CN116937685A - Renewable energy power grid time series production simulation method based on security domain - Google Patents

Renewable energy power grid time series production simulation method based on security domain Download PDF

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CN116937685A
CN116937685A CN202310911541.9A CN202310911541A CN116937685A CN 116937685 A CN116937685 A CN 116937685A CN 202310911541 A CN202310911541 A CN 202310911541A CN 116937685 A CN116937685 A CN 116937685A
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田增垚
李春山
张弘鹏
孙铭泽
刘少午
王超
张强
朱时雨
谢赐戬
赵清松
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Northeast Branch Of State Grid Corp Of China
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Abstract

The invention relates to a simulation method, in particular to a renewable energy power grid time series production simulation method based on a security domain. The method solves the problems that new energy consumption capability evaluation is optimistic and calculation speed is slow when high-proportion new energy power generation grid connection is processed. Determining a power transmission network structure and defining a safety domain in a power injection space; step two, a current amplitude formula is obtained through load flow calculation, and the current amplitude formula is developed by using a Taylor formula; step three, a voltage increment expression of any node and a current increment expression of any line are deduced by combining a tide equation; determining operation points on the boundaries of node voltage and line current; step five, finishing to obtain a safety domain boundary corresponding to the power transmission network; step six, determining an objective function of the time sequence production simulation evaluation model; writing power grid operation constraint into a time sequence production simulation evaluation model; and step eight, solving by adopting a selection strategy of the key time section.

Description

Renewable energy power grid time series production simulation method based on security domain
Technical Field
The invention relates to a simulation method, in particular to a renewable energy power grid time series production simulation method based on a security domain, and particularly relates to a power transmission grid linearization operation constraint method established by using a security domain theory.
Background
At present, the development and utilization scale of renewable energy sources continues to expand rapidly. However, the high permeability of renewable energy complicates the flow constraints in the power transmission network. The volatility and intermittence of renewable energy sources makes real-time operating constraints difficult to balance. Currently, established grid topologies cannot support a large number of applications of renewable energy sources, which have been installed beyond the prescribed power generation limits. The large-scale electricity discarding event frequently occurs, and renewable resources are seriously wasted. Therefore, a reasonable plan should be made for the construction location and capacity of the renewable energy source, and the permeability of the renewable energy source in the power transmission network should be accurately estimated.
The currently commonly used evaluation methods are mainly divided into three types: typical daily, random production simulations, and time series production simulations. Typical daily methods focus on the worst case of grid operation and the calculation results may be relatively conservative. The random production simulation method utilizes renewable energy sources and power injection of loads to obey a certain probability distribution, and an evaluation model for maximizing the power generation permeability is provided. The method only needs to randomly produce the simulated probability distribution information, and has high calculation speed. However, the random production simulation method is not suitable for unit combination, and cannot simulate climbing performance and peak shaving capacity. In contrast, because the time series production simulation method can consider the starting/closing process, peak regulation capacity and climbing rate of the unit and evaluate the adaptability of the renewable energy source in a continuous period, the time series production simulation method can better reflect the annual running state of the renewable energy source and is more suitable for power transmission network planning.
However, the improved time series production simulation method described above does not take into account the tidal current constraints of the power transmission network, and the resulting renewable energy consumption capability may be optimistic. For example, when all renewable energy sources are accommodated at a certain moment, certain tide portions may violate node voltage and branch current constraints, in other words, the renewable energy source simulation results obtained by the time series production simulation method cannot meet the practical application requirements. The security domain theory may provide a new solution to the above-mentioned problems. Many simulations indicate that the application of the security domain can linearize the operating constraints. However, most existing security domain generation methods are computationally intensive and unsuitable for online applications. Therefore, there is a need to derive a method for quickly generating security domain boundaries.
Disclosure of Invention
The invention provides a renewable energy power grid time series production simulation method based on a security domain, aiming at the problems that new energy consumption capability evaluation is optimistic, the calculation speed is low and the online application is not suitable for processing high-proportion new energy power generation grid connection. The method is combined with a static security domain SSR (step-state security region), a time sequence production simulation method and a key time section selection strategy to provide a renewable energy power grid time sequence production simulation based on a security domain.
In order to achieve the above purpose, the present invention adopts the following technical scheme, and is characterized by comprising:
step one, determining a power transmission network structure and defining a safety domain in a power injection space;
step two, a current amplitude formula is obtained through load flow calculation, and the current amplitude formula is developed by using a Taylor formula;
step three, a voltage increment expression of any node and a current increment expression of any line are deduced by combining a tide equation;
determining operation points on the boundaries of node voltage and line current;
step five, finishing to obtain a safety domain boundary corresponding to the power transmission network;
step six, determining an objective function of the time sequence production simulation evaluation model;
writing power grid operation constraint into a time sequence production simulation evaluation model;
and step eight, solving by adopting a selection strategy of the key time section.
Further, in the first step, the determining the structure of the power transmission network and defining the safety domain in the power injection space include:
the grid consists of n+1 nodes and bn branches; node 0 is a slack node; n and B are node and branch sets, respectively; p and Q are active and reactive power vectors, respectively; in the power injection space, SR considering the power flow operation constraint can be defined as follows:
wherein: x = (P) T ,Q T ) T ∈R 2n ；V i m 、V i And V i M Respectively the minimum value, the current value and the maximum value of the voltage amplitude of the node i,I l and->The current amplitude vector and the upper current amplitude limit of line l, respectively,/->|I l I is the calculation vector I l A function of the modulus; f (V, θ) =x is the flow equation.
In the second step, the calculating the current amplitude formula by the tide and expanding by using the taylor formula includes:
let the first and end nodes of line l be i and j, respectively, and its admittance be g l +jb l ，I l Which is the current on line l, can be expressed as
Wherein: v (V) i 、θ i And V j 、θ j The voltage amplitude and phase angle of the nodes i and j are respectively; b i0 Is the self admittance of node i;
assume thatThe current amplitude value flowing on the current line I is the current amplitude value; taylor expansion is performed with respect to formula (2) to obtain
Wherein: delta|I l | 2 Is I l Increment of S l ∈R 1×4 Is a row vector formed by theta i 、θ j 、V i And V j Is composed of the first derivative of (a); Δθ i 、Δθ j 、ΔV i 、ΔV j Is a corresponding increment.
Further, in the third step, the deriving the voltage increment expression of any node and the current increment expression of any line by combining the tide equation includes:
from the equation of the flow
Wherein: j is a jacobian matrix of a tide equation; a is that ij Is composed of J -1 A matrix of vectors in (a); Δp, Δq are the increments of P and Q, respectively;
furthermore, it is known that:
wherein a is ik And b ik Can be found from the jacobian matrix J;
the combination of formula (3) and formula (6) shows that:
wherein, c lk And d lk Can be formed by matrix S l Sum matrix A ij And (5) obtaining.
Further, in the fourth step, the determining the operating point on the node voltage and line current boundary includes:
from the operation constraints of all nodes and branches, the following equations can be derived from formulas (6) and (7) in step three
In the method, in the process of the invention,and->The critical power injection variables corresponding to the maximum node voltage, the minimum node voltage and the maximum branch current are respectively.
Further, in the fifth step, the step of sorting out the security domain boundary corresponding to the power transmission network includes:
sorting the formula (8) in the fourth step and performing normalization processing to obtain an SR expression considering the operation constraint, wherein the SR expression is as follows:
in the method, in the process of the invention,and->Is a hyperplane coefficient; (prior studies have shown that hyperplane is constant for a given network topology; the safety domain taking into account all operating constraints of the grid can be derived as:
further, in step six, the determining the objective function of the time series production simulation evaluation model includes:
the maximum consumption of renewable energy sources is set as a target f for time series production simulation model evaluation under the condition of considering the safety of the power grid, as follows:
wherein: TN isTaking TN as 8760h for the total operation time of the time sequence production simulation; p (P) iw (t) is total wind power which can be consumed by the system at the moment t; p (P) is And (t) is the total photovoltaic power that the system can consume at time t.
Further, in step seven, the writing all the grid operation constraints into the time series production simulation evaluation model includes:
the tide constraint is as follows:
wherein: n is n gen Is the number of conventional units in the system;the active output of the kth unit at the time t is obtained; p (P) l (t) is the total load of the system at time t;
the rotation reserve constraint is:
wherein:the upper limit of the active output of the unit i; p (P) b The system is used for positive rotation; e (t) is a 0-1 variable representing the running state of the unit i at the time t, E (t) represents that the unit k is in the running state at the time t when being equal to 1, and E (t) represents that the unit k is in the shutdown state at the time t when being equal to 0;
the output constraint of the conventional unit is as follows:
wherein:the minimum technical output of the unit i;
the climbing constraint of the conventional unit is as follows:
wherein: p (P) up (i) And P down (i) Respectively a maximum uphill speed and a maximum downhill speed allowed by the unit i;
the minimum starting and stopping time constraint of the unit is as follows:
the method comprises the steps that a generator set is added with 3 types of 0-1 variables E (t), F (t) and G (t) describing the running state of the generator set, and the start-stop starting mode of the generator set is optimized by means of the minimum start-stop time constraint of the generator set and the start-stop logic constraint of the generator set and with the maximum new energy consumption as an optimization target, wherein the start-stop starting mode of the generator set is optimized to improve the new energy consumption level;
wherein: f (t) and G (t) respectively represent binary variables of the starting and stopping states of the unit i at the moment t, F (t) represents that the unit is started at the moment t when being 1, and F (t) represents that the unit is not in the starting state at the moment t when being 0; when G (t) is 1, the unit is stopped at the moment t, and when G (t) is 0, the unit is not stopped at the moment t; t (T) run And T shut Minimum continuous running time and minimum continuous downtime of the unit respectively;
the unit start-up and shut-down running state logic constraint is as follows:
new energy output constraint:
in the method, in the process of the invention,and->Theoretical maximum output of wind power and photovoltaic at t time respectively
Further, in the eighth step, the solving by using the selection strategy of the key time section includes:
( Even if the security domain method is applied in the time series production simulation model, the evaluation model cannot be quickly solved when the operation constraint under 8760 time periods is considered. Accordingly, a key time slice selection strategy based on a security domain is presented herein. )
By selecting the operational constraints under the critical time section, the constraints involved are equivalent to the operational constraints considering 8760 time periods; the selection of the key time section can ensure operation safety and improve calculation efficiency; the specific process including selecting strategy is as follows:
the first step: neglecting the operation constraint, and executing time sequence production simulation to obtain an initial optimal operation point;
and a second step of: judging an optimal working point by a security domain method; if the step (10) is not satisfied at the time t, selecting the time t as a key time section; otherwise, the process ends;
thirdly, under the operation constraint condition under the key time section, obtaining an optimal operation point by using time sequence production simulation; returning to the second step.
Compared with the prior art, the invention has the beneficial effects.
The method aims to solve the problems that the new energy consumption capability evaluation is optimistic, the calculation speed is low and the method is not suitable for online application when the existing method is used for processing high-proportion new energy power generation grid connection.
The invention provides a renewable energy power grid time series production simulation based on a security domain by combining a static security domain method (SSR, step-state security region), a time series production simulation method (TSP, time Series Production) and a key time section selection strategy. Firstly, establishing a corrected time sequence production simulation model by using a Safe Region (SR) method; secondly, deriving a linear SR expression meeting the trend constraint based on a sensitivity method; then, a key time period selection strategy is provided based on an iterative method.
Compared with the conventional time sequence production simulation method, the method can improve the solving speed of the established production simulation model, and evaluate the capacity of the renewable energy sources to be absorbed more in accordance with the application requirements on the premise of ensuring the operation safety of the simulated power transmission network, so that the method has stronger applicability.
Drawings
The invention is further described below with reference to the drawings and the detailed description. The scope of the present invention is not limited to the following description.
Fig. 1 is a current schematic of a transmission line.
FIG. 2 is a block diagram of a modified IEEE-30 node power transmission network.
Fig. 3 is a photovoltaic digestion case.
FIG. 4 is a wind power consumption scenario.
Fig. 5 shows the voltage distribution of each node.
Detailed Description
As shown in fig. 1-5, the renewable energy power grid time series production simulation method based on the security domain comprises the following steps:
1. a grid structure is determined and a security domain in the power injection space is defined.
Let the grid consist of n+1 nodes and bn branches. Node 0 is a slack node. N and B are node and branch sets, respectively. P and Q are active and reactive power vectors, respectively. In the power injection space, SR considering the power flow operation constraint can be defined as follows.
Wherein: x = (P) T ,Q T ) T ∈R 2n ；V i m 、V i And V i M Respectively the minimum value, the current value and the maximum value of the voltage amplitude of the node i,I l and->The current amplitude vector and the upper current amplitude limit of line l, respectively,/->|I l I is the calculation vector I l A function of the modulus; f (V, θ) =x is the flow equation.
2. And obtaining a current amplitude formula through load flow calculation, and expanding by using a Taylor formula.
Let the first and end nodes of line l be i and j, respectively, and its admittance be g l +jb l ，I l The current on line l can be expressed as:
wherein: v (V) i 、θ i And V j 、θ j The voltage amplitude and phase angle of the nodes i and j are respectively; b i0 Is the self admittance of node i.
Assume thatIs the current amplitude flowing on the present line i. Taylor expansion is performed with respect to formula (2) to obtain
Wherein: delta|I l | 2 Is I l Increment of S l ∈R 1×4 Is a row vector formed by theta i 、θ j 、V i And V j Is composed of the first derivative of (a); Δθ i 、Δθ j 、ΔV i 、ΔV j Is a corresponding increment.
3. And (3) deriving a voltage increment expression of any node and a current increment expression of any line by combining a tide equation.
From the equation of the flow
Wherein: j is a jacobian matrix of a tide equation; a is that ij Is composed of J -1 A matrix of vectors in (a); Δp, Δq are the increments of P and Q, respectively.
Furthermore, it is known that:
wherein a is ik And b ik Can be found from the jacobian matrix J.
The combination of formula (3) and formula (6) shows that:
wherein, c lk And d lk Can be formed by matrix S l Sum matrix A ij And (5) obtaining.
4. Determining an operating point on node voltage and line current boundaries:
from the operating constraints of all nodes and branches, the following equations can be derived from formulas (6) and (7) in step three.
In the method, in the process of the invention,and->The critical power injection variables corresponding to the maximum node voltage, the minimum node voltage and the maximum branch current are respectively.
5. And (3) finishing to obtain a safety domain boundary corresponding to the power transmission network:
and (3) finishing the formula (8) in the fourth step and carrying out normalization processing to obtain an SR expression considering the operation constraint, as shown below.
In the method, in the process of the invention,and->Is a hyperplane coefficient. Studies have shown that hyperplane is constant for a given network topology. To sum up the above steps, the safety domain taking into account all operating constraints of the grid can be derived as:
6. determining an objective function of a time sequence production simulation evaluation model:
the maximum consumption of renewable energy sources is set as a target f for the time series production simulation model evaluation in consideration of grid safety, as follows.
Wherein: TN is the total operation time of the time sequence production simulation, and TN is 8760h; p (P) iw (t) is total wind power which can be consumed by the system at the moment t; p (P) is (t) is the system at the time tTotal photovoltaic power dissipated.
7. And writing all power grid operation constraints into a time sequence production simulation evaluation model.
The flow constraints are as follows:
wherein: n is n gen Is the number of conventional units in the system;the active output of the kth unit at the time t is obtained; p (P) l And (t) is the total load of the system at the moment t.
Rotating the reserve constraint:
wherein:the upper limit of the active output of the unit i; p (P) b The system is used for positive rotation; e (t) is a 0-1 variable representing the running state of the unit i at the time t, E (t) is equal to 1, and represents that the unit k is in the running state at the time t, and E (t) is equal to 0, and represents that the unit k is in the shutdown state at the time t.
The output constraint of the conventional unit is as follows:
wherein:the minimum technical output of the machine set i.
Conventional unit climbing constraint:
wherein: p (P) up (i) And P down (i) The maximum uphill speed and the maximum downhill speed allowed by the unit i respectively.
Minimum start-stop time constraint of the unit:
the conventional generator set is added with 3 types of 0-1 variables E (t), F (t) and G (t) for describing the running state of the generator set, and the start-stop starting mode of the generator set is optimized by using the minimum start-stop time constraint of the generator set and the maximum new energy consumption as an optimization target and adopting an optimized start-stop starting mode of the generator set, wherein the start-stop time constraint of the generator set can improve the new energy consumption level.
Wherein: f (t) and G (t) respectively represent binary variables of the starting and stopping states of the unit i at the moment t, F (t) represents that the unit is started at the moment t when being 1, and F (t) represents that the unit is not in the starting state at the moment t when being 0; when G (t) is 1, the unit is stopped at the moment t, and when G (t) is 0, the unit is not stopped at the moment t; t (T) run And T shut The minimum continuous operation time and the minimum continuous shutdown time of the unit are respectively.
Logical constraint of unit start-up and stop running states:
new energy output constraint:
in the middle ofAnd->The theoretical maximum output of wind power and photovoltaic at the time t is respectively.
8. And solving by adopting a selection strategy of the key time section.
Even if the security domain method is applied in the time series production simulation model, the evaluation model cannot be quickly solved when the operation constraint under 8760 time periods is considered. Accordingly, a key time slice selection strategy based on a security domain is presented herein. By selecting the operational constraints under the critical time section, the constraints involved are equivalent to the operational constraints considering 8760 time periods. The selection of the key time section can ensure operation safety and improve calculation efficiency. The specific procedure including the selection strategy is as follows.
The first step: ignoring the operational constraints, a time series production simulation is performed to obtain an initial optimal operating point.
And a second step of: and judging the optimal working point by a security domain method. If the step (10) is not satisfied at the time t, selecting the time t as a key time section; otherwise, the process ends.
And thirdly, obtaining an optimal operating point by using time sequence production simulation under the operation constraint condition under the key time section. Returning to the step 2.
To verify the method effectiveness, a test is performed on an IEEE-30 node power transmission network as shown in FIG. 2. And the nodes 7 and 11 in the whole power transmission network diagram are all provided with photovoltaic, and all photovoltaic installed capacities are 70MW. Nodes 19 and 29 are equipped with wind turbines, all of which have installed capacities of 70 megawatts and 45 megawatts, respectively. The time sequence production simulation method is constructed by using 8760h load data, 5954h wind power generation data and 4380h photovoltaic power generation data. Meanwhile, the simulated boundary conditions are shown in table one.
TABLE 1 boundary conditions
When the selection strategy provided by the invention is adopted, 324 key time periods are selected in the first iteration, and after 4 iterations, all node voltage amplitudes and branch line amplitudes meet constraint conditions, so that 379 key time periods are obtained. After simulation, the total photovoltaic consumption is 219.316GWh, the total waste light is 10.516GWh, the waste electricity rate is 4.6%, and the actual utilization hours are 4380 hours; the total consumption of the wind power is 238.202GWh, the total power rejection is 13.471GWh, the power rejection rate is 5.4%, and the actual utilization time is 5888 hours. Fig. 3 and 4 show the month adjustment of photovoltaic and wind power generation, respectively. The voltage distribution at all nodes at 8760h is shown in fig. 5.
As can be seen from fig. 4, all node voltage magnitudes for each time period are in the range of 0.95-1.05p.u. By selecting operation constraint conditions of the key time period, operation safety of the simulated power transmission network is guaranteed, and the evaluation capability of renewable energy sources is more in line with application requirements.
Here, two scenarios are set for the simulation of this section.
Scene 1: and constructing a time sequence production simulation method considering the operation constraint.
Scene 2: a time sequence production simulation method neglecting operation constraint is constructed.
A comparison of the power generation and permeability at different time scales is shown in table two. It can be seen that, taking into account the operational constraints, both the total power generation capacity and the renewable energy permeability are lower than the results obtained in scenario 2. In other words, the evaluation results obtained by the conventional time series production simulation are optimistic. Although the generated energy of the renewable energy source is reduced under the condition of considering the operation constraint, the simulation result obtained by the method can meet all the operation constraint, so that the new energy source digestion capability evaluation is more suitable for the requirement of future power grid planning.
Table 2 comparison of the Capacity to dissipate and penetration for scenario 1 and scenario 2
As for the calculation time in table III, we can see that by using the linear evaluation model based on SR, the calculation time is greatly reduced. Furthermore, while the computational complexity and computational time increases rapidly with increasing time scale, number of cells, and operational constraints, this does not mean that the model is not solvable. That is, the proposed time series production simulation method model is effective and has strong applicability.
Table 3 comparison of solution time for scenario 1 and scenario 2
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced with equivalents; such modifications and substitutions do not depart from the spirit of the invention, which is defined by the following claims.

Claims (9)

1. A renewable energy power grid time series production simulation method based on a security domain is characterized by comprising the following steps of: comprising the following steps:
step one, determining a power transmission network structure and defining a safety domain in a power injection space;
step two, a current amplitude formula is obtained through load flow calculation, and the current amplitude formula is developed by using a Taylor formula;
step three, a voltage increment expression of any node and a current increment expression of any line are deduced by combining a tide equation;
determining operation points on the boundaries of node voltage and line current;
step five, finishing to obtain a safety domain boundary corresponding to the power transmission network;
step six, determining an objective function of the time sequence production simulation evaluation model;
writing power grid operation constraint into a time sequence production simulation evaluation model;
and step eight, solving by adopting a selection strategy of the key time section.
2. A method for simulating time-series production of a renewable energy power grid based on a security domain according to claim 1, wherein: in a first step, the determining the structure of the power transmission network and defining the safety domain in the power injection space include:
the grid consists of n+1 nodes and bn branches; node 0 is a slack node; n and B are node and branch sets, respectively; p and Q are active and reactive power vectors, respectively; in the power injection space, SR considering the power flow operation constraint can be defined as follows:
wherein: x: = (P) T ,Q T ) T ∈R 2n ；V i m 、V i And V i M Respectively the minimum value, the current value and the maximum value of the voltage amplitude of the node i,I l and I l M The current amplitude vector and the upper current amplitude limit of line l, respectively,/->|I l I is the calculation vector I l A function of the modulus; f (V, θ) =x is the flow equation.
3. A method for simulating time-series production of a renewable energy power grid based on a security domain according to claim 2, wherein: in the second step, the current amplitude formula is obtained through load flow calculation, and the expansion by using the taylor formula comprises the following steps:
let the first and end nodes of line l be i and j, respectively, and its admittance be g l +jb l ，I l Which is the current on line l, can be expressed as
Wherein: v (V) i 、θ i And V j 、θ j The voltage amplitude and phase angle of the nodes i and j are respectively; b i0 Is the self admittance of node i;
assume |I l 0 The I is the current amplitude flowing on the current line I; taylor expansion is performed with respect to formula (2) to obtain
Wherein: delta|I l | 2 Is I l Increment of S l ∈R 1×4 Is a row vector formed by theta i 、θ j 、V i And V j Is composed of the first derivative of (a); Δθ i 、Δθ j 、ΔV i 、ΔV j Is a corresponding increment.
4. A method for simulating time-series production of a renewable energy power grid based on a security domain according to claim 3, wherein: in the third step, the step of combining the tide equation to derive the voltage increment expression of any node and the current increment expression of any line comprises the following steps:
from the equation of the flow
Wherein: j is a jacobian matrix of a tide equation; a is that ij Is composed of J -1 A matrix of vectors in (a); Δp, Δq are the increments of P and Q, respectively;
furthermore, it is known that:
wherein a is ik And b ik Can be found from the jacobian matrix J;
the combination of formula (3) and formula (6) shows that:
wherein, c lk And d lk Can be formed by matrix S l Sum matrix A ij And (5) obtaining.
5. The security domain-based renewable energy grid time series production simulation method as set forth in claim 4, wherein: in the fourth step, the determining the operation point on the node voltage and line current boundary includes:
from the operation constraints of all nodes and branches, the following equations can be derived from formulas (6) and (7) in step three
In the method, in the process of the invention,and->The critical power injection variables corresponding to the maximum node voltage, the minimum node voltage and the maximum branch current are respectively.
6. The security domain-based renewable energy grid time series production simulation method as set forth in claim 5, wherein: in the fifth step, the step of sorting and obtaining the safety domain boundary corresponding to the power transmission network comprises the following steps:
sorting the formula (8) in the fourth step and performing normalization processing to obtain an SR expression considering the operation constraint, wherein the SR expression is as follows:
in the method, in the process of the invention,and->Is a hyperplane coefficient; for a given network topology, the hyperplane is constant; the safety domain taking into account all operating constraints of the grid can be derived as:
7. the security domain-based renewable energy grid time series production simulation method as set forth in claim 6, wherein: in the sixth step, the determining the objective function of the time sequence production simulation evaluation model includes:
the maximum consumption of renewable energy sources is set as a target f for time series production simulation model evaluation under the condition of considering the safety of the power grid, as follows:
wherein: TN is the total operation time of time sequence production simulation, and TN is 8760h; p (P) iw (t) is total wind power which can be consumed by the system at the moment t; p (P) is And (t) is the total photovoltaic power that the system can consume at time t.
8. A method for simulating time-series production of a renewable energy power grid based on a security domain according to claim 7, wherein: in the seventh step, the writing all the power grid operation constraints into the time sequence production simulation evaluation model includes:
the tide constraint is as follows:
wherein: n is n gen Is the number of conventional units in the system;the active output of the kth unit at the time t is obtained; p (P) l (t) is the total load of the system at time t;
the rotation reserve constraint is:
wherein:the upper limit of the active output of the unit i; p (P) b The system is used for positive rotation; e (t) is a 0-1 variable representing the running state of the unit i at the time t, E (t) represents that the unit k is in the running state at the time t when being equal to 1, and E (t) represents that the unit k is in the shutdown state at the time t when being equal to 0;
the output constraint of the conventional unit is as follows:
wherein:the minimum technical output of the unit i;
the climbing constraint of the conventional unit is as follows:
wherein: p (P) up (i) And P down (i) Respectively a maximum uphill speed and a maximum downhill speed allowed by the unit i;
the minimum starting and stopping time constraint of the unit is as follows:
the method comprises the steps that a generator set is added with 3 types of 0-1 variables E (t), F (t) and G (t) describing the running state of the generator set, and the start-stop starting mode of the generator set is optimized by means of the minimum start-stop time constraint of the generator set and the start-stop logic constraint of the generator set and with the maximum new energy consumption as an optimization target, wherein the start-stop starting mode of the generator set is optimized to improve the new energy consumption level;
wherein: f (t) and G (t) respectively represent binary variables of the starting and stopping states of the unit i at the moment t, F (t) represents that the unit is started at the moment t when being 1, and F (t) represents that the unit is not in the starting state at the moment t when being 0; when G (t) is 1, the unit is stopped at the moment t, and when G (t) is 0, the unit is not stopped at the moment t; t (T) run And T shut Minimum continuous running time and minimum continuous downtime of the unit respectively;
the unit start-up and shut-down running state logic constraint is as follows:
new energy output constraint:
in the method, in the process of the invention,and->The theoretical maximum output of wind power and photovoltaic at the time t is respectively.
9. A method for simulating time-series production of a renewable energy power grid based on a security domain according to claim 8, wherein: in the eighth step, the solving by adopting the selection strategy of the key time section includes:
by selecting the operational constraints under the critical time section, the constraints involved are equivalent to the operational constraints considering 8760 time periods; the selection of the key time section can ensure operation safety and improve calculation efficiency; the specific process including selecting strategy is as follows:
the first step: neglecting the operation constraint, and executing time sequence production simulation to obtain an initial optimal operation point;
and a second step of: judging an optimal working point by a security domain method; if the step (10) is not satisfied at the time t, selecting the time t as a key time section; otherwise, the process ends;
thirdly, under the operation constraint condition under the key time section, obtaining an optimal operation point by using time sequence production simulation; returning to the second step.
CN202310911541.9A 2023-07-24 2023-07-24 Renewable energy power grid time series production simulation method based on security domain Pending CN116937685A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117791716A (en) * 2024-02-28 2024-03-29 国网江西省电力有限公司电力科学研究院 New energy synchronous stabilization and dynamic voltage support security domain modeling method and system
CN117791716B (en) * 2024-02-28 2024-06-04 国网江西省电力有限公司电力科学研究院 New energy synchronous stabilization and dynamic voltage support security domain modeling method and system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117791716A (en) * 2024-02-28 2024-03-29 国网江西省电力有限公司电力科学研究院 New energy synchronous stabilization and dynamic voltage support security domain modeling method and system
CN117791716B (en) * 2024-02-28 2024-06-04 国网江西省电力有限公司电力科学研究院 New energy synchronous stabilization and dynamic voltage support security domain modeling method and system

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