CN110705066A - Projection integral-based dynamic simulation method for integrated energy system of gas-electricity coupling park - Google Patents
Projection integral-based dynamic simulation method for integrated energy system of gas-electricity coupling park Download PDFInfo
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Abstract
The invention discloses a projection integral-based dynamic simulation method for a gas-electric coupling park comprehensive energy system, which is suitable for solving the simulation problem of the gas-electric coupling park comprehensive energy system with rigid characteristics. The specific algorithm comprises the following steps: and performing integral operation of the internal integrator for k times, and performing operation of the external integrator for one time according to the system state variables obtained by solving for the k-2 th time, the k-1 th time and the k-1 th time. In the internal integrator, the electric system model adopts forward Euler method differentiation, and the differential equation and the algebraic equation are alternately solved, and the natural gas system model adopts backward Euler method differentiation, and the partial differential equation and the algebraic equation are simultaneously solved; the external integrator uses extrapolation to solve. The method of the invention can not only meet the numerical precision and numerical stability required by simulation, but also improve the calculation speed to a certain extent and reduce the space and resources occupied by calculation.
Description
Technical Field
The invention relates to a dynamic simulation method of a comprehensive energy system. In particular to a projection integral-based dynamic simulation method for a comprehensive energy system of a gas-electricity coupling park.
Background
With the increasingly prominent energy and environmental problems, a comprehensive energy system capable of realizing the fusion of multiple energy forms and high-efficiency utilization becomes a research hotspot in the technical field of current energy. The electric energy is clean, efficient, easy to convert and utilize and strong in controllability, and is a core energy form of a comprehensive energy system; natural gas is also considered as an important component of future comprehensive energy systems due to its characteristics of economy, environmental protection, abundant reserves and the like. Because the dynamic characteristics and behavior modes of electric power and gas are different greatly, how to carry out accurate and reliable collaborative modeling and simulation analysis on the two energy forms becomes a problem to be solved urgently, and a targeted technical method needs to be developed to solve the dynamic simulation problem of the integrated energy system of the gas-electric coupling park.
At present, the existing joint simulation analysis of the power grid and the natural gas grid is mostly calculated based on steady-state models of the two networks, namely, the changes of the pressure and the flow of the natural gas system caused by the external environment are not considered; when a power grid and an air grid system are coupled, a micro gas turbine is generally adopted for unidirectional coupling at present; from the aspect of a solving method, the existing research mostly adopts a small step length to solve the power grid and the gas grid on the same time scale, although the solving precision is higher, the calculation consumes long time, and the occupied space and resources are more. Therefore, it is urgently needed to find a dynamic simulation method which can meet the requirement of calculation accuracy and has higher calculation efficiency.
Disclosure of Invention
The invention aims to solve the technical problem of providing a projection integral-based dynamic simulation method for the integrated gas-electric coupling park energy system, which can meet the numerical precision and numerical stability required by simulation.
The technical scheme adopted by the invention is as follows: a gas-electricity coupling park comprehensive energy system dynamic simulation method based on projection integration comprises the following steps:
1) inputting system parameters, simulation calculation parameters and disturbance event information according to a gas-electricity coupling park comprehensive energy system to be simulated;
2) establishing a gas-electric coupling park comprehensive energy system simulation model comprising an electric system model and a natural gas system model according to system parameters:
in the formula (I), the compound is shown in the specification,
in order to be a partial differential equation,
in order to be a differential equation,
in order to be an algebraic equation,as a result of the state variables of the entire system,
the algebraic variables are used for the whole system,
is a position variable;
3) setting an initial simulation time t as 0 and an initial value of a system, wherein the initial value of the system comprises the branch flow of a natural gas pipeline, the node pressure, the natural gas load and the electric load in the system, the rotating speed of a micro gas turbine unit, the mechanical power of a prime motor, the electromagnetic power of a synchronous generator, a power angle and the port voltage;
4) setting the cycle number i of the current internal integrator to be 1 and the extrapolation step number M to be M0；
5) When setting up simulationAnd (4) performing integral operation of an integral internal integrator of the projection once to obtain the state variable x of the whole system at the moment after the ith solutioniAnd algebraic variable yiThe counter i is i + 1;
6) judging whether disturbance occurs at the next moment according to the disturbance event information set in the step 1), and if so, judging whether the disturbance occurs at the moment tbIf the system parameters are t + delta t, modifying the system parameters according to the disturbance information, resetting the cycle number i of the internal integrator to be 1, and otherwise, entering the next step;
7) judging whether the value i of the cycle number of the internal integrator is less than or equal to the set cycle number k, if so, returning to the step 5), otherwise, entering the next step;
8) judging whether a disturbance event occurs within t-t + M delta t according to the disturbance event information set in the step 1), and if the disturbance event occurs, determining the occurrence time t of the disturbance eventbSatisfy t < tbIf the sum of t and M delta t is less than t, returning to the step 4), otherwise, entering the next step;
9) solving the system state variable x according to the k-2 th time, the k-1 th time and the k-th timek-2、xk-1And xkPerforming a projection integral external integrator operation to obtain the state variable x of the system at the time of t + M delta tk+MK is the number of internal integrator cycles;
10) according to the obtained state variable xk+MSolving algebraic equations
Obtaining algebraic variable y of systemk+M，t＝t+MΔt；
11) Judging whether the simulation time T is greater than the simulation termination time T, if not, returning to the step 4), otherwise, entering the next step;
12) and outputting a simulation result, and finishing the simulation task.
The invention relates to a projection integral-based dynamic simulation method for a gas-electric coupling park comprehensive energy system, which fully considers the rigidity characteristic of the comprehensive energy dynamic simulation system, differentiates a dynamic equation, adopts proper extrapolation in the solution, can meet the numerical precision and the numerical stability required by simulation, can improve the calculation speed to a certain extent, and reduces the space and resources occupied by calculation.
Drawings
FIG. 1 is a flow chart of a dynamic simulation method of a gas-electricity coupling park comprehensive energy system based on projection integration;
FIG. 2 is an exemplary topological diagram of the method of the present invention;
FIG. 3 is a graph of the change in flow to the micro gas turbine as the natural gas pipeline network flow changes;
FIG. 4 is a graph of the mechanical power change of a gas turbine as the flow of the natural gas pipeline network changes;
FIG. 5 is a diagram of the change of the rotating speed of the synchronous motor when the flow of the natural gas pipe network changes;
FIG. 6 is a diagram of the change of power angle when the flow of the natural gas pipe network changes;
FIG. 7 is a graph of the change in flow to the gas turbine during a change in grid load;
FIG. 8 is a graph of the mechanical power variation of a gas turbine with grid load variation;
FIG. 9 is a graph of the change in the synchronous machine speed with changes in the grid load;
fig. 10 is a diagram of power angle variation when the load of the power grid varies.
Detailed Description
The invention provides a projection integration-based dynamic simulation method for an integrated gas-electric coupling park energy system, which is described in detail below with reference to the embodiments and the accompanying drawings.
As shown in fig. 1, the method for dynamically simulating the integrated energy system of the gas-electric coupling park based on projection integration of the invention comprises the following steps:
1) inputting system parameters, simulation calculation parameters and disturbance event information according to a gas-electricity coupling park comprehensive energy system to be simulated;
the system parameters and the simulation calculation parameters are specifically as follows: the system parameters comprise the topological connection relation of a natural gas pipe network and a power grid, the access position, the capacity and the dynamic parameters of the micro gas turbine, the position, the capacity and the conversion efficiency of an electricity-to-gas (P2G) device, the length, the diameter and the friction coefficient of each branch of the natural gas pipe network, and the line of a power distribution networkAnd the simulation calculation parameters comprise simulation termination time T, simulation time step delta T, natural gas pipe network space step delta l, internal integrator cycle times k, and multiple M of projection integration algorithm external integrator step length relative to internal integrator step length0。
2) Establishing a gas-electric coupling park comprehensive energy system simulation model comprising an electric system model and a natural gas system model according to system parameters:
in the formula (I), the compound is shown in the specification,
in order to be a partial differential equation,
in order to be a differential equation,
in order to be an algebraic equation,
as a result of the state variables of the entire system,
the algebraic variables are used for the whole system,
is a position variable; wherein the content of the first and second substances,
the electrical system model is as follows:
the natural gas system model is as follows:
in the formula (I), the compound is shown in the specification,
andrepresenting state variables of the electrical system and the natural gas system respectively,
and
representing algebraic variables of the electrical system and the natural gas system respectively,
and
respectively representing algebraic equations of an electric system and a natural gas system, wherein a state variable x ═ x of the whole systeme；xg]The algebraic variable y ═ ye；yg]。
3) Setting an initial simulation time t as 0 and an initial value of a system, wherein the initial value of the system comprises the branch flow of a natural gas pipeline, the node pressure, the natural gas load and the electric load in the system, the rotating speed of a micro gas turbine unit, the mechanical power of a prime motor, the electromagnetic power of a synchronous generator, a power angle and the port voltage;
4) setting the cycle number i of the current internal integrator to be 1 and the extrapolation step number M to be M0；
5) Setting simulation time t as t + delta t, and performing integral operation of an internal integrator of the projection integral once to obtain a state variable x of the whole system at the moment after the ith solutioniAnd algebraic variable yiThe counter i is i + 1;
the integral operation of the projection integral internal integrator is to solve the electric system mode firstlyModel, obtaining the state variable x of the electrical system at time t + Δ te(t + Δ t) and algebraic variable yeAfter (t + delta t), substituting the obtained state variable and algebraic variable of the electrical system into the natural gas system model to solve the state variable x of the natural gas systemg(t + Δ t) and algebraic variable yg(t + Δ t), the specific method is as follows:
(5.1) modeling of an Electrical SystemAnd (3) solving:
differentiating the differential equation by adopting a forward Euler method, solving the electrical system model once, wherein the step length is delta t, the time is from t to t + delta t, and the state variable x of a natural gas system in the modelgAnd algebraic variable ygUsing the history of the previous time, the state variable x of the system at the time te(t) obtaining the state variable x of the system at the moment of t + delta te(t + Δ t), the recurrence formula is as follows:
xe(t+Δt)＝xe(t)+G(xe(t),ye(t),xg(t),yg(t))Δt
solving for
To obtain ye(t+Δt)；
(5.2) model of Natural gas System
And (3) solving:
differentiating the partial differential equation by adopting a backward Euler method, wherein the step length is delta t, the time is from t to t + delta t, and the state variable and the algebraic variable of the electrical system in the model adopt a t + delta t time value x obtained by the step (5.1)e(t + Δ t) and ye(t+Δt)：
Solving x by combining partial differential equation and algebraic equation after natural gas system differentiationg(t+Δt)And yg(t+Δt)：
Wherein A is a coefficient matrix, b is a constant vector,
and
representing state variables of the electrical system and the natural gas system respectively,
and
representing algebraic variables of the electrical system and the natural gas system respectively,
and
respectively representing algebraic equations of an electric system and a natural gas system, wherein a state variable x ═ x of the whole systeme；xg]The algebraic variable y ═ ye；yg]。
6) Judging whether disturbance occurs at the next moment according to the disturbance event information set in the step 1), and if so, judging whether the disturbance occurs at the moment tbIf the system parameters are t + delta t, modifying the system parameters according to the disturbance information, resetting the cycle number i of the internal integrator to be 1, and otherwise, entering the next step;
7) judging whether the value i of the cycle number of the internal integrator is less than or equal to the set cycle number k, if so, returning to the step 5), otherwise, entering the next step;
8) judging whether a disturbance event occurs within t-t + M delta t according to the disturbance event information set in the step 1), and if the disturbance event occurs, determining the occurrence time t of the disturbance eventbSatisfy t < tbIf < t + M Δ t, the procedure returns to step4) Otherwise, entering the next step;
9) solving the system state variable x according to the k-2 th time, the k-1 th time and the k-th timek-2、xk-1And xkPerforming a projection integral external integrator operation to obtain the state variable x of the system at the time of t + M delta tk+MK is the number of internal integrator cycles;
the projection integral external integrator operates as follows:
(9.1) extrapolation using historical quantities:
solving the system state variable x according to the k-2 th time, the k-1 th time and the k-th timek-2、xk-1And xkExtrapolating a large step by using the following formula to obtain the system state variable x at the time of t + M delta tk+M：
(9.2) stability verification:
judging extrapolated xk+MWhether the stable condition is satisfied:
max|xk+M-xk|＜ξ
where ξ is a preset threshold, if a stability condition is satisfied, step 10) is performed, otherwise, M is M-1, and the process returns to the step (9.1) to repeat extrapolation calculation until the stability condition is satisfied.
10) According to the obtained state variable xk+MSolving algebraic equationsObtaining algebraic variable y of systemk+M，t＝t+MΔt；
11) Judging whether the simulation time T is greater than the simulation termination time T, if not, returning to the step 4), otherwise, entering the next step;
12) and outputting a simulation result, and finishing the simulation task.
Specific examples are given below:
in the embodiment, a Matlab programming language is adopted, the projection integral-based gas-electricity coupled dynamic simulation method for the park comprehensive energy system is realized, and the method is analyzed and verified through a gas-electricity coupled comprehensive energy system calculation example (shown in an attached figure 2) comprising a pipeline dynamic model, a micro gas turbine set dynamic model and a power grid model, and is compared with a simulation result of a synchronous solving simulation method. The hardware platform of the simulation test is a 4-Core PC machine with Intel Core (TM) i5-6300HQ CPU @2.30GHz and 8GB RAM; the software environment is a 64-bit Windows 10 operating system.
In the present embodiment, after passing through a 50m pipeline, a part of the natural gas flows to a constant natural gas load through a 100m pipeline, and the other part of the natural gas flows to the micro gas turbine unit through a 150m pipeline to generate electricity, the power grid adopts an IEEE 33 node embodiment, the parameters of the natural gas system are shown in table 1, and the parameters of the electrical system are shown in tables 2 to 4.
The simulation scenario is set as follows:
setting the simulation time T to 1000s, the simulation step length delta T to 0.001s, the base value of the natural gas flow to 50kg/s, the delta x to 25m, and 600s, respectively, when the natural gas load flow is reduced from 50kg/s to 45kg/s and the disturbance of the per unit value of the node impedance of the No. 25 power grid is increased by 0.1+ j0.1, comparing the result with the conventional synchronous solving method, as shown in FIGS. 3-10, and the time used for simulation is shown in Table 5.
TABLE 1 transport pipe parameters
TABLE 2 synchronous machine parameter table
TABLE 3 micro gas turbine parameter table
| Parameter name | Parameter value |
| Gas turbine reference power | 250kW |
| Reference value of active power | 0.8p.u. |
| Damping coefficient | 0.03 |
| Fuel system delay time constant | 0.1s |
| Fuel system delay time constant | 1.0s |
| Load limiting time constant | 3.0s |
| Load limiting | 1.2 |
| Temperature cycling control gain | 1.0 |
| Power control proportional gain | 0.01 |
| Power control |
5 |
TABLE 4P2G parameter Table
| Parameter name | Parameter value |
| Natural gas calorific value | 35588kJ/m3 |
| P2G transformation efficiency | 0.62 |
| Natural gas density | 0.7174kg/m3 |
TABLE 5 time comparison table for different solving methods
| Solving method | Solution time(s) |
| The method of the invention | 445.47 |
| Traditional method (synchronous solution) | 673.87 |
Claims (5)
1. A gas-electric coupling park comprehensive energy system dynamic simulation method based on projection integration is characterized by comprising the following steps:
1) inputting system parameters, simulation calculation parameters and disturbance event information according to a gas-electricity coupling park comprehensive energy system to be simulated;
2) establishing a gas-electric coupling park comprehensive energy system simulation model comprising an electric system model and a natural gas system model according to system parameters:
in the formula (I), the compound is shown in the specification,
in order to be a partial differential equation,
in order to be a differential equation,
in order to be an algebraic equation,
as a result of the state variables of the entire system,
the algebraic variables are used for the whole system,is a position variable;
3) setting an initial simulation time t as 0 and an initial value of a system, wherein the initial value of the system comprises the branch flow of a natural gas pipeline, the node pressure, the natural gas load and the electric load in the system, the rotating speed of a micro gas turbine unit, the mechanical power of a prime motor, the electromagnetic power of a synchronous generator, a power angle and the port voltage;
4) setting a current inner productThe number of times of the separator circulation i is 1, and the number of extrapolation steps M is M0；
5) Setting simulation time t as t + delta t, and performing integral operation of an internal integrator of the projection integral once to obtain a state variable x of the whole system at the moment after the ith solutioniAnd algebraic variable yiThe counter i is i + 1;
6) judging whether disturbance occurs at the next moment according to the disturbance event information set in the step 1), and if so, judging whether the disturbance occurs at the moment tbIf the system parameters are t + delta t, modifying the system parameters according to the disturbance information, resetting the cycle number i of the internal integrator to be 1, and otherwise, entering the next step;
7) judging whether the value i of the cycle number of the internal integrator is less than or equal to the set cycle number k, if so, returning to the step 5), otherwise, entering the next step;
8) judging whether a disturbance event occurs within t-t + M delta t according to the disturbance event information set in the step 1), and if the disturbance event occurs, determining the occurrence time t of the disturbance eventbSatisfy t < tbIf the sum of t and M delta t is less than t, returning to the step 4), otherwise, entering the next step;
9) solving the system state variable x according to the k-2 th time, the k-1 th time and the k-th timek-2、xk-1And xkPerforming a projection integral external integrator operation to obtain the state variable x of the system at the time of t + M delta tk+MK is the number of internal integrator cycles;
10) according to the obtained state variable xk+MSolving algebraic equations
Obtaining algebraic variable y of systemk+M，t＝t+MΔt；
11) Judging whether the simulation time T is greater than the simulation termination time T, if not, returning to the step 4), otherwise, entering the next step;
12) and outputting a simulation result, and finishing the simulation task.
2. The method for dynamically simulating the integrated energy system of the pneumoelectric coupling park based on the projection integration as claimed in claim 1, wherein the step 1) The system parameters and the simulation calculation parameters are specifically as follows: the system parameters comprise the topological connection relation of a natural gas pipe network and a power grid, the access position, the capacity and the dynamic parameters of a micro gas turbine, the position, the capacity and the conversion efficiency of an electric-to-gas device, the length, the diameter and the friction coefficient of each branch of the natural gas pipe network, the line and the transformer parameters of a power distribution network, and the simulation calculation parameters comprise simulation termination time T, simulation time step length delta T, natural gas pipe network space step length delta l, internal integrator cycle times k, and the multiple M of the projection integration algorithm external integrator step length relative to the internal integrator step length0。
3. The dynamic simulation method of the integrated energy system of the gas-electric coupling park based on projection integration as claimed in claim 1, wherein in the step 2),
the electrical system model is as follows:
the natural gas system model is as follows:
in the formula (I), the compound is shown in the specification,
and
representing state variables of the electrical system and the natural gas system respectively,
andrepresenting algebraic variables of the electrical system and the natural gas system respectively,
and
respectively representing algebraic equations of an electric system and a natural gas system, wherein a state variable x ═ x of the whole systeme；xg]The algebraic variable y ═ ye；yg]。
4. The method for dynamically simulating the integrated energy system of the pneumoelectric coupling park according to claim 1, wherein the step 5) of integrating the internal integrator is to solve the model of the electric system to obtain the state variable x of the electric system at the time t + Δ te(t + Δ t) and algebraic variable yeAfter (t + delta t), substituting the obtained state variable and algebraic variable of the electrical system into the natural gas system model to solve the state variable x of the natural gas systemg(t + Δ t) and algebraic variable yg(t + Δ t), the specific method is as follows:
(5.1) modeling of an Electrical System
And (3) solving:
differentiating the differential equation by adopting a forward Euler method, solving the electrical system model once, wherein the step length is delta t, the time is from t to t + delta t, and the state variable x of a natural gas system in the modelgAnd algebraic variable ygUsing the history of the previous time, the state variable x of the system at the time te(t) obtaining the state variable x of the system at the moment of t + delta te(t + Δ t), the recurrence formula is as follows:
xe(t+Δt)＝xe(t)+G(xe(t),ye(t),xg(t),yg(t))Δt
solving for
To obtain ye(t+Δt)；
(5.2) model of Natural gas System
And (3) solving:
differentiating the partial differential equation by adopting a backward Euler method, wherein the step length is delta t, the time is from t to t + delta t, and the state variable and the algebraic variable of the electrical system in the model adopt a t + delta t time value x obtained by the step (5.1)e(t + Δ t) and ye(t+Δt)：
Solving x by combining partial differential equation and algebraic equation after natural gas system differentiationg(t + Δ t) and yg(t+Δt)：
Wherein A is a coefficient matrix, b is a constant vector,
and
representing state variables of the electrical system and the natural gas system respectively,andrepresenting algebraic variables of the electrical system and the natural gas system respectively,
and
respectively representing algebraic equations of an electric system and a natural gas system, wherein a state variable x ═ x of the whole systeme；xg]The algebraic variable y ═ ye；yg]。
5. The dynamic simulation method of the integrated energy system of the pneumoelectric coupling park based on projection integration according to claim 1, wherein the operation of the projection integration external integrator in the step 9) is as follows:
(9.1) extrapolation using historical quantities:
solving the system state variable x according to the k-2 th time, the k-1 th time and the k-th timek-2、xk-1And xkExtrapolating a large step by using the following formula to obtain the system state variable x at the time of t + M delta tk+M：
(9.2) stability verification:
judging extrapolated xk+MWhether the stable condition is satisfied:
max|xk+M-xk|＜ξ
where ξ is a preset threshold, step 10) is performed if a stability condition is satisfied, otherwise M ═ M-1, and the process returns to the (9.1) th stage to repeat extrapolation calculation until the stability condition is satisfied.
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| Publication number | Priority date | Publication date | Assignee | Title |
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010104855A2 (en) * | 2009-03-09 | 2010-09-16 | The Johns Hopkins University | Apparatus and method for magnetic resonance imaging with high spatial and temporal resolutions |
| CN101853334A (en) * | 2010-05-27 | 2010-10-06 | 重庆大学 | Equation-free multi-scale simulation method in chemical reaction diffusion |
| CN103700036A (en) * | 2013-12-19 | 2014-04-02 | 天津大学 | Transient stability projection integral method suitable for multi-time scale of electrical power system |
| CN103810646A (en) * | 2014-01-16 | 2014-05-21 | 天津大学 | Improved projection integral algorithm based active power distribution system dynamic simulation method |
| CN104156542A (en) * | 2014-08-26 | 2014-11-19 | 天津大学 | Implicit-projection-based method for simulating stability of active power distribution system |
| CN104679937A (en) * | 2015-01-08 | 2015-06-03 | 国家电网公司 | Error estimation and parameter adaptive adjusting method suitable for implicit projection algorithm |
| CN105700494A (en) * | 2014-12-15 | 2016-06-22 | 爱默生过程管理电力和水解决方案公司 | Model-based combined cycle power plant load control |
| CN105808825A (en) * | 2016-02-29 | 2016-07-27 | 天津大学 | Rolling type stochastic projection integration method suitable for dynamic simulation of active power distribution networks |
| CN108256378A (en) * | 2016-12-29 | 2018-07-06 | 广州映博智能科技有限公司 | Driver Fatigue Detection based on eyeball action recognition |
| CN108574299A (en) * | 2017-03-14 | 2018-09-25 | Abb瑞士股份有限公司 | Method and control system for controlling power converter |
-
2019
- 2019-09-20 CN CN201910896422.4A patent/CN110705066B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010104855A2 (en) * | 2009-03-09 | 2010-09-16 | The Johns Hopkins University | Apparatus and method for magnetic resonance imaging with high spatial and temporal resolutions |
| CN101853334A (en) * | 2010-05-27 | 2010-10-06 | 重庆大学 | Equation-free multi-scale simulation method in chemical reaction diffusion |
| CN103700036A (en) * | 2013-12-19 | 2014-04-02 | 天津大学 | Transient stability projection integral method suitable for multi-time scale of electrical power system |
| CN103810646A (en) * | 2014-01-16 | 2014-05-21 | 天津大学 | Improved projection integral algorithm based active power distribution system dynamic simulation method |
| CN104156542A (en) * | 2014-08-26 | 2014-11-19 | 天津大学 | Implicit-projection-based method for simulating stability of active power distribution system |
| CN105700494A (en) * | 2014-12-15 | 2016-06-22 | 爱默生过程管理电力和水解决方案公司 | Model-based combined cycle power plant load control |
| CN104679937A (en) * | 2015-01-08 | 2015-06-03 | 国家电网公司 | Error estimation and parameter adaptive adjusting method suitable for implicit projection algorithm |
| CN105808825A (en) * | 2016-02-29 | 2016-07-27 | 天津大学 | Rolling type stochastic projection integration method suitable for dynamic simulation of active power distribution networks |
| CN108256378A (en) * | 2016-12-29 | 2018-07-06 | 广州映博智能科技有限公司 | Driver Fatigue Detection based on eyeball action recognition |
| CN108574299A (en) * | 2017-03-14 | 2018-09-25 | Abb瑞士股份有限公司 | Method and control system for controlling power converter |
Non-Patent Citations (1)
| Title |
|---|
| 王成山等: "一种适于有源配电网随机动态仿真的滚动投影积分方法" * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114114958A (en) * | 2021-11-17 | 2022-03-01 | 天津大学 | Heat supply system state discrete simulation method considering source load temperature control characteristics |
| CN114114958B (en) * | 2021-11-17 | 2023-09-29 | 天津大学 | Discrete simulation method for state of heating system by considering control characteristics of source load temperature |
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