CN114004110B - Quantized event driven simulation method for electric-thermal integrated energy system - Google Patents
Quantized event driven simulation method for electric-thermal integrated energy system Download PDFInfo
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Abstract
The invention relates to a quantized event driven simulation method for an electric-thermal integrated energy system, which comprises the steps of firstly inputting simulation parameters aiming at the electric-thermal integrated energy system to be simulated, and carrying out simulation initialization; establishing a quantized coupling model of an electric-thermal integrated energy system to be simulated, wherein the quantized coupling model comprises a thermodynamic subsystem model, an electric subsystem model and an electric-thermal coupling interface equation; enabling the current simulation time to be equal to the minimum value of the next simulation time in all variables, and integrating the corresponding variables to the current simulation time or updating the value of the current simulation time according to an equation and an integration method; and finally judging whether the simulation time reaches the simulation termination time. The invention is suitable for the dynamic simulation of the comprehensive energy system taking the electric-thermal coupling characteristic and the load discrete characteristic into consideration, can simulate the multi-energy flow coupling characteristic and the discrete-continuous hybrid characteristic, and provides an efficient simulation method for the electric-thermal comprehensive energy system model.
Description
Technical Field
The invention relates to a quantized event driven simulation method. In particular to a quantized event driven simulation method oriented to an electric-thermal comprehensive energy system.
Background
The comprehensive energy system integrates refrigeration, heat supply and power generation, improves the utilization rate of primary energy through comprehensive utilization of energy, and also shows great advantages in the aspect of reducing emission. With the rapid development of micro gas turbines and electric refrigeration/heating technologies, the coupling of electric energy and other energy forms is deepened continuously, and a comprehensive energy system integrating multiple energy forms such as cooling, heating, electricity, gas and the like becomes an important development direction of a future smart grid. The comprehensive energy system relates to deep fusion and tight interaction of multiple energy sources, and a scientific and efficient simulation analysis method is a necessary premise for developing planning, design and operation control of the comprehensive energy system, and has important theoretical significance and practical value. Compared with the traditional power system simulation, the system has the advantages that the inertia of the energy forms such as cold, heat and fuel gas in the comprehensive energy system is strong, the time scale is large, a large number of discrete variables are brought by the user behavior on the load side, and the continuous state variables are frequently interacted with the system, so that the complexity of the modeling simulation problem of the comprehensive energy system is greatly increased.
The quantized state system (quantized state system, QSS) is an integration algorithm for solving a continuous-discrete hybrid system, and the QSS algorithm replaces the time discretization of classical numerical integration by quantization of state variables, the state variables of the system change in units of "quanta", and the time required for each state variable change is calculated in turn, so that integration is advanced. The event-driven framework can integrate a QSS method and a time domain integration algorithm, and has good application prospect in comprehensive energy system simulation. Considering the electric-thermal coupling characteristics in an electric-thermal integrated energy system, accurately and efficiently characterizing the coupling influence of source-network-charge is one of the important problems currently faced. Therefore, the invention designs a quantized event driven simulation method for the electric-thermal integrated energy system by considering the thermodynamic and electric coupling characteristics and the load discrete characteristics of the electric-thermal integrated energy system, and provides a necessary tool for the multi-energy flow high-efficiency simulation calculation of the integrated energy system.
Disclosure of Invention
The invention aims to solve the technical problem of providing a quantized event driven simulation method for an electric-thermal integrated energy system, which can simulate the coupling characteristic and the discrete-continuous hybrid characteristic of a multi-energy stream.
The technical scheme adopted by the invention is as follows: a quantized event driven simulation method for an electric-thermal integrated energy system comprises the following steps:
1) Inputting topological connection relation, element parameters, control parameters and simulation calculation parameters of a system aiming at an electric-thermal comprehensive energy system to be simulated, and carrying out simulation initialization; the control parameters comprise a heat source outlet temperature control interval and a user indoor temperature control interval, and the simulation calculation parameters comprise simulation termination time, a quantized integral threshold, an integral error tolerance, a voltage change threshold, initial values of various simulation variables and simulation variable historic quantities, first-order, second-order and third-order derivative initial values of thermodynamic state variables, initial values of quantized thermodynamic state variables and first-order and second-order derivative initial values; setting the last update time and the next update time of all variables to 0, and setting the current simulation time t=0;
2) Establishing a quantized coupling model of an electric-thermal integrated energy system to be simulated, wherein the quantized coupling model comprises a thermodynamic link differential equation set, a thermodynamic control link discrete algebraic equation set, an electric link differential algebraic equation set and a coupling interface algebraic equation set;
3) Generating a simulation event schedule T list ＝[t h,s ,t h,d ,t e ,t he ,t eh ]Wherein t is h,s For the next update time of the thermodynamic state variable, t h,d For next update time of thermal discrete algebraic variable, t e As a power state variable x e And the algebraic variable y of electric power e T is the next update time of (2) he For the next update time of the thermo-electric coupling interface variable, t eh The next updating time of the electric-thermal coupling interface variable is; taking the simulation event time t=min { T { which occurs first in the next step list }；
4) If the current simulation time t=min { t h,s Integrating the differential equation set of the thermodynamic link to the current simulation time t by adopting a third-order quantized state system integration method, and updating the thermodynamic state variable x h Time t of next update of (a) h,s Algebraic variable u of thermal discrete h Time t of next update of (a) h,d Executing step 5); otherwise, directly executing the step 5);
5) If the current simulation time t=t h,d Calculating a thermodynamic discrete algebraic variable u at the current simulation moment t according to a thermodynamic control link discrete algebraic equation set h (t) and updating the thermal discrete algebraic variable u h Next time furtherNew time t h,d Thermal-electrical coupling interface variable u he Time t of next update of (a) he Executing step 6); otherwise, directly executing the step 6);
6) If the current simulation time t=t e Integrating the differential algebraic equation set of the power link to the current simulation time t by adopting a variable step integration algorithm, and updating the power state variable x e And the algebraic variable y of electric power e Time t of next update of (a) e Electric-thermal coupling interface variable u eh Time t of next update of (a) eh Executing step 7); otherwise, directly executing the step 7);
7) If the current simulation time t=min { t he Then calculating the thermal-electric coupling interface variable u of the current simulation time t according to the algebraic equation set of the coupling interface he (t) and updating the electro-thermal coupling interface variable u eh Next update time t he Executing step 8); otherwise, directly executing the step 8);
8) If the current simulation time t=min { t eh Then calculating the current simulation time t electricity-heat coupling interface variable u according to the algebraic equation set of the coupling interface eh (t), and update u eh (t) next update time t eh Executing step 9); otherwise, directly executing the step 9);
9) Judging whether the current simulation time T reaches the input simulation termination time T, if T is more than or equal to T, finishing the simulation, and outputting a simulation result; otherwise, returning to the step 3).
The quantized event driven simulation method for the electric-thermal integrated energy system greatly shortens simulation time, has acceptable simulation precision, can efficiently simulate the electric-thermal integrated energy system with a discrete controller at the source load side, and has advantages in the modeling simulation of a discrete-continuous hybrid system with multiple time scales. The invention is suitable for the dynamic simulation of the comprehensive energy system taking the electric-thermal coupling characteristic and the load discrete characteristic into consideration, can simulate the multi-energy flow coupling characteristic and the discrete-continuous hybrid characteristic, and provides an efficient simulation method for the electric-thermal comprehensive energy system model.
Drawings
FIG. 1 is a flow chart of a quantized event driven simulation method for an electric-thermal integrated energy system of the present invention;
FIG. 2 is a topology of an example thermodynamic system;
FIG. 3 is a schematic diagram of a heat source and heat load configuration;
FIG. 4 is a graph of outlet temperature versus time for heat source number 2 in an example of the invention;
FIG. 5 is a graph of voltage at node 21 over time in an example of the invention;
FIG. 6 is a graph of the output of a photovoltaic power supply over time in an example of the present invention;
fig. 7 is a graph of the output of a photovoltaic power supply over time in an example of the present invention.
Detailed Description
The following describes a detailed description of a quantized event driven simulation method for an electric-thermal integrated energy system according to the present invention with reference to the examples and the accompanying drawings.
As shown in fig. 1, the quantized event driven simulation method for the electric-thermal integrated energy system of the invention comprises the following steps:
1) Inputting topological connection relation, element parameters, control parameters and simulation calculation parameters of a system aiming at an electric-thermal comprehensive energy system to be simulated, and carrying out simulation initialization; the control parameters comprise a heat source outlet temperature control interval and a user indoor temperature control interval, and the simulation calculation parameters comprise simulation termination time, a quantized integral threshold, an integral error tolerance, a voltage change threshold, initial values of various simulation variables and simulation variable historic quantities, first-order, second-order and third-order derivative initial values of thermodynamic state variables, initial values of quantized thermodynamic state variables and first-order and second-order derivative initial values; setting the last update time and the next update time of all variables to 0, and setting the current simulation time t=0;
2) Establishing a quantized coupling model of an electric-thermal integrated energy system to be simulated, wherein the quantized coupling model comprises a thermodynamic link differential equation set, a thermodynamic control link discrete algebraic equation set, an electric link differential algebraic equation set and a coupling interface algebraic equation set; wherein, the following steps:
(1) Differential equations of thermodynamic link:
wherein x is h The system is a thermodynamic state variable, and comprises a pipeline temperature variable, a heat source outlet temperature variable, a user radiator outlet temperature variable and a user indoor temperature variable; f (f) h The function relation of differential equation sets in the thermodynamic link; u (u) h The heat source heating units output by the heat source controllers are connected with the power grid in number and the radiator switch state output by the user temperature controllers are included as thermodynamic discrete algebraic variables; u (u) eh The variable is an electric-thermal coupling interface, and is the thermal power of a single heating unit;
(2) Discrete algebraic equation set of thermodynamic control links:
u h ＝z h (x h ,u h- )
wherein z is h The functional relation of the discrete algebraic equation set in the thermodynamic control link, u h- A historical quantity that is a thermal discrete algebraic variable;
(3) Electric power link differential algebraic equation set:
wherein f e G is the functional relation of differential equation set in the electric power link e Is the algebraic equation set function relation of the electric power link, x e Is a power state variable, y e As algebraic variable of electric power, u he The variable is a thermal-electric coupling interface variable, and is the impedance of a heat source connected to a power grid;
(4) A system of coupled interface algebraic equations:
in the formula g eh Algebraic equation set function relation g for electric-thermal coupling interface he Is a functional relationship of a thermal-electric coupling algebraic equation set.
3) Generating a simulation event schedule T list ＝[t h,s ,t h,d ,t e ,t he ,t eh ]Wherein t is h,s For the next update time of the thermodynamic state variable, t h,d For next update time of thermal discrete algebraic variable, t e As a power state variable x e And the algebraic variable y of electric power e T is the next update time of (2) he For the next update time of the thermo-electric coupling interface variable, t eh The next updating time of the electric-thermal coupling interface variable is; taking the simulation event time t=min { T { which occurs first in the next step list }；
4) If the current simulation time t=min { t h,s Integrating the differential equation set of the thermodynamic link to the current simulation time t by adopting a third-order quantized state system integration method, and updating the thermodynamic state variable x h Time t of next update of (a) h,s Algebraic variable u of thermal discrete h Time t of next update of (a) h,d Executing step 5); otherwise, directly executing the step 5); wherein,
(1) The method for integrating the thermodynamic link differential equation set to the current simulation time t by adopting the third-order quantized state system integration method specifically comprises the following steps:
(1.1) setting the next update time t of the thermal state variable h,s The minimum value of (a) is the mth element, which is marked asIs provided with->Representing a thermal state variable x h The m element in the thermodynamic link differential equation system comprisesThe set of equation numbers for the terms is denoted omega a The method comprises the steps of carrying out a first treatment on the surface of the Let aggregate omega b ＝Ω a U{m}；
(1.2) set upAs thermodynamic state variable x h The j-th element of (a), for j epsilon omega b The following formula was used to find->I.e.)>Integrating to the current simulation time t:
in the method, in the process of the invention,at t h,s,l The j-th element, t h,s,l As thermodynamic state variable x h Is set to be the last time of updating, and->Respectively->Time->Values of +.>First, second, third derivative values of (c).
(2) Said updating the thermal state variable x h Time t of next update of (a) h,s The method specifically comprises the following steps:
(2.1) calculating the quantized thermal state variable q h Q h First and second derivatives of (2)The value of the current simulation time t:
in the method, in the process of the invention,respectively q h 、/>I element of (a)>Andrespectively->Time->Values of +.>Values of the first and second derivatives, +.>As thermodynamic state variable x h Time t of last update of (a) h,s,l The i-th element, N s Is the total number of thermodynamic state variables;
(2.2) let t be h,s The minimum value of (2) is the mth element, and the quantized thermal state variable is updated according to the following formulaIs->Derivative:
in the method, in the process of the invention,respectively quantized thermal state variables q h Thermal state variable x h The m-th element of the group (a), respectively +.>Values of +.>Is a value of a first order and a second order derivative of (c),respectively +.>Values of +.>A value of a first order, second order derivative of (a);
(2.3) assume a thermal discrete algebraic variable u h Electric-thermal coupling interface variable u eh Keeping the current value unchanged for j epsilon omega b Calculating the j-th element in the thermodynamic state variableAt time tFirst, second and third derivatives +.>
In the method, in the process of the invention,is->Differential equation function of thermodynamic link of +.>Is->First and second derivative expressions of q h (t)、/>The values of the quantized thermodynamic state variable and the first and second derivatives of the quantized thermodynamic state variable at the current simulation time t, u h (t) is the value of the thermal discrete algebraic variable at the current simulation time t, u eh (t) is the value of the current simulation time t of the electric-thermal coupling interface variable, Ω b Is a collection;
(2.4) p.j.epsilon.Ω b ObtainingUpdating thermal state variable x h Time t of next update of (a) h,s ：
Wherein:
in the method, in the process of the invention,at t h,s The j-th element in (a), deltaQ is the input quantized integral threshold,/and (b)>As thermodynamic state variable x h Time t of next update of (a) h,s The j-th element of (a)>For quantising the thermodynamic state variable q h The j-th element of (2)>Is thatTime->Value of->Respectively +.>Values of +.>Values of the first and second derivatives, +.>As thermodynamic state variable x h The j-th element of (2)>Is->Time->Is used as a reference to the value of (a),respectively +.>Values of +.>First, second, third derivative values of (c);
(2.5) updating the thermal state variable x h Time t of last update of (a) h,s,l Order of
(3) Said updating the thermal discrete algebraic variable u h Time t of next update of (a) h,d The method specifically comprises the following steps:
let omega c Representing a thermal state variable x h Sequence number set of medium heat source outlet temperature variable and user indoor temperature variable, if omega b ∩Ω c Non-empty, then the p-th element in the thermodynamic state variable is utilizedUpper and lower event localization equations of (2) to calculate t h,d And taking the minimum value obtained by solving as the final t h,d ：
Upper limit event localization equation:
lower limit event localization equation:
wherein t is h,d Is a thermodynamic discrete algebraic variable u h Is used for the next time of updating,and->P-th element in thermodynamic state variables at current simulation time t>Values of +.>First, second and third derivatives of (c), representation->Upper and lower limits of a control interval of a heat source outlet temperature or a user indoor temperature; if the upper limit event positioning equation and the lower limit event positioning equation are not solved, taking t h,d Let T be the simulation termination time of the input, otherwise take the minimum value obtained by the solution as T h,d 。
5) If the current simulation time t=t h,d Calculating a thermodynamic discrete algebraic variable u at the current simulation moment t according to a thermodynamic control link discrete algebraic equation set h (t) and updating the thermal discrete algebraic variable u h Time t of next update of (a) h,d Thermal-electrical coupling interface variable u he Next time of (a)Update time t he Executing step 6); otherwise, directly executing the step 6); the thermal discrete algebraic variable u of the current simulation time t is calculated according to the discrete algebraic equation set of the thermal control link h (t) and updating the thermal discrete algebraic variable u h Time t of next update of (a) h,d Thermal-electrical coupling interface variable u he Time t of next update of (a) he The method specifically comprises the following steps:
(1) Calculating the current simulation moment t thermal discrete algebraic variable u h (t)：
u h (t)＝z h (x h (t h,s,l ),u h- )
Wherein x is h Is a thermal state variable, t h,s,l Is x h X is the last update time of (1) h (t h,s,l ) Is x h At t h,s,l The value of the time, u h- Is a thermodynamic discrete algebraic variable u h History of (2);
(2) Updating the thermodynamic discrete algebraic variable u h History u of (2) h- ＝u h (t)；
(3) Updating the thermodynamic discrete algebraic variable u h Time t of next update of (a) h,d T, T is the simulation termination time of the input;
(4) Updating thermo-electric coupling interface variable u he Time t of next update of (a) he ＝t。
6) If the current simulation time t=t e Integrating the differential algebraic equation set of the power link to the current simulation time t by adopting a variable step integration algorithm, and updating the power state variable x e And the algebraic variable y of electric power e Time t of next update of (a) e Electric-thermal coupling interface variable u eh Time t of next update of (a) eh Executing step 7); otherwise, directly executing the step 7); the power state variable x e And the algebraic variable y of electric power e Time t of next update of (a) e Electric-thermal coupling interface variable u eh Time t of next update of (a) eh The method specifically comprises the following steps:
(1) Calculating the next step integrating step delta according to the integrating error tolerance by adopting a variable step integrating algorithmt, and let the power state variable x e And the algebraic variable y of electric power e Time t of next update of (a) e ＝t+Δt；
(2) Updating the electrical-thermal coupling interface variable u eh Time t of next update of (a) eh ＝t。
7) If the current simulation time t=min { t he Then calculating the thermal-electric coupling interface variable u of the current simulation time t according to the algebraic equation set of the coupling interface he (t) and updating the electro-thermal coupling interface variable u eh Next update time t he Executing step 8); otherwise, directly executing the step 8); the thermal-electric coupling interface variable u of the current simulation time t is calculated according to the algebraic equation set of the coupling interface he (t) and updating the electro-thermal coupling interface variable u eh Next update time t he The method specifically comprises the following steps:
(1) The thermo-electric interface coupling variable u for the current simulation time t is calculated by he (t)：
u he (t)＝g he (u h (t))
In the formula g he Algebraic equation set function relation for thermo-electric coupling interface, u h (t) is the value of the thermodynamic discrete algebraic variable at the current simulation time t;
(2) The following threshold condition judgment is carried out:
in the method, in the process of the invention,is a thermodynamic discrete algebraic variable u h V element of (a)>Is->At the value of the current simulation time t +.>For the last time the threshold condition is established +.>History value omega d Is u h The medium heat source heating unit is connected with a sequence number set of the quantity variable; if the threshold condition is satisfied, the power state variable x is set e And the algebraic variable y of electric power e Time t of next update of (a) e ＝t、Otherwise keep t e 、/>Unchanged;
(3) Thermal-electric coupling interface variable u he Time t of next update of (a) he T, T is the simulation termination time of the input.
8) If the current simulation time t=min { t eh Then calculating the current simulation time t electricity-heat coupling interface variable u according to the algebraic equation set of the coupling interface eh (t), and update u eh (t) next update time t eh Executing step 9); otherwise, directly executing the step 9); the current simulation time t electric-thermal coupling interface variable u is calculated according to the algebraic equation set of the coupling interface eh (t) specifically comprising:
(1) The variable u of the electric-thermal coupling interface at the current simulation time t is calculated by eh (t)：
u eh (t)＝g eh (y e (t))
In the formula g eh Algebraic equation set function relation, y for electric-thermal coupling interface e (t) is the value of the power algebraic variable at the current simulation time t;
(2) The following threshold condition judgment is carried out:
in the method, in the process of the invention,is the algebraic variable y of the electric power e W element of (2) ->Is->At the value of the current simulation time t +.>For the last time the threshold condition is established +.>Historical value, Δy e For the threshold of voltage variation of the input, Ω e A power algebraic variable sequence number set corresponding to a power grid node connected with a heat source; if the threshold condition is satisfied, put +.> Time t for next update of thermodynamic state variables h,s K is +.>The outlet temperature variable of the corresponding heat source is the power state variable x e Serial numbers of (3); otherwise keep->Unchanged;
(3) Set electric-thermal coupling interface variable u eh Time t of next update of (a) eh T, T is the simulation termination time of the input.
9) Judging whether the current simulation time T reaches the input simulation termination time T, if T is more than or equal to T, finishing the simulation, and outputting a simulation result; otherwise, returning to the step 3).
Specific examples are given below:
the embodiment is based on MATLAB programming language environment, realizes a quantized event driven simulation method oriented to an electric-thermal comprehensive energy system, and verifies and analyzes the method through a heating system computing example. The hardware platform for simulation test is a 4-Core PC of Intel Core (TM) i7-8700 CPU@3.20GHz,8GB RAM; the software environment is a 64-bit Windows10 operating system.
The electric-thermal comprehensive energy thermodynamic system consists of a heat supply network and a power grid. The heat supply system is divided into two parts, namely a water supply network and a water return network, the water supply network and the water return network are completely symmetrical, corresponding pipeline branch parameters are the same, a heat source branch and a heat user branch are connected with the water supply network and the water return network to form a closed heat working medium flow loop, the water supply network and the water return network are composed of pipeline branches and nodes, the node numbers of the water supply network are 1-32, the node numbers of the water return network are 33-64, and the sequence is consistent with that of the water supply network; the number of the branch of the water supply network pipeline is 1-32, the number of the branch of the backwater network pipeline is 33-64, and the sequence is consistent with that of the water supply network; the number sequence of the nodes and the branches of the water return network is consistent with that of the water supply network, and can be easily deduced without being listed in the figure. The numbers of the heat source and the heat user branch are 65-88. The topology of the system is shown in figure 1, and the No. 65 branch is the position of the No. 1 heat source; the No. 87 branch is the position where the No. 2 heat source is located; the No. 88 branch is the position of the No. 3 heat source. The heat loads 1 to 21 are respectively positioned on the branches 66 to 86, and each branch 66 to 86 supplies heat for 10 buildings. The power grid adopts an IEEE-33 node power distribution network calculation example, the No. 1, no. 2 and No. 3 heat sources are respectively connected into nodes 18, 21 and 31 of the power distribution network, 8 distributed photovoltaic power sources are also connected into the power grid, and the specific positions are shown in figure 2.
Setting a simulation initial time t=0, a simulation end time t=3600 s, and a quantized integral threshold Δq=1×10 -6 Integral error margin 1 x 10 -3 Voltage change threshold 1×10 -6 Initial value x of thermodynamic state variable h (0) Quantized initial value q of thermodynamic state variable h (0)＝x h (0) Initial values of first, second and third derivatives of thermodynamic state variables Quantized first-order second-order derivative of initial value of thermodynamic state variable +.>Initial value u of thermodynamic discrete algebraic variable h (0) Initial value y of electric algebraic variable e (0) Historical values u of variables h- ＝u h (0)，u' h ＝u h (0)，y' e ＝y e (0) The simulation scenario is set as follows:
the indoor temperature control interval of the user is 24-25 ℃, and the outlet temperature control interval of the heat source is 80-82 ℃. Three methods are adopted to compare simulation precision, and the reference method is as follows: the electric-thermal comprehensive energy system adopts a backward differential formula (backward differentiation formula, BDF) integral method to solve simultaneously, and the method comprises the following steps: the quantized event driven simulation method is characterized in that a third-order quantized state system (QSS 3) integration method is adopted for solving a thermodynamic link, and a BDF integration method is adopted for solving an electric power link.
FIG. 3 is a schematic diagram of a heat source and a heat load structure, wherein a temperature controller of the heat source monitors the outlet temperature of the heat source and controls the number of connected heat source heating units to adjust the outlet temperature of the heat source, and a temperature controller in a user building adjusts the indoor temperature by outputting the on-off state of a radiator; FIG. 4 is a graph of outlet temperature of heat source number 2 over time, heat source number 2 turning off a heating unit and decreasing temperature when the temperature reaches a set upper limit; fig. 5 is a time-dependent voltage change chart of the node 21, and after the No. 2 heat source turns off a heating unit, the consumed electric power decreases, so that the node voltage of the No. 21 power grid to which the No. 2 heat source is connected increases; FIG. 6 is a graph of the output of a photovoltaic power supply over time; fig. 7 shows the indoor temperature and the average value thereof, the indoor temperature of all buildings is set to 24-25 ℃, and the indoor temperature is kept in the section by controlling the switch of the radiator. As shown in Table 1, the simulation efficiency of the quantized event driven simulation method for the electric-thermal integrated energy system greatly shortens the simulation time compared with the BDF algorithm, has acceptable simulation precision, can efficiently simulate the electric-thermal integrated energy system with a discrete controller at the source load side, and has advantages in the modeling simulation of a discrete-continuous hybrid system with multiple time scales as shown in Table 1.
TABLE 1 simulation efficiency
| Method | Maximum relative error (%) | Simulation time-consuming(s) |
| The method of the invention | 1.2×10 -5 | 56.7 |
| Datum | - | >1h |
Claims (9)
1. The quantized event driven simulation method for the electric-thermal integrated energy system is characterized by comprising the following steps of:
1) Inputting topological connection relation, element parameters, control parameters and simulation calculation parameters of a system aiming at an electric-thermal comprehensive energy system to be simulated, and carrying out simulation initialization; the control parameters comprise a heat source outlet temperature control interval and a user indoor temperature control interval, and the simulation calculation parameters comprise simulation termination time, a quantized integral threshold, an integral error tolerance, a voltage change threshold, initial values of various simulation variables and simulation variable historic quantities, first-order, second-order and third-order derivative initial values of thermodynamic state variables, initial values of quantized thermodynamic state variables and first-order and second-order derivative initial values; setting the last update time and the next update time of all variables to 0, and setting the current simulation time t=0;
2) Establishing a quantized coupling model of an electric-thermal integrated energy system to be simulated, wherein the quantized coupling model comprises a thermodynamic link differential equation set, a thermodynamic control link discrete algebraic equation set, an electric link differential algebraic equation set and a coupling interface algebraic equation set;
3) Generating a simulation event schedule T list ＝[t h,s ,t h,d ,t e ,t he ,t eh ]Wherein t is h,s For the next update time of the thermodynamic state variable, t h,d For next update time of thermal discrete algebraic variable, t e As a power state variable x e And the algebraic variable y of electric power e T is the next update time of (2) he For the next update time of the thermo-electric coupling interface variable, t eh The next updating time of the electric-thermal coupling interface variable is; taking the simulation event time t=min { T { which occurs first in the next step list }；
4) If the current simulation time t=min { t h,s Integrating the differential equation set of the thermodynamic link to the current simulation time t by adopting a third-order quantized state system integration method, and updating the thermodynamic state variable x h Time t of next update of (a) h,s Algebraic variable u of thermal discrete h Time t of next update of (a) h,d Executing step 5); otherwise, directly executing the step 5);
5) If the current simulation time t=t h,d Calculating a thermodynamic discrete algebraic variable u at the current simulation moment t according to a thermodynamic control link discrete algebraic equation set h (t) and updating the thermal discrete algebraic variable u h Time t of next update of (a) h,d Thermal-electrical coupling interface variable u he Time t of next update of (a) he Executing step 6); otherwise, directly executing the step 6);
6) If the current simulation time t=t e Then the variable step length integral algorithm is adopted to micro-substitute the power linkIntegrating the equation set to the current simulation time t, and updating the power state variable x e And the algebraic variable y of electric power e Time t of next update of (a) e Electric-thermal coupling interface variable u eh Time t of next update of (a) eh Executing step 7); otherwise, directly executing the step 7);
7) If the current simulation time t=min { t he Then calculating the thermal-electric coupling interface variable u of the current simulation time t according to the algebraic equation set of the coupling interface he (t) and updating the electro-thermal coupling interface variable u eh Next update time t he Executing step 8); otherwise, directly executing the step 8);
8) If the current simulation time t=min { t eh Then calculating the current simulation time t electricity-heat coupling interface variable u according to the algebraic equation set of the coupling interface eh (t), and update u eh (t) next update time t eh Executing step 9); otherwise, directly executing the step 9);
9) Judging whether the current simulation time T reaches the input simulation termination time T, if T is more than or equal to T, finishing the simulation, and outputting a simulation result; otherwise, returning to the step 3).
2. The method for quantized event driven simulation for an electric-thermal integrated energy system according to claim 1, wherein the following steps 2) are performed:
(1) Differential equations of thermodynamic link:
wherein x is h The system is a thermodynamic state variable, and comprises a pipeline temperature variable, a heat source outlet temperature variable, a user radiator outlet temperature variable and a user indoor temperature variable; f (f) h The function relation of differential equation sets in the thermodynamic link; u (u) h The heat source heating units output by the heat source controllers are connected with the power grid in number and the radiator switch state output by the user temperature controllers are included as thermodynamic discrete algebraic variables; u (u) eh As a variant of the electrical-thermal coupling interface,thermal power for a single heating unit;
(2) Discrete algebraic equation set of thermodynamic control links:
u h ＝z h (x h ,u h- )
wherein z is h The functional relation of the discrete algebraic equation set in the thermodynamic control link, u h- A historical quantity that is a thermal discrete algebraic variable;
(3) Electric power link differential algebraic equation set:
wherein f e G is the functional relation of differential equation set in the electric power link e Is the algebraic equation set function relation of the electric power link, x e Is a power state variable, y e As algebraic variable of electric power, u he The variable is a thermal-electric coupling interface variable, and is the impedance of a heat source connected to a power grid;
(4) A system of coupled interface algebraic equations:
in the formula g eh Algebraic equation set function relation g for electric-thermal coupling interface he Is a functional relationship of a thermal-electric coupling algebraic equation set.
3. The method for quantized event driven simulation of an electric-thermal integrated energy system according to claim 1, wherein the step 4) integrates a thermodynamic differential equation set to a current simulation time t by using a third-order quantized state system integration method, and specifically comprises:
(1) Setting the next updating time t of the thermal state variable h,s The minimum value of (a) is the mth element, which is marked asIs provided withRepresenting a thermal state variable x h In the thermodynamic element differential equation set, all of which contain +.>The set of equation numbers for the terms is denoted omega a The method comprises the steps of carrying out a first treatment on the surface of the Let aggregate omega b ＝Ω a ∪{m}；
(2) Is provided withAs thermodynamic state variable x h The j-th element of (a), for j epsilon omega b The following formula was used to find->I.e.)>Integrating to the current simulation time t:
in the method, in the process of the invention,at t h,s,l The j-th element, t h,s,l As thermodynamic state variable x h Time of last update of-> And->Respectively->Time->Values of +.>First, second, third derivative values of (c).
4. The method for quantized event driven simulation of an electro-thermal integrated energy system according to claim 1, wherein the updating of the thermal state variable x in step 4) is performed by h Time t of next update of (a) h,s The method specifically comprises the following steps:
(1) Calculating a quantized thermal state variable q h Q h First and second derivatives of (2)The value of the current simulation time t:
in the method, in the process of the invention,respectively q h 、/>I element of (a)>And->Respectively is/>Time->Values of +.>Values of the first and second derivatives, +.>As thermodynamic state variable x h Time t of last update of (a) h,s,l The i-th element, N s Is the total number of thermodynamic state variables;
(2) Let t be h,s The minimum value of (2) is the mth element, and the quantized thermal state variable is updated according to the following formulaIs->Derivative:
in the method, in the process of the invention,respectively quantized thermal state variables q h Thermal state variable x h M element of (a)> Respectively the current simulation time t/>Values of +.>Values of the first and second derivatives, +.> Respectively +.>Values of +.>A value of a first order, second order derivative of (a);
(3) Assuming a thermodynamic discrete algebraic variable u h Electric-thermal coupling interface variable u eh Keeping the current value unchanged for j epsilon omega b Calculating the j-th element in the thermodynamic state variableFirst, second and third derivatives at time t +.>
In the method, in the process of the invention,is->Differential equation function of thermodynamic link of +.>Is->First and second derivative expressions of q h (t)、/>The values of the quantized thermodynamic state variable and the first and second derivatives of the quantized thermodynamic state variable at the current simulation time t, u h (t) is the value of the thermal discrete algebraic variable at the current simulation time t, u eh (t) is the value of the current simulation time t of the electric-thermal coupling interface variable, Ω b Is a collection;
(4) By the following pair j epsilon omega b ObtainingUpdating thermal state variable x h Time t of next update of (a) h,s ：
Wherein:
in the method, in the process of the invention,at t h,s The j-th element in (a), deltaQ is the input quantized integral threshold,/and (b)>As thermodynamic state variable x h Time t of next update of (a) h,s The j-th element of (a)>For quantising the thermodynamic state variable q h The j-th element of (2)>Is->Time->Value of->Respectively +.>Values of +.>Values of the first and second derivatives, +.>As thermodynamic state variable x h The j-th element of (2)>Is->Time->Is used as a reference to the value of (a),respectively +.>Values of +.>First, second, third derivative values of (c);
(5) Updating thermal state variable x h Time t of last update of (a) h,s,l Order of
5. The method for quantized event driven simulation for an electro-thermal integrated energy system according to claim 1, wherein the updating of the thermal discrete algebraic variable u in step 4) is performed by h Time t of next update of (a) h,d The method specifically comprises the following steps:
let omega c Representing a thermal state variable x h Sequence number set of medium heat source outlet temperature variable and user indoor temperature variable, if omega b ∩Ω c Non-empty, then the p-th element in the thermodynamic state variable is utilizedUpper and lower event localization equations of (2) to calculate t h,d And taking the minimum value obtained by solving as the final t h,d ：
Upper limit event localization equation:
lower limit event localization equation:
wherein t is h,d Is a thermodynamic discrete algebraic variable u h Is used for the next time of updating,and->P-th element in thermodynamic state variables at current simulation time t>Values of +.>First, second and third derivatives of (c), representation->Upper and lower limits of a control interval of a heat source outlet temperature or a user indoor temperature; if the upper limit event positioning equation and the lower limit event positioning equation are not solved, taking t h,d Let T be the simulation termination time of the input, otherwise take the minimum value obtained by the solution as T h,d 。
6. The method for quantized event driven simulation of an electro-thermal integrated energy system according to claim 1, wherein the step 5) calculates the thermal discrete algebraic variation of the current simulation time t according to a set of thermal control link discrete algebraic equationsQuantity u h (t) and updating the thermal discrete algebraic variable u h Time t of next update of (a) h,d Thermal-electrical coupling interface variable u he Time t of next update of (a) he The method specifically comprises the following steps:
(1) Calculating the current simulation moment t thermal discrete algebraic variable u h (t)：
u h (t)＝z h (x h (t h,s,l ),u h- )
Wherein x is h Is a thermal state variable, t h,s,l Is x h X is the last update time of (1) h (t h,s,l ) Is x h At t h,s,l The value of the time, u h- Is a thermodynamic discrete algebraic variable u h History of (2);
(2) Updating the thermodynamic discrete algebraic variable u h History u of (2) h- ＝u h (t)；
(3) Updating the thermodynamic discrete algebraic variable u h Time t of next update of (a) h,d T, T is the simulation termination time of the input;
(4) Updating thermo-electric coupling interface variable u he Time t of next update of (a) he ＝t。
7. The method for quantized event driven simulation of an electro-thermal integrated energy system according to claim 1, wherein the power state variable x in step 6) is as follows e And the algebraic variable y of electric power e Time t of next update of (a) e Electric-thermal coupling interface variable u eh Time t of next update of (a) eh The method specifically comprises the following steps:
(1) Calculating the next step integrating step delta t according to the integrating error tolerance by the adopted variable step integrating algorithm, and enabling the power state variable x e And the algebraic variable y of electric power e Time t of next update of (a) e ＝t+Δt；
(2) Updating the electrical-thermal coupling interface variable u eh Time t of next update of (a) eh ＝t。
8. An electro-thermal oriented complex as claimed in claim 1The quantized event driven simulation method of the energy system is characterized in that the step 7) calculates a thermal-electric coupling interface variable u of the current simulation time t according to a coupling interface algebraic equation set he (t) and updating the electro-thermal coupling interface variable u eh Next update time t he The method specifically comprises the following steps:
(1) The thermo-electric interface coupling variable u for the current simulation time t is calculated by he (t)：
u he (t)＝g he (u h (t))
In the formula g he Algebraic equation set function relation for thermo-electric coupling interface, u h (t) is the value of the thermodynamic discrete algebraic variable at the current simulation time t;
(2) The following threshold condition judgment is carried out:
in the method, in the process of the invention,is a thermodynamic discrete algebraic variable u h V element of (a)>Is->At the value of the current simulation time t +.>For the last time the threshold condition is established +.>History value omega d Is u h The medium heat source heating unit is connected with a sequence number set of the quantity variable; if the threshold condition is satisfied, the power state variable x is set e And algebraic power transformationQuantity y e Time t of next update of (a) e ＝t、Otherwise keep t e 、/>Unchanged;
(3) Thermal-electric coupling interface variable u he Time t of next update of (a) he T, T is the simulation termination time of the input.
9. The method for quantized event driven simulation of an electro-thermal integrated energy system according to claim 1, wherein step 8) calculates a current simulation time t electro-thermal coupling interface variable u according to a coupling interface algebraic equation set eh (t) specifically comprising:
(1) The variable u of the electric-thermal coupling interface at the current simulation time t is calculated by eh (t)：
u eh (t)＝g eh (y e (t))
In the formula g eh Algebraic equation set function relation, y for electric-thermal coupling interface e (t) is the value of the power algebraic variable at the current simulation time t;
(2) The following threshold condition judgment is carried out:
in the method, in the process of the invention,is the algebraic variable y of the electric power e W element of (2) ->Is->At the value of the current simulation time t +.>For the last time the threshold condition is established +.>Historical value, Δy e For the threshold of voltage variation of the input, Ω e A power algebraic variable sequence number set corresponding to a power grid node connected with a heat source; if the threshold condition is satisfied, put +.> Time t for next update of thermodynamic state variables h,s K is +.>The outlet temperature variable of the corresponding heat source is the power state variable x e Serial numbers of (3); otherwise keep->Unchanged;
(3) Set electric-thermal coupling interface variable u eh Time t of next update of (a) eh T, T is the simulation termination time of the input.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010089253A1 (en) * | 2009-02-03 | 2010-08-12 | Dong Energy Power A/S | Distributed electrical power production system and method of control thereof |
| CN109193626A (en) * | 2018-09-15 | 2019-01-11 | 天津大学 | Unified solving method for model selection and constant volume optimization planning of distributed energy station |
| CN109541961A (en) * | 2018-10-23 | 2019-03-29 | 清华大学 | For the discrete state event-driven simulation method of power electronics hybrid system emulation |
| CN110555264A (en) * | 2019-08-30 | 2019-12-10 | 南方电网科学研究院有限责任公司 | Dynamic simulation method and device of comprehensive energy heat supply system based on extended node method |
| WO2020093296A1 (en) * | 2018-11-06 | 2020-05-14 | 国电南瑞科技股份有限公司 | Interval power flow calculation method for power-heat integrated energy system |
| CN113095538A (en) * | 2020-06-08 | 2021-07-09 | 华北电力大学 | Flexible operation-oriented wide-load operation dynamic characteristic modeling method for cogeneration unit |
-
2021
- 2021-11-24 CN CN202111407795.4A patent/CN114004110B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010089253A1 (en) * | 2009-02-03 | 2010-08-12 | Dong Energy Power A/S | Distributed electrical power production system and method of control thereof |
| CN109193626A (en) * | 2018-09-15 | 2019-01-11 | 天津大学 | Unified solving method for model selection and constant volume optimization planning of distributed energy station |
| CN109541961A (en) * | 2018-10-23 | 2019-03-29 | 清华大学 | For the discrete state event-driven simulation method of power electronics hybrid system emulation |
| WO2020093296A1 (en) * | 2018-11-06 | 2020-05-14 | 国电南瑞科技股份有限公司 | Interval power flow calculation method for power-heat integrated energy system |
| CN110555264A (en) * | 2019-08-30 | 2019-12-10 | 南方电网科学研究院有限责任公司 | Dynamic simulation method and device of comprehensive energy heat supply system based on extended node method |
| CN113095538A (en) * | 2020-06-08 | 2021-07-09 | 华北电力大学 | Flexible operation-oriented wide-load operation dynamic characteristic modeling method for cogeneration unit |
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