Power transmission system reactive power planning method and system based on steady-state load model

Abstract

The invention discloses a power transmission system reactive power planning method and system based on a steady-state load model, and the method comprises the steps: employing a steady-state load model, determining an index static load model of a power transmission system, facilitating the accurate analysis of a load flow condition, carrying out the power flow solution calculation through a Newton-Raphson method, and obtaining a power flow solution. The load flow condition can be accurately analyzed; weak buses and lines are identified, the installation position of FACTS equipment is optimized, reactive power is compensated by using the FACTS equipment, and independent and collective influences of active and reactive power modeling on load flow are fully considered; and an active power loss model and a total cost model are constructed, different optimization algorithms are used to find an optimal control parameter set so as to enable the total cost to be lowest, and finally an optimal reactive power planning scheme is obtained. According to the method, active power loss and TOC can be remarkably reduced, a more optimized reactive power planning solution is provided for a power transmission system, and stable operation and economic performance of the power system can be ensured.

Description

Technical Field

[0001] The invention belongs to the field of reactive power planning of electric power systems, and in particular relates to a reactive power planning method for a power transmission system based on a steady-state load model. Background Art

[0002] Currently, transmission operators are facing multiple challenges in the power industry due to the growing population and high demand for electricity over the years. The power grid is experiencing sudden blackouts due to lack of sufficient reactive power flow through the transmission network. Therefore, power system researchers and power company analysts have been working on the proper planning of reactive power since decades ago. The reactive power planning problem is attached to minimizing the actual power losses and managing the distribution and cost.

[0003] Minimization of actual power losses and reduction of operating costs and allocation of new reactive power sources under base load conditions. The bus admittance matrix and Jacobian matrix for voltage magnitude, active and reactive power in the network are determined using conventional load flow analysis methods. The Jacobian matrix is ​​rearranged to obtain correction vectors based on the power flow solution.

[0004] Reactive power planning is a nonlinear complex optimization oriented problem. Therefore, great importance is given in solving the reactive power planning problem. By decomposing the dynamic problem into installed capacity and additional equipment as state vector and control vector respectively, only two levels of load are considered during the minimization of the total operating cost.

[0005] Reactive power planning is very important to provide continuous, stable and economical power supply to the consumers. In the real world, the transmission system is experiencing multiple types of loads. From this perspective, the total operating cost due to the echelon of loads can be painful for analysts and managers of the power system. Load flow method for the response of the transmission system under active and reactive loads. The study showed that the load model has only a limited significant impact on voltage stability. It can be observed that the load model acts as an important variable in the reactive power planning process of some test systems. Whereas the load flow analysis with separate and combined effects on the total operating cost after adding active and reactive loads has not been performed as per the best. Summary of the invention

[0006] Therefore, the purpose of the present invention is to observe the changes in the actual power loss after adding the load model through the Newton-Raphson method. It is expected that this change will also affect the total operating cost. In order to minimize the actual power loss and total operating cost of the system under load conditions, the present invention proposes necessary compensation and control arrangements. In order to prove the effectiveness of the proposed method, after testing and verification in small, medium and large transmission systems, the method of the present invention can significantly reduce active power loss and TOC, provide a more optimized reactive power planning solution for the power transmission system, help ensure the stable operation and economic performance of the power system, and meet the growing power demand.

[0007] To address the deficiencies in the prior art, the present invention provides a unique reactive power planning strategy that considers a static load model in the power transmission system to minimize active power loss and total operating costs. The Newton-Raphson method is used to study load flow, which can effectively minimize power loss. After testing and verification in small, medium and large transmission systems, the method of the present invention can significantly reduce active power loss and total operating costs, provide a more optimized reactive power planning solution for the power transmission system, help ensure the stable operation and economic performance of the power system, and meet the growing demand for electricity.

[0008] The present invention adopts the following technical solution.

[0009] The first aspect of the present invention provides a reactive power planning method for a power transmission system based on a steady-state load model, comprising the following steps:

[0010] Step 1, using a steady-state load model, calculating the power flow solution of the steady-state load model to obtain an initial power flow distribution model;

[0011] Step 2, identifying weak buses and lines, optimizing the installation location of FACTS devices, and using FACTS devices to compensate for the reactive power in the initial power flow distribution model of step 1 to obtain a compensated power flow distribution model;

[0012] Step 3: Based on the compensated power flow distribution model obtained in step 2, an active power loss model is constructed, and different optimization algorithms are used to search for optimization parameters of the active power loss model respectively to iteratively solve the active power loss model to obtain the minimum active power loss;

[0013] Step 4, constructing a total cost model according to the minimum active power loss obtained in step 3;

[0014] Step 5, using different optimization algorithms to search for the optimization parameters of the total cost model respectively, and iteratively solve the total cost model constructed in step 4 to find the optimal control parameter set to minimize the total cost, and finally obtain the optimal reactive power planning scheme.

[0015] Preferably, in step 1, the steady-state load model includes an active and / or reactive power exponential static load model, wherein the active power P in the exponential static load model is i and reactive power Q i , expressed as follows:

[0016] ln(P i )=ln(P gi -P di )+lpln(V i ) (1)

[0017] ln(Q i )=ln(Q gi -Q di )+lqln(V i ) (2)

[0018] In the formula,

[0019] V i is the voltage of the ith bus,

[0020] P gi is the active power generation, P di is the active power requirement,

[0021] Q gi is reactive power generation, Q di is the reactive power demand,

[0022] lp and lq are active and reactive power load factors respectively.

[0023] Preferably, in step 2, the process of identifying weak buses and lines includes:

[0024] Power flow analysis, modal analysis and loss sensitivity analysis are performed to select the installation location of FACTS equipment based on the process of identifying weak buses and lines.

[0025] Preferably, the FACTS device includes a static VAR compensator and a thyristor-controlled series capacitor, and the static VAR compensator and the thyristor-controlled series capacitor are used to compensate reactive power. After the thyristor-controlled series capacitor is installed, the effective reactance X eff Equal to XX TCSC , where X TCSC represents the variable reactance of the thyristor-controlled series capacitor, X represents the series impedance, and -0.6X≤X TCSC ≤0.1X.

[0026] Preferably, in step 3, the different optimization algorithms include particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm;

[0027] The optimization parameters of the active power loss model include generator output power parameters, transformer parameters, capacitor parameters and line parameters. The objective function of the active power loss model is expressed as follows:

[0028]

[0029] In the formula,

[0030] P LOSS is the active power loss,

[0031] N rl is the total number of lines in the network,

[0032] k0 is the k0th line,

[0033] G k0 is the conductance of the k0th circuit,

[0034] V i is the voltage of the ith bus,

[0035] V j is the j-th bus voltage,

[0036] δ i is the voltage phase angle of the ith bus,

[0037] δ j is the voltage phase angle of the jth bus;

[0038] The constraints of the active power loss model include: equipment operation constraints, system stability constraints and network topology constraints.

[0039] Preferably, in step 4, the objective function of the total cost model is constructed and expressed as the following formula:

[0040] TOC=C1(P LOSS )+C2(Q gen )+C3(Q lhch )+C4(Q facts ) (3)

[0041] In the formula,

[0042] TOC is the total cost,

[0043] C1(P LOSS ) is the active power loss cost,

[0044] C2(Q gen ) is the reactive power generation cost,

[0045] C3(Q lhch ) is the line charging cost,

[0046] C4(Q facts ) is the installation cost of FACTS equipment.

[0047] Preferably, C1(P LOSS ) According to the active power loss P LOSS Calculated, C2(Q gen ) According to the reactive power generation Q gen Calculated, C3(Q lhch ) According to the total line charging reactive power Q lhch Calculated, C4(Q facts ) According to the reactive power Q of FACTS equipment installation facts Calculated, reactive power generation Q gen , expressed as follows:

[0048]

[0049] In the formula,

[0050] Q gen is the reactive power generation,

[0051] Q gen (k) is the reactive power generation of the kth generator,

[0052] a q is the reactive power cost coefficient,

[0053] N g is the number of generators,

[0054] b q is the reactive power cost coefficient,

[0055] c q is the reactive power cost coefficient;

[0056] Total line charging reactive power Q lnch , expressed as follows:

[0057]

[0058] In the formula,

[0059] Q lnch Reactive power for charging the total line,

[0060] Y ch Charging admittance for the line,

[0061] N ch The number of charging elements for the circuit ch,

[0062] V i is the voltage of the ith bus,

[0063] V j is the voltage of the jth bus.

[0064] Preferably, the constraints of the total cost model specifically include load balance constraints, power generation limit constraints, tap setting limit constraints, voltage and current limit constraints, and FACTS unit limit constraints. The load balance constraint is expressed by the following formula:

[0065]

[0066] in,

[0067] P Gi and P Di are the generation and demand active power of the i-th bus,

[0068] Q Gi and Q Di are the generation and demand reactive power of the i-th bus,

[0069] B ij and G ij is the susceptance and conductance between the i-th and j-th busbars,

[0070] n b is the total number of buses,

[0071] is the voltage phase angle of the i-th and j-th buses;

[0072] The power generation limit constraint is expressed as follows:

[0073]

[0074] in,

[0075] min P gk and max P gk are the minimum and maximum limits for the generator's active power generation,

[0076] min Q gk and max Q gk are the minimum and maximum limits for the reactive power generation of the generator,

[0077] P gk is the active power generation of the kth generator,

[0078] Q gk is the reactive power generation of the kth generator;

[0079] The tap setting limit constraint is expressed as follows:

[0080]

[0081] in,

[0082] min tap t and max tap t Set upper and lower limits for transformer taps,

[0083] N tf is the number of transformers,

[0084] tap t is the tap setting of the t-th transformer;

[0085] The voltage and current limit constraints are expressed as follows:

[0086]

[0087] In the formula,

[0088] min V k and max V k is the bus voltage V k The upper and lower limits of

[0089] max I i-jk I is the current of line ij i-j The maximum current limit,

[0090] N bs is the number of buses,

[0091] N nl is the number of lines;

[0092] The FACTS unit constraint is expressed as follows:

[0093]

[0094] in,

[0095] and are the pth static VAR compensator SVC p The minimum and maximum susceptance,

[0096] and The qth thyristor controlled series capacitor TCSC is q Reactance limit, N svcis the number of static VAR compensators,

[0097] N tsvc The number of capacitors in series for thyristor control.

[0098] Preferably, in step 5, the different optimization algorithms include particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm;

[0099] The optimization parameters of the total cost model include the reactive power of the generator, the tap setting of the transformer, and the impedance and susceptance of the line.

[0100] A second aspect of the present invention provides a reactive power planning system for a power transmission system based on a steady-state load model, which is used to run the reactive power planning method for a power transmission system based on a steady-state load model, comprising:

[0101] The power flow distribution model module is used to adopt a steady-state load model and perform power flow solution calculation on the steady-state load model to obtain an initial power flow distribution model;

[0102] Weak bus and line identification module, used to identify weak buses and lines to determine the installation location of FACTS equipment;

[0103] FACTS equipment modules, including static VAR compensators and thyristor-controlled series capacitors, for reactive power compensation;

[0104] Active power loss model construction module, used to construct active power loss model, using different optimization algorithms including particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm, respectively searching for the optimization parameters of active power loss model to iteratively solve the active power loss model and obtain the minimum active power loss;

[0105] A total cost model building module, used to build a total cost model, including an objective function of the total cost model of active power loss cost, reactive power generation cost, line charging cost and FACTS equipment installation cost, and setting constraints of the total cost model including load balancing, generation limit, tap setting limit, voltage and current limit and FACTS unit limit;

[0106] The optimization parameter search module is used to use different optimization algorithms including particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm to search for the optimization parameters of the total cost model respectively, iteratively solve the total cost model, find the optimal control parameter set, minimize the total cost, and finally obtain the optimal reactive power planning scheme.

[0107] The beneficial effects of the present invention are as follows:

[0108] The present invention proposes a novel reactive power planning strategy that takes into account a static load model in a power transmission system. An exponential static load model of active and / or reactive power is introduced in the invention, which designs corresponding active and reactive indices according to the flow of active and reactive power in the transmission network. In addition, the study also focuses on the optimal arrangement of reactive power compensation equipment to minimize power losses in load flow solutions. The application of FACTS equipment in reactive power compensation is also proposed, as well as the independent and combined effects of active and reactive power modeling on the total operating cost of the system;

[0109] The present invention effectively reduces the active power loss of the system and reduces the total operating cost. The voltage stability of the power system is improved by optimizing the layout of reactive power compensation equipment. FACTS devices such as static VAR compensators and thyristor-controlled series capacitors are optimized to enhance voltage stability and reduce power loss. The impact of static VAR compensators on system performance under different conditions is solved to solve different constraints, limit the challenges during the minimization of actual power loss, and reduce the additional cost of compensation equipment. Voltage stability is established by adding reactive power devices to the power grid. In order to restore the sudden voltage instability of the system, the reactive power compensator is installed and its appropriate location is determined. In the power flow model, reactive power compensators are used as reactive power generators. Different types of sensitivity indexes to voltage, current and load angle fluctuations consider the optimal placement of these compensation devices. In addition, small, medium and large transmission systems are considered to verify the wide applicability of the proposed planning strategy. Finally, a variety of optimization algorithms, such as particle swarm optimization, differential evolution, etc., are used to find the optimization parameters, which increases the diversity and effectiveness of the solution;

[0110] This invention significantly improves the efficiency and stability of the power system and reduces the operating cost by introducing a new reactive power planning strategy and optimization method. The innovation lies in the in-depth analysis and optimization of the static load model and the discussion of the application of FACTS equipment in reactive power compensation. It not only improves the economy and reliability of the power system, but also provides a new perspective and tool for the planning and operation of the power system.

[0111] The present invention minimizes both the total operating cost and the active power loss, so as to realize the economic and stable operation of the power system. This phased optimization method can effectively reduce the complexity of the problem and improve the efficiency of solving it. At the same time, by comprehensively considering the active power loss and the total cost, a more comprehensive and optimized solution can be obtained, which provides support for the economic operation and sustainable development of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0112] Figure 1It is a single line diagram of the present invention for installing a FACTS device to a power network;

[0113] Figure 2 is a flow chart of the RPP operation proposed by the present invention;

[0114] Figure 3 is a possible combination of loads in the system of the present invention;

[0115] Figure 4 It is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0116] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0117] Example 1

[0118] Embodiment 1 of the present invention proposes a reactive power planning method for a power transmission system based on a steady-state load model, such as Figure 2 As shown, the specific steps include:

[0119] Step 1, using a steady-state load model, the model considers that the flow solution is calculated by the Newton-Raphson method to obtain the initial flow distribution model;

[0120] Steady-state load models include active and / or reactive power exponential static load models.

[0121] The exponential static model that considers active power, reactive power, and the difference between active and reactive power will affect the subsequent solution of the total cost in different aspects. The active model mainly starts from the perspective of active power, and the reactive model focuses on the effect of reactive power on cost. The model that considers both active and reactive power at the same time can more comprehensively reflect the characteristics of the power system and provide a more accurate basis for the solution of the total cost.

[0122] Further, in step 1, in the exponential static load model, the active power P i and reactive power Q i The load factors are l p and l q , and the active and reactive power satisfy formula (1) and formula (2) respectively:

[0123] ln(P i )=ln(P gi -P di )+lpln(V i) (1)

[0124] ln(Q i )=ln(Q gi -Q di )+lqln(V i ) (2)

[0125] V i is the voltage of the ith bus, P gi is the active power generation, P di is the active power demand, Q gi Reactive power generation Q di is the reactive power demand, lp and lq are the active and reactive power load factors respectively.

[0126] The Newton-Raphson method is used to successively update the voltage V i , find the bus voltage V in the iterative process i The stable value of P is obtained until the voltage is stable and the active and reactive power supply and demand are balanced. Each iteration uses the current voltage P i and Q i The power increment is calculated and the voltage is adjusted accordingly until convergence to a solution.

[0127] Step 2, identifying weak buses and lines, optimizing the installation location of FACTS devices, and using FACTS devices to compensate for the reactive power in the initial power flow distribution model of step 1 to obtain a compensated power flow distribution model;

[0128] Further, in step 2, the process of identifying weak buses and lines includes implementing power flow analysis, modal analysis and loss sensitivity analysis to determine the nodes and lines most susceptible to voltage instability or reactive power imbalance, thereby selecting the installation location of the FACTS equipment.

[0129] The FACTS device includes a static VAR compensator and a thyristor-controlled series capacitor. The two FACTS devices, the static VAR compensator and the thyristor-controlled series capacitor, are used to compensate for reactive power.

[0130] Further, in step 2, the TCSC controls the power flow and enhances the voltage stability by reducing the effective series impedance of the transmission line. After the TCSC is installed, the effective reactance X eff Equal to XX TCSC , where X TCSC represents the variable reactance of TCSC, X represents the series impedance, and -0.6X≤X TCSC ≤0.1X.

[0131] Step 3: Based on the compensated power flow distribution model obtained in step 2, an active power loss model is constructed, and different optimization algorithms are used to search for optimization parameters of the active power loss model respectively to iteratively solve the active power loss model so as to minimize the active power loss and obtain the active power optimization parameters and the minimum active power;

[0132] Active power optimization parameters include generator output power parameters, transformer parameters, capacitor parameters, line parameters, etc.

[0133] The objective function of the active power loss model is expressed as follows:

[0134]

[0135] In the formula,

[0136] P LOSS is the active power loss,

[0137] N rl is the total number of lines in the network,

[0138] k0 is the k0th line,

[0139] G k0 is the conductance of the k0th circuit,

[0140] V i is the voltage of the ith bus,

[0141] V j is the j-th bus voltage,

[0142] δ i is the voltage phase angle of the ith bus,

[0143] δ j is the voltage phase angle of the jth bus.

[0144] The active power loss model includes: equipment operation constraints, system stability constraints, and network topology constraints.

[0145] Step 4, constructing a total cost model according to the minimum active power loss obtained in step 3;

[0146] Constructing the objective function of the total cost model, which includes active power loss cost, reactive power generation cost, line charging cost and FACTS equipment installation cost;

[0147] Further, in step 4, the objective function of the total cost model is constructed, and the objective function includes active power loss cost, reactive power generation cost, line charging cost and FACTS equipment installation cost. The objective function expression is as shown in formula (3):

[0148] TOC=C1(P LOSS )+C2(Q gen )+C3(Q lhch )+C4(Q facts ) (3)

[0149] In the formula,

[0150] TOC is the total cost,

[0151] C1(P LOSS ) is the active power loss cost,

[0152] C2(Q gen ) is the reactive power generation cost,

[0153] Charging costs for the line,

[0154] C4(Q facts ) is the installation cost of FACTS equipment.

[0155] Among them, C1(P LOSS ) and active power loss (P LOSS ) related, C2(Q gen )、C3(Q lnch ) and C4(Q facts ) is calculated based on reactive power support, C1(P LOSS ) According to the active power loss P LOSS Calculate, C2(Q gen ) According to the reactive power generation Q gen Calculate, C3(Q lhch ) According to the total line charging reactive power Q lhch Calculate, C4(Q facts ) According to the reactive power Q of FACTS equipment installation facts Calculation, the specific calculation formula is formula (4) (5) and (6):

[0156]

[0157] In the formula,

[0158] Q gen is the reactive power generation,

[0159] Q gen (k) is the reactive power generation of the kth generator,

[0160] a q is the reactive power cost coefficient,

[0161] N g is the number of generators,

[0162] bq is the reactive power cost coefficient,

[0163] c q is the reactive power cost coefficient,

[0164]

[0165] In the formula,

[0166] Q lhch Reactive power for charging the total line,

[0167] Y ch Charging admittance for the line,

[0168] N ch The number of charging elements for the line,

[0169] ch is the line.

[0170] Set constraints, including load balancing, generation limits, tap setting limits, voltage and current limits, and FACTS unit limits;

[0171] Furthermore, in step 4, the reactive power planning method considers various limiting factors of the power system more comprehensively and meticulously, thereby providing more reliable constraint conditions for reactive power planning. The constraint conditions are specifically as shown in formulas (7) to (15):

[0172] The load balancing constraint is expressed as follows:

[0173]

[0174] in,

[0175] P Gi and P Di are the generation and demand active power of the i-th bus,

[0176] Q Gi and Q Di are the generation and demand reactive power of the i-th bus,

[0177] B ij and G ij is the susceptance and conductance between the i-th and j-th busbars,

[0178] n b is the total number of buses,

[0179] is the voltage phase angle of the i-th and j-th buses;

[0180] The power generation limit constraint is expressed as follows:

[0181]

[0182] in,

[0183] min P gk and max P gk are the minimum and maximum limits for the generator's active power generation,

[0184] min Q gk and max Q gk are the minimum and maximum limits for the reactive power generation of the generator,

[0185] P gk is the active power generation of the kth generator,

[0186] Q gk is the reactive power generation of the kth generator,

[0187] The tap setting limit constraint is expressed as follows:

[0188]

[0189] in,

[0190] min tap t and max tap t Set upper and lower limits for transformer taps,

[0191] N tf is the number of transformers,

[0192] tap t is the tap setting of the t-th transformer;

[0193] The voltage and current limit constraints are expressed as follows:

[0194]

[0195] In the formula,

[0196] min V k and max V k is the bus voltage V k The upper and lower limits of

[0197] max I i-jk I is the current of line ij i-j The maximum current limit,

[0198] N bs is the number of buses,

[0199] N nl is the number of lines,

[0200] The FACTS unit constraint is expressed as follows:

[0201]

[0202]

[0203] in,

[0204] and are the pth static VAR compensators The minimum and maximum susceptance,

[0205] and The qth thyristor controls the series capacitor The reactance limit,

[0206] N svc is the number of static VAR compensators,

[0207] N tsvc The number of capacitors in series for thyristor control.

[0208] Different optimization algorithms are used to search for optimization parameters respectively, and the total cost model is iteratively solved respectively until the optimal set of control parameters is found to minimize the total cost and obtain the optimal reactive power planning scheme.

[0209] Step 5, use different optimization algorithms to search for the optimization parameters of the total cost model respectively, and iteratively solve the total cost model of step 4 respectively until the optimal control parameter set is found to minimize the total cost and obtain the optimal reactive power planning scheme.

[0210] Different optimization algorithms include particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm, and crow search algorithm.

[0211] The optimization parameters of the total cost model include the reactive power of the generator, the tap setting of the transformer, the impedance and susceptance of the line, etc. For example, the PSO algorithm finds the optimal parameters by exploring and adjusting the control variables in the randomly generated search space. These parameters will affect the calculation of each cost component in the total cost model, thereby minimizing the total cost.

[0212] After the active power loss is minimized, the optimal parameters of the active power loss are retained. When solving the optimal total cost, the original optimal parameters of the active power remain unchanged and the remaining parameters are optimized.

[0213] Solving the optimization parameters is not only to minimize the active power loss, but also to minimize the total cost. The optimization parameters cover multiple aspects related to system operation, such as the reactive power of the generator, the tap setting of the transformer, the impedance and susceptance of the line, etc. When performing reactive power planning, the total cost model is solved, the optimization parameters are searched by using the optimization algorithm, and these parameters are substituted into the total cost model for calculation and iteration to find the optimal control parameter set that minimizes the total cost.

[0214] The total cost is used to evaluate the pros and cons of reactive power planning schemes to find the optimal planning strategy. The total operating cost includes active power loss, but the lowest active power loss does not necessarily mean the lowest total operating cost, because the total operating cost also includes reactive power generation cost, line charging cost and FACTS equipment installation cost.

[0215] The beneficial effects of the present invention are as follows:

[0216] The present invention proposes a novel reactive power planning strategy that takes into account a static load model in a power transmission system. An exponential static load model of active and / or reactive power is introduced in the invention, which designs corresponding active and reactive indices according to the flow of active and reactive power in the transmission network. In addition, the study also focuses on the optimal arrangement of reactive power compensation equipment to minimize power losses in load flow solutions. The application of FACTS equipment in reactive power compensation is also proposed, as well as the independent and combined effects of active and reactive power modeling on the total operating cost of the system;

[0217] The present invention effectively reduces the active power loss of the system and reduces the total operating cost. The voltage stability of the power system is improved by optimizing the layout of reactive power compensation equipment. FACTS devices such as static VAR compensators and thyristor-controlled series capacitors are optimized to enhance voltage stability and reduce power loss. The impact of static VAR compensators on system performance under different conditions is solved to solve different constraints, limit the challenges during the minimization of actual power loss, and reduce the additional cost of compensation equipment. Voltage stability is established by adding reactive power devices to the power grid. In order to restore the sudden voltage instability of the system, the reactive power compensator is installed and its appropriate location is determined. In the power flow model, reactive power compensators are used as reactive power generators. Different types of sensitivity indexes to voltage, current and load angle fluctuations consider the optimal placement of these compensation devices. In addition, small, medium and large transmission systems are considered to verify the wide applicability of the proposed planning strategy. Finally, a variety of optimization algorithms, such as particle swarm optimization, differential evolution, etc., are used to find the optimization parameters, which increases the diversity and effectiveness of the solution;

[0218] This invention significantly improves the efficiency and stability of the power system and reduces the operating cost by introducing a new reactive power planning strategy and optimization method. The innovation lies in the in-depth analysis and optimization of the static load model and the discussion of the application of FACTS equipment in reactive power compensation. It not only improves the economy and reliability of the power system, but also provides a new perspective and tool for the planning and operation of the power system.

[0219] The present invention minimizes both the total operating cost and the active power loss, so as to realize the economic and stable operation of the power system. This phased optimization method can effectively reduce the complexity of the problem and improve the efficiency of solving it. At the same time, by comprehensively considering the active power loss and the total cost, a more comprehensive and optimized solution can be obtained, which provides support for the economic operation and sustainable development of the power system.

[0220] Example 2

[0221] Embodiment 2 of the present invention proposes a reactive power planning system for a power transmission system based on a steady-state load model, which is used to run a reactive power planning method for a power transmission system based on a steady-state load model of embodiment 1, such as Figure 4 As shown, including:

[0222] The power flow distribution model module is used to adopt a steady-state load model and perform power flow solution calculations through the Newton-Raphson method to obtain an initial power flow distribution model;

[0223] Weak bus and line identification module, used to identify weak buses and lines to determine the installation location of FACTS equipment;

[0224] FACTS equipment modules, including static VAR compensators and thyristor-controlled series capacitors, for reactive power compensation;

[0225] Active power loss model construction module, used to construct active power loss model, using different optimization algorithms including particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm, respectively searching for the optimization parameters of active power loss model to iteratively solve the active power loss model and obtain the minimum active power loss;

[0226] A total cost model building module, used to build a total cost model, including an objective function of the total cost model of active power loss cost, reactive power generation cost, line charging cost and FACTS equipment installation cost, and setting constraints of the total cost model including load balancing, generation limit, tap setting limit, voltage and current limit and FACTS unit limit;

[0227] The optimization parameter search module is used to use different optimization algorithms including particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm to search for the optimization parameters of the total cost model respectively, iteratively solve the total cost model, find the optimal control parameter set, minimize the total cost, and finally obtain the optimal reactive power planning scheme.

[0228] Example 3

[0229] like Figure 1 As shown, a basic connection diagram of reactive power compensation devices SVC and TCSC for reactive power support transmission system is shown. Taking IEEE 14 bus, IEEE 39 bus and IEEE 118 bus test system as examples, the present invention performs reactive power planning, provides power system data, including line data and bus data; identifies weak locations, and determines the installation locations of SVC and TCSC through power flow analysis, modal analysis and loss sensitivity analysis; performs power flow analysis, uses the proposed objective function and updated system data to calculate, and determines whether the updated solution is better than the previous solution; if the stopping criteria are not met, continues to iterate, considers and uses the optimized control variables; and saves the best solution.

[0230] Figure 3 The possible combinations of loads in the system are demonstrated, including different types of load models (CLC, RLC, ILC and MLC) and their corresponding load factors (lp and lq). These load models are used to consider load characteristics in different situations in reactive power planning studies. The load levels in different load models include commercial load level, industrial load level, residential load level and mixed load level.

[0231] Case 1

[0232] Take the IEEE 14-bus test system as an example: the system contains 14 nodes, 21 lines, 4 generators, 3 transformers and 1 capacitor (parallel) source. The weak buses are numbered 13, 14 and 10 for installing SVCs; candidate lines 7, 13 and 12 are for installing TCSCs. After executing various algorithms, the optimal total operating cost solution is as follows:

[0233] Under different load models, such as CLC, RLC, ILC and MLC, the RPL and TOC of the system before and after RPP are recorded. For example, under the CLC load model, the RPL before RPP is 0.1427pu and the TOC is $7.4989×10^6; the RPL after RPP (taking the CSA algorithm as an example) is 0.1417pu and the TOC is $7.4518

[0234] ^

[0235] ×106.

[0236] For different algorithms, such as PSO, DE, JAYA, SCA, and CSA, their convergence characteristics under different load models are analyzed. As the number of iterations increases, the power loss gradually decreases and converges smoothly. For example, the power loss of the PSO algorithm is high in the initial stage, but it gradually decreases and stabilizes as the iterations proceed; the CSA algorithm performs relatively stably throughout the process and finally achieves a lower power loss.

[0237] Case 2

[0238] Take the IEEE 39 bus test system as an example: the system contains 39 buses, 46 lines, 9 generators and 12 transformers. SVCs are installed at bus numbers 15, 4, 8 and 27, and TCSCs are installed at line numbers 9, 16 and 17. SVCs are installed at bus numbers 15, 4, 8 and 27, and TCSCs are installed at line numbers 9, 16 and 17. After executing various algorithms, the optimal total operating cost solution is as follows:

[0239] Under different load models, such as CLC, RLC, ILC and MLC, the active power loss (RPL) and total operating cost (TOC) of the system before and after reactive power planning (RPP) are recorded. For example, under the CLC load model, the RPL before RPP is 0.1427pu and the TOC is $7.4989×10^6; the RPL after RPP (taking the CSA algorithm as an example) is 0.1417pu and the TOC is $7.4518×10^6.

[0240] For different algorithms, such as PSO, DE, JAYA, SCA, and CSA, their convergence characteristics under different load models are analyzed. As the number of iterations increases, the power loss gradually decreases and converges smoothly. For example, the power loss of the PSO algorithm is high in the initial stage, but it gradually decreases and stabilizes as the iterations proceed; the CSA algorithm performs relatively stably throughout the process and finally achieves a lower power loss.

[0241] Case 3

[0242] Take the IEEE 118 bus test system as an example: the system contains 118 nodes, 186 lines, 53 generators and 9 transformers, and bus 1 is selected as the slack bus. The parallel FACTS devices are installed at bus numbers 95, 78, 11, 118 and 45, and the series FACTS devices are installed at line numbers 183, 13 and 121.

[0243] The convergence characteristics of each algorithm under different load models (CLC, RLC, ILC) are analyzed. With the increase of iteration times, the power loss gradually decreases and tends to converge stably. There are certain differences in the convergence speed and the final power loss level of different algorithms.

[0244] The experiments and analysis on the above test system show that the reactive power planning system based on the steady-state load model proposed in the present invention can effectively realize the optimal planning of reactive power and provide strong support for the stable operation of the power system.

[0245] In test systems of different sizes, each algorithm can reduce active power loss and total operating cost to a certain extent, but different algorithms perform differently under different system and load conditions.

[0246] Taking all factors into consideration, the CSA algorithm shows good performance in multiple test systems and can produce smaller RPL and TOC, but in specific applications, it is still necessary to select a suitable algorithm based on actual needs and system characteristics.

[0247] Abbreviations:

[0248] PSO: Particle Swarm Optimization, particle swarm optimization;

[0249] DE: Differential Evolution;

[0250] SCA: Sine Cosine Algorithm, sine cosine algorithm;

[0251] CSA: Crow Search Algorithm, Crow Search Algorithm;

[0252] RPP: Reactive Power Planning, reactive power planning;

[0253] RPL: Real Power Loss, active power loss;

[0254] FACTS: Flexible AC Transmission Systems, Flexible AC Transmission Systems;

[0255] TOC: Total Operating Cost, total operating cost;

[0256] SVC: Static VAR Compensator, reactive power compensation device;

[0257] TCSC: Thyristor-Controlled Series Capacitor, thyristor controlled series compensator.

[0258] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0259] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0260] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0261] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0262] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0263] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations. The present invention optimizes the existing mobile energy storage equipment, and uses a centralized control center control unit during optimization, and no other systems and equipment need to be protected.

Claims

1. A reactive power planning method for transmission system based on steady-state load model. Features: Step 1, using a steady-state load model, calculating the power flow solution of the steady-state load model to obtain an initial power flow distribution model; Step 2, identifying weak buses and lines, optimizing the installation location of FACTS devices, and using FACTS devices to compensate for the reactive power in the initial power flow distribution model of step 1 to obtain a compensated power flow distribution model; Step 3: Based on the compensated power flow distribution model obtained in step 2, an active power loss model is constructed, and different optimization algorithms are used to search for optimization parameters of the active power loss model respectively to iteratively solve the active power loss model to obtain the minimum active power loss; Step 4, constructing a total cost model according to the minimum active power loss obtained in step 3; Step 5, using different optimization algorithms to search for the optimization parameters of the total cost model respectively, and iteratively solve the total cost model constructed in step 4 to find the optimal control parameter set to minimize the total cost, and finally obtain the optimal reactive power planning scheme.

2. According to the reactive power planning method of a power transmission system based on a steady-state load model as described in claim 1, Features: In step 1, the steady-state load model includes an active and / or reactive power exponential static load model, wherein the active power P in the exponential static load model is i and reactive power Q i , expressed as follows: ln(P i )=ln(P gi -P di )+lpln(V i ) (1) ln(Q i )=ln(Q gi -Q di )+lqln(V i ) (2) In the formula, V i is the voltage of the ith bus, P gi is the active power generation, P di is the active power requirement, Q gi is reactive power generation, Q di is the reactive power demand, lp and lq are active and reactive power load factors respectively.

3. According to the reactive power planning method of a power transmission system based on a steady-state load model as claimed in claim 1, Features: In step 2, the process of identifying weak buses and lines includes: Power flow analysis, modal analysis and loss sensitivity analysis are performed to select the installation location of FACTS equipment based on the process of identifying weak buses and lines.

4. According to the reactive power planning method of a power transmission system based on a steady-state load model as claimed in claim 3, Features: The FACTS device includes a static VAR compensator and a thyristor-controlled series capacitor. The static VAR compensator and the thyristor-controlled series capacitor are used to compensate reactive power. After the thyristor-controlled series capacitor is installed, the effective reactance X eff Equal to XX TCSC , where X TCSC represents the variable reactance of the thyristor-controlled series capacitor, X represents the series impedance, and -0.6X≤X TCSC ≤0.1X.

5. According to the reactive power planning method of a power transmission system based on a steady-state load model as claimed in claim 1, Features: In step 3, different optimization algorithms include particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm; The optimization parameters of the active power loss model include generator output power parameters, transformer parameters, capacitor parameters and line parameters. The objective function of the active power loss model is expressed as follows: In the formula, P LOSS is the active power loss, N rl is the total number of lines in the network, k0 is the k0th line, G k0 is the conductance of the k0th circuit, V i is the voltage of the ith bus, V j is the j-th bus voltage, δ i is the voltage phase angle of the ith bus, δ j is the voltage phase angle of the jth bus; The constraints of the active power loss model include: equipment operation constraints, system stability constraints and network topology constraints.

6. According to the reactive power planning method of a power transmission system based on a steady-state load model as claimed in claim 1, Features: In step 4, the objective function of the total cost model is constructed and expressed as follows: TOC=C1(P LOSS )+C2(Q gen )+C3(Q lhch) +C4(Q facts ) (3) In the formula, TOC is the total cost, C1(P LOSS ) is the active power loss cost, C2(Q gen ) is the reactive power generation cost, C3(Q lhch ) is the line charging cost, C4(Q facts ) is the installation cost of FACTS equipment.

7. According to claim 6, a reactive power planning method for a power transmission system based on a steady-state load model, Features: C1(P LOSS ) According to the active power loss P LOSS Calculated, C2(Q gen ) According to the reactive power generation Q gen Calculated, C3(Q lnch ) According to the total line charging reactive power Q lhch Calculated, C4(Q facts ) According to the reactive power Q of FACTS equipment installation facts Calculated, reactive power generation Q gen , expressed as follows: In the formula, Q gen is the reactive power generation, Q gen (k) is the reactive power generation of the kth generator, a q is the reactive power cost coefficient, N g is the number of generators, b q is the reactive power cost coefficient, c q is the reactive power cost coefficient; Total line charging reactive power Q lhch , expressed as follows: In the formula, Q lnch Reactive power for charging the total line, Y ch Charging admittance for the line, N ch The number of charging elements for the circuit ch, V i is the voltage of the ith bus, V j is the voltage of the j-th bus.

8. According to the reactive power planning method of a power transmission system based on a steady-state load model as claimed in claim 7, Features: The constraints of the total cost model include load balance constraints, generation limit constraints, tap setting limit constraints, voltage and current limit constraints, and FACTS unit limit constraints. The load balance constraint is expressed as follows: in, P Gi and P Di are the generation and demand active power of the i-th bus, Q Gi and Q Di are the generation and demand reactive power of the i-th bus, B ij and G ij is the susceptance and conductance between the i-th and j-th busbars, n b is the total number of buses, is the voltage phase angle of the ith and jth buses; The power generation limit constraint is expressed as follows: in, min P gk and max P gk are the minimum and maximum limits for the generator's active power generation, min Q gk and max Q gk are the minimum and maximum limits for the reactive power generation of the generator, P gk is the active power generation of the kth generator, Q gk is the reactive power generation of the kth generator; The tap setting limit constraint is expressed as follows: in, min tap t and max tap t Set upper and lower limits for transformer taps, N tf is the number of transformers, tap t is the tap setting of the t-th transformer; The voltage and current limit constraints are expressed as follows: In the formula, min V k and max V k is the bus voltage V k The upper and lower limits of max I i-jk I is the current of line ij i-j The maximum current limit, N bs is the number of buses, N nl is the number of lines; The FACTS unit constraint is expressed as follows: in, and are the pth static VAR compensator SVC p The minimum and maximum susceptance, and The qth thyristor controlled series capacitor TCSC is q The reactance limit, N svc is the number of static VAR compensators, N tsvc The number of capacitors in series for thyristor control.

9. The method for reactive power planning of a power transmission system based on a steady-state load model according to claim 1, Features: In step 5, different optimization algorithms include particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm; The optimization parameters of the total cost model include the reactive power of the generator, the tap setting of the transformer, and the impedance and susceptance of the line.

10. A reactive power planning system for a power transmission system based on a steady-state load model, used for running a reactive power planning method for a power transmission system based on a steady-state load model according to any one of claims 1 to 9, It is characterized in that include: The power flow distribution model module is used to adopt a steady-state load model and perform power flow solution calculation on the steady-state load model to obtain an initial power flow distribution model; Weak bus and line identification module, used to identify weak buses and lines to determine the installation location of FACTS equipment; FACTS equipment modules, including static VAR compensators and thyristor-controlled series capacitors, for reactive power compensation; Active power loss model construction module, used to construct active power loss model, using different optimization algorithms including particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm, respectively searching for the optimization parameters of active power loss model to iteratively solve the active power loss model and obtain the minimum active power loss; A total cost model building module, used to build a total cost model, including an objective function of the total cost model of active power loss cost, reactive power generation cost, line charging cost and FACTS equipment installation cost, and setting constraints of the total cost model including load balancing, generation limit, tap setting limit, voltage and current limit and FACTS unit limit; The optimization parameter search module is used to use different optimization algorithms including particle swarm optimization, differential evolution algorithm, JAYA algorithm, sine-cosine algorithm and crow search algorithm to search for the optimization parameters of the total cost model respectively, iteratively solve the total cost model, find the optimal control parameter set, minimize the total cost, and finally obtain the optimal reactive power planning scheme.

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