is regulated for tens of minutes or even hours. The key point of this embodiment is to incorporate regulation of the heat pipe network into the power scheduling framework, so in order to unify the time scale of operation regulation of each part of the integrated electric heating energy system, this embodiment establishes a heat transmission equation of a 15-minute regulation period for the heat pipe network.

In the embodiment, the transmission capacity of the related lines is assumed to be within the limit value, and the influence of the transmission capacity of the power grid on the regulation of the thermodynamic system and the coordinated operation of the electric heating comprehensive energy system is not considered.

The optimization objectives and decision variables of the present embodiment will be explained below.

In order to realize the optimal operation of the heating power system and the electric power system, the system operation indexes of the heating power system and the electric power system need to be considered. And selecting the total thermal comfort degree of the user at each moment as an evaluation index from the aspect of a thermodynamic system, and representing the degree of the thermal comfort degree by adopting the thermal deviation. And selecting the maximum wind power total consumption at each moment as an optimization target from the aspect of the power system, namely selecting the minimum wind power total wind abandon amount as the optimization target. The minimum air loss amount at all times of the whole day is taken as a primary optimization target, and the minimum absolute value of the total heat deviation amount of the whole day is taken as a secondary optimization target, which is shown in the following formula.

Wherein i represents the node number, Pⁱ _curw,tShowing the air curtailment quantity of the ith node at the time T, Tⁱ _dev,tThe thermal deviation of the ith node at the moment t is represented, alpha is a weight coefficient, and the value is a minimum value, such as 0.001, and the aim is to convert into an optimal optimization problem only considering thermal comfort when the air abandoning amount is 0.

The decision variables are the hourly heat source heat supply temperature, the heat supply amount and the electric output of the thermoelectric unit, the output of the thermal power unit and the hourly wind power output.

The method is an electric heating coordination optimization model considering the overall operation of the pipe network and the system, and the heat transmission dynamic characteristic of the pipe network, the temperature feedback regulation mechanism of the pipe network, the operation characteristic of the heat exchanger and the operation constraint of the power system are comprehensively considered. The model can provide an accurate operation boundary for an electric heating comprehensive energy system, and realizes system coordination optimization operation considering performance indexes of an electric power system and a thermodynamic system.

The following describes the operation effect of the coordinated electric heating optimization considering the dynamic characteristics of the heat supply network, and the beneficial effect compared with the prior art, with reference to the variation of the present embodiment and the comparative example of the prior art.

The method comprises the steps that a user node which is 1.26km away from a heat source is selected as a research object, a power generation system is composed of 2 gas turbine cogeneration units (one for one), and a wind power plant, a time-by-time output curve of the wind power unit adopts data in documents, the maximum power generation power and the minimum power generation power of the cogeneration units are 23MW and 8MW respectively, and the climbing power is 10 MW/h.

The heat exchange area and coefficient of the building envelope structure of the user node and the area and coefficient of the heat exchanger are shown in tables 1 and 2.

Table 1: single user node user side heat exchange parameter table

Table 2: single user node user side heat exchange parameter table

And taking historical electric load data of a certain area obtained by investigation as original data. The time-by-time electrical load curve and the wind power limit output curve of the user are shown in figure 7.

The outdoor temperature is taken as an example of data of 2016, 11, 16, 24 hours all day in Beijing, and the outdoor temperature curve of every hour all day is shown in figure 8.

The length of a pipeline from a heat source to a single-user node is 1.26km, the pipe diameter is 0.5m, the flow speed is 0.68m/s, the grid ratio is 0.25, the space node step length is 24m, and the time step length is 6 s. According to the 3.3-section heat transfer formula, a composite heat transfer contribution matrix of the user node can be obtained, wherein B represents an influence coefficient matrix of the inlet temperature on the outlet temperature, and a represents an influence coefficient matrix of the initial temperature on the outlet temperature, as shown in the following formula.

On this basis, this example provides 3 comparative examples for analysis:

comparative example 1, namely scheme 1, carries out electric heating coordinated scheduling based on the embodiment, and considers a pipe network temperature feedback regulation mechanism and a pipe network heat transmission accurate model, namely comparative example 1 establishes heat transmission constraint based on a multistage heat exchange process, and simultaneously considers the constraint of a first function and a second function on electric heating coordinated scheduling. The electric heating coordinated scheduling of the comparative example 1 takes the maximum wind power total consumption as a primary optimization target, takes the best thermal comfort as a secondary optimization target, and takes the lowest indoor temperature of more than or equal to 20 ℃ at each moment as an operation constraint.

Comparative example 2, namely scheme 2, is based on the prior art (Liu x., Jenkins n., Wu J., et al. Combined analysis of electric and heat networks [ J ]. Energy procedure, 2014, 61: 155-.

Comparative example 3, namely scheme 3, does not consider the flexible fluctuation of the transmission dynamic characteristic of the heat medium water in the pipeline and the thermal comfort of users, but considers the feedback adjustment of the temperature, and the adjustment standard is that the indoor temperature reaches the optimal value of 20 ℃.

The total air loss in all days of each scheme obtained by the optimization calculation is shown in table 3, and it can be seen that the total air loss is as follows from large to small: comparative example 3, comparative example 2, comparative example 1. The data in the table can provide reference for subsequent analysis.

Table 3: all-day total air abandon rate of each proportion

Fig. 9 and 10 are graphs of the heating temperature of the heat source and the indoor temperature of comparative example 1, comparative example 2, and comparative example 3. The three schemes all consider a pipe network temperature feedback regulation mechanism. And the influence of the heat transmission characteristic of the pipe network and the accurate modeling on the system operation is considered in the comparative analysis. As can be seen from the figure, the variation trends of the heating temperatures of all the schemes are basically consistent, namely the heating temperature at night is higher than that at daytime, because the temperature at night is low, in order to ensure the heat load of the user, the heating temperature at night is increased. Comparing the heat supply temperatures under different schemes, wherein the heat supply temperature of the comparative example 1 is obviously lower than that of the comparative example 2 and that of the comparative example 3 from 1 morning to 8 morning and from 14 afternoon to 16 afternoon, because the wind power limit output is larger in the above time period, the wind power is even larger than the total power load at night, the maximum wind power consumption of the comparative example 1 is a first-level optimization target, and in order to maximally consume the wind power, the heat supply temperature is correspondingly adjusted down in the time period, and the thermoelectric output is reduced; in a period of time between 1 am and 13 pm, the heating temperature of the comparative example 1 is significantly higher than that of the other two schemes, and the purpose is to improve the heating temperature in advance by using the transmission delay characteristic of the heat supply network so as to meet the heat load in the subsequent period of time (avoid insufficient heat load caused by reducing the heating load in the subsequent period of time); in other periods, the heating temperature of comparative example 1 was slightly lower than that of the other solutions, but the difference was small and was substantially equal. The results are in accordance with the scheduling principles of comparative example 1. Comparing the heating temperatures of comparative example 2 and comparative example 3, it can be seen that the heating temperature sequence of comparative example 2 is out of phase with comparative example 3, i.e., the heating temperature at the previous moment of comparative example 2 is approximately equal to the temperature at the moment of comparative example 3, because comparative example 2 considers the heat transfer delay and the heating amount is provided before a transfer delay time.

As can be seen from the indoor temperature graph 10, the room temperature in the initial period from the early 7 th to the early 9 th of the scheme 1 is low, because the heat source temperature is not transmitted to the heat user, and the initial temperature of the pipe network is not enough to make the room temperature reach the expected target; the indoor temperature is higher than 20 c from about 11 to 15 c and from night 22 to early morning 1c, because the wind power is about to increase in the period after these times, so increasing the heat supply amount in advance can suitably reduce the thermal output in the period of wind power generation, so the heat supply temperature at these times is higher, resulting in the room temperature exceeding the expected 20 c, and the conclusion is in agreement with fig. 9. At other times, the room temperature of comparative example 1 was stabilized at 20 ℃. The room temperature of comparative examples 2 and 3 was lower than 20 ℃ at a higher time than that of comparative example 1. For comparison 2, the reason why the temperature is frequently lower than 20 ℃ is that the pipe network model is not accurate enough, and the pipe network model is difficult to be directly incorporated into the electric heating coordination optimization for calculation, and an accurate operation boundary cannot be provided. The reason why the room temperature is frequently lower than 20 c for comparative example 3 is that the feedback regulation mechanism has a certain hysteresis, and a relatively stable room temperature cannot be secured by quantitatively optimizing the time-by-time heating temperature in advance as in comparative example 1. The total sum of absolute values of all-day thermal deviation of the three schemes of the comparative example 1, the comparative example 2 and the comparative example 3 is 31.91, 30.46 and 37.39 respectively, and the lower the total sum is, the better the thermal comfort is, so the thermal comfort of the comparative example 3 is the worst, and the comparative example 1 and the comparative example 2 are basically consistent, which shows that the consideration of the transmission characteristic of the heat network is beneficial to improving the thermal comfort of users to a certain extent.

Fig. 11 reflects the nighttime wind abandoning curves of comparative example 1, comparative example 2 and comparative example 3, only the wind abandoning data from 1 to 5 in the morning are selected, and the wind abandoning effects of different schemes at the nighttime wind power outbreak period are mainly analyzed because the differences of the wind abandoning amounts of the three schemes in other periods are not large. It can be seen that the hourly air rejection rate of comparative example 1 is much lower than that of comparative examples 2 and 3 at most times, and the air rejection rates of comparative examples 2 and 3 are alternately increased at each period. According to the table 3, the total daily air loss of the comparative example 1 is 167.57MW & h, which is reduced by 5.9% compared with the comparative example 3(178.10 MW & h), and the effect of promoting wind power consumption by considering the transmission characteristic of a pipe network in electric heat coordination optimization is shown; the total air curtailment rate is reduced by 4.9% compared with the ratio 2(176.28MW & h), which indicates that the accurate pipe network heat transmission dynamic model adopted in the comparative example 1 can promote wind power consumption better than the accurate model adopted in the ratio 2, and the accurate pipe network model can provide an accurate heat supply operation boundary for electric heat coordination optimization, so that the quantitative and coordination optimization of system operation is realized, and the aim of reducing the air curtailment rate is fulfilled.

From the above comparative example analysis, the following conclusions can be drawn.

The influence of each element such as pipe network characteristics on the electric heating coordination optimization operation effect is quantitatively evaluated. Taking a single hot user as an example, the calculation result shows that: the air volume of the system is reduced by 5.9% by considering the heat transmission characteristic of the pipe network.

The total air curtailment of the comparative example 1 in the whole day is 167.57MW & h, which is reduced by 5.9% compared with that of the comparative example 3(178.10 MW & h), and the effect of promoting wind power consumption can be achieved by considering the transmission characteristic of a pipe network in the electric heating coordination optimization; the total air curtailment rate is reduced by 4.9% compared with the ratio 2(176.28MW & h), which indicates that the accurate pipe network heat transmission dynamic model adopted in the comparative example 1 can promote wind power consumption better than the accurate model adopted in the ratio 2, and the accurate pipe network model can provide an accurate heat supply operation boundary for electric heat coordination optimization, so that the quantitative and coordination optimization of system operation is realized, and the aim of reducing the air curtailment rate is fulfilled.

The beneficial effect of this embodiment lies in:

an electric heating coordination optimization model considering the overall operation of the pipe network and the system is provided, and the heat transmission dynamic characteristic of the pipe network, the temperature feedback regulation mechanism of the pipe network, the operation characteristic of a heat exchanger and the operation constraint of the power system are comprehensively considered. The model can provide an accurate operation boundary for the electric heating comprehensive energy system so as to realize the coordination optimization calculation simulation considering the performance indexes of the electric power and the thermodynamic system.

The electric heating coordination scheduling device considering the heat transmission dynamic characteristic of the heat supply network provided by the invention is described below, and the electric heating coordination scheduling device considering the heat transmission dynamic characteristic of the heat supply network described below and the electric heating coordination scheduling method considering the heat transmission dynamic characteristic of the heat supply network described above can be referred to correspondingly.

The embodiment of the invention also provides an electric heating coordination scheduling device considering the heat transmission dynamic characteristics of the heat supply network, which comprises a model establishing module, a constraint condition setting module, a calculating module, a scheduling module and a feedback adjusting module;

The beneficial effect of the embodiment is that

Fig. 12 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 12: a processor (processor)1210, a communication Interface (Communications Interface)1220, a memory (memory)1230, and a communication bus 1240, wherein the processor 1210, the communication Interface 1220, and the memory 1230 communicate with each other via the communication bus 1240. Processor 1210 may invoke logic instructions in memory 1230 to perform a method of thermoelectric coordinated scheduling that accounts for thermal network thermal transfer dynamics, the method comprising: establishing an electric heating coordination scheduling model; establishing heat transmission constraint based on a multi-stage heat exchange process as a constraint condition; obtaining the current value of a decision variable, and calculating through an electric heating coordinated scheduling model according to the current value of the decision variable and a constraint condition to obtain the current value of a target variable; determining a target interval of a target variable or a target value of the target variable based on the set scheduling condition; and feeding back and adjusting the decision variable according to the relative relation between the current value of the target variable and the target interval or according to the difference value between the current value of the target variable and the target value, thereby realizing the electric heating coordinated scheduling.

In addition, the logic instructions in the memory 1230 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, which when executed by a computer, enable the computer to perform a method of electric heating coordinated scheduling taking into account thermal transport dynamics of a heat grid, the method comprising: establishing an electric heating coordination scheduling model; establishing heat transmission constraint based on a multi-stage heat exchange process as a constraint condition; obtaining the current value of a decision variable, and calculating through an electric heating coordinated scheduling model according to the current value of the decision variable and a constraint condition to obtain the current value of a target variable; determining a target interval of a target variable or a target value of the target variable based on the set scheduling condition; and feeding back and adjusting the decision variable according to the relative relation between the current value of the target variable and the target interval or according to the difference value between the current value of the target variable and the target value, thereby realizing the electric heating coordinated scheduling.

In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the method for coordinating and scheduling electric heat and heat in consideration of heat transfer dynamics of a heat supply network, the method comprising: establishing an electric heating coordination scheduling model; establishing heat supply network dynamic constraints based on a heat supply network linearization heat transfer model and a multi-stage heat exchange process, wherein the heat supply network dynamic constraints are used as constraint conditions; obtaining the current value of a decision variable, and calculating through an electric heating coordinated scheduling model according to the current value of the decision variable and a constraint condition to obtain the current value of a target variable; determining a target interval of a target variable or a target value of the target variable based on the set scheduling condition; and feeding back and adjusting the decision variable according to the relative relation between the current value of the target variable and the target interval or according to the difference value between the current value of the target variable and the target value, thereby realizing the electric heating coordinated scheduling.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. An electric heating coordination scheduling method considering heat transmission dynamic characteristics of a heat supply network is characterized by comprising the following steps:

establishing an electric heating coordination scheduling model;

2. The method of claim 1, wherein the heat supply network constraints comprise a first function corresponding to a heat exchange process:

in the formula:

T_c,in,tthe inlet temperature of the heat medium of the secondary network at the time t; t is_outdoor,tIs the outdoor atmospheric temperature at time t; t is_h,in,tThe inlet temperature of the heat medium of the primary network at the time t;

T_h,out,tthe outlet temperature of the primary network heat medium at the moment t; g_cMass flow of the secondary network heat medium; g_hMass flow rate of the primary net heat medium;

T_user,tthe indoor temperature of the user at the moment t;

s_h,c、s_evl、s_c,user、s_12hare respectively:

wherein e is the base of the natural logarithm; k is a radical of_h,cThe heat exchange coefficient of the primary network heat exchanger and the secondary network heat exchanger is obtained; a. the_h,cThe heat exchange area of the primary net and the secondary net heat exchanger is shown; c is the specific heat capacity of the heat medium; k is a radical of_evlAverage heat exchange coefficient of the building envelope for the user; a. the_evlAverage heat exchange area of the building envelope for the user; k is a radical of_c,userThe heat exchange coefficient of the radiator between the secondary network and the user is shown; a. the_c,userThe heat exchange area of the radiator between the secondary network and the user.

3. The method of claim 1 or 2, wherein the heat supply network constraints comprise a second function corresponding to a heat supply network heat transfer process:

in the formula, phi_m,nThe outlet excess temperature is the outlet excess temperature with a space node of m and a time node of n; i. j is a space node serial number and a time node serial number respectively; the surplus temperature refers to the difference between the temperature of the heat medium and the temperature of the soil;

parameter A_n、B_nAnd A'_nSatisfies the following conditions:

wherein, C is a permutation and combination operator;

the parameters a and r satisfy:

4. The method of claim 1, wherein the constraints further include cogeneration unit constraints;

the thermoelectric ratio constraints are:

in the formula, epsilon is a set thermoelectric ratio of the cogeneration unit; q_CHP，tThe thermal output of the cogeneration unit at the moment t; p_CHP,tThe electric output of the cogeneration unit at the moment t;

the climbing restriction is as follows:

in the formula, P_CHP,up、P_CHP，downRespectively restricting the upward and downward climbing of the set cogeneration unit; p_CHP,t-1The power output of the cogeneration unit at the time of t-1; p_thp,up、P_thp,downRespectively performing upward and downward climbing constraints on the set thermal power cogeneration unit; p_thp,t、P_thp,t-1The thermal power cogeneration unit power output at the time t and the time t-1 respectively; wherein the t-1 moment is the last moment of the t moment;

the unit ultimate output restriction package is as follows:

in the formula, P_CHP,max、P_CHP,minThe maximum power output and the minimum power output of the cogeneration unit are respectively; p_thp,max、P_thp,minRespectively the maximum and minimum power output of the thermal power cogeneration unit;

the heat source water supply temperature constraint is as follows:

40℃≤T_source,t≤90℃

in the formula, T_source,tThe temperature of the heat source water supply at the time t;

5. The method of claim 1, wherein the constraints further include grid and wind farm constraints;

the power balance constraint of the power grid is as follows:

P_CHP,t+O_wind,t＝O_user,t+O_pump,t

in the formula, O_CHP,tThe electric output of the cogeneration unit at the moment t; p_wind,tThe actual wind power output at the moment t is obtained; p_user,tThe load is the residential electricity load at the moment t; p_pump,tThe power consumption of the circulating pump at the time t;

the wind power limit output constraint is as follows:

P_wind,t≤P_wind,max,t

in the formula, P_wind,max,tWind power limit at time tForce is exerted;

the line capacity constraints are:

P_tr,min≤P_tr,t≤P_tr,max

in the formula, P_tr,tThe transmission capacity of the power grid at the moment t; p_tr,min、P_tr,maxThe minimum and maximum transmission capacities of the power grid at the moment t are respectively.

6. The electric heat coordination scheduling method considering heat transmission dynamic characteristics of the heat supply network according to claim 1, wherein the scheduling condition is that air abandonment amount at all time of the whole day is minimum; the target variable corresponding to the scheduling condition with the minimum air abandon amount at all times in the whole day is the sum of the air abandon amounts, and the corresponding target value is 0.

7. The electric heating coordinated scheduling method considering heat transmission dynamic characteristics of the heat supply network according to claim 1, wherein the scheduling condition is that the absolute value of total thermal deviation of the whole day is minimum, the target variable corresponding to the scheduling condition with the minimum absolute value of total thermal deviation of the whole day is the sum of the absolute values of the thermal deviation, and the corresponding target value is 0.

8. An electric heating coordination scheduling device considering heat transmission dynamic characteristics of a heat supply network is characterized by comprising a model establishing module, a constraint condition setting module, a calculating module, a scheduling module and a feedback adjusting module;

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of any of claims 1 to 7 for electro-thermal coordinated scheduling taking into account thermal transport dynamics of a heat network.

10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the method of any of claims 1 to 7 for electric heat coordinated scheduling taking into account thermal transport dynamics of a heat network.