187 results about "Probabilistic load flow" patented technology

The invention discloses a planning method for a distributed power source in a power distribution network. The planning method includes the steps that a distributed power source planning model in the power distribution network is established; according to the establishment of the distributed power source, multiple scenes are selected and time sequence features and probability features of the distributed power source are taken into consideration on the basis of analyzing the typical time sequence features of the distributed power source and analyzing the probability features of the distributed power source, and an indefinite model of the distributed power source is established; according to the load flow calculation of a power system, a probabilistic load flow calculation method based on a semi-invariant method is adopted for conducting the load flow calculation; the power distribution network accessing position and volume of the distributed power source are determined, wherein the probabilistic load flow calculation based on the semi-invariant method is embedded into the particle swarm optimization for solving the optimization problem, the method of a penalty function is used for processing constraint conditions, and the optimized optimal solution serves as the address constant volume scheme of the distributed power source. According to the planning method, the time sequence features and the randomness of the distributed power source can be involved at the same time, and the unit earning and cost, obtained after the access of the distributed power source, of the power distribution network are taken into consideration.

The invention discloses an on-line calculation method of probability power flow based on BP neural network, which mainly comprises the following steps: 1) establishing a BP neural network power flow model. 2) initializing the basic parameters of BP neural network power flow model. 3) acquiring training sample data. 4) identifying training objectives; using the training sample data, the BP neural network power flow model being trained to obtain the trained BP neural network power flow model. 5) obtaining a calculation sample. 6) inputting the training sample data obtained in the step 3 into theBP neural network power flow model trained in the step 4 at one time to obtain the training target, thereby judging the solvability of the power flow of all the training samples; calculating the tidal current value of the solvable sample. 7) performing statistic probability power flow index. That invention can be widely apply to on-line calculation of probability power flow of a power system, andis particularly suitable for the situation that the uncertainty of the power system is enhance due to high proportion access of new energy sources.

The invention discloses a method for reconstructing and modeling the uncertainty of a distribution network in a demand response viewing angle, which comprises the following steps: 1) constructing a distribution network reconstruction model, which comprises a distributed power supply parameter and an electric automobile parameter; 2) dividing the system into corresponding periods according to a peak-valley time-of-use tariff method for reconstruction respectively; and 3) taking the minimum network loss as a target function for the reconstruction to obtain the desired value of the target function by probabilistic load flow computation and solve the distribution network reconstruction model by an improved quantum evolutionary algorithm. The reconstruction model provided by the invention performs reconstruction in different periods according to the influence of one of demand response forms (peak-valley time-of-use tariff) on load to better overcome the defect of a lot of operation on a switch of the real-time reconstruction. Meanwhile, the method reconstructs data of a section without taking the influence of demand response on load into account to overcome the defects of larger network loss of an obtained topological structure in other periods.

The invention discloses a dynamical probability load flow calculation method with consideration of wind power integration. A draught-fan output model is established on the basis of the Markov chain and a state scenario tree, draught-fan output historical data are normalized, states are partitioned, and a state transfer matrix is obtained according to the change relations between the states; according to the draught-fan output state at the current moment and the state transfer matrix, the most possible states of the draught-fan output at the next moment and the probabilities of the most possible states are predicted, repeated analysis is conducted, and the state scenario tree in a future period is generated; multi-period and multi-state distribution of the draught-fan output is obtained through the state scenario tree; probability load flow calculation based on the semi-invariant method and improved Von-Mises series expansion is conducted on each time section. Calculation results can reflect the relations between probability load flows of a power grid in different time periods, probability distribution of the draught-fan output states can be reasonably predicted, the change rule of the draught-fan output states is accurately described, and the method is used for comprehensively assessing safety and stability of a power system achieving wind power integration.

The invention discloses a probabilistic power flow data acquisition method based on renewable energy uncertainty. The method comprises steps of S1 inputting a data file of electric parameters of a power grid and configuring random parameters of the power grid; S2, carrying out AC power flow calculation and probabilistic power flow calculation, and outputting MCS sampling scale, bus independent variable parameters and line independent variable parameters; S3, configuring a network equipment interval, including a bus voltage amplitude interval, a line load rate interval, and a transformer load rate interval; S4, utilizing the kernel density estimation to obtain the evaluation result of the utilization ratio of the electrical equipment; The invention can fully consider a plurality of uncertain factors of a power network, establishes a calculation program for estimating a power network power flow based on a probabilistic power flow method of Monte Carlo simulation, applies the program to apractical transmission system, analyzes a power network capacity level and a load rate, etc., and better guides the planning and evaluation of the power network.

The invention relates to a power system voltage stability risk assessment method, and in particular relates to a power system voltage stability risk assessment method capable of considering load fluctuation limit, aiming at solving the problem that the existing voltage stability assessment is single in point of view. According to the method, a probabilistic power flow simulation method of Latin hypercube sampling is applied to voltage stability analysis of a power system, and the situation of system crash caused by load power radical change and system network framework structure change can be studied. The voltage risk index, load node type risk index, network load bearing capacity risk index and financial loss risk index are taken as basis, and the voltage stability of the system is comprehensively analyzed by the multiple indexes from multiple points of view, so that the nodes with weak voltage in the system, the nodes with weak load fluctuation, the range of load bearing capacity of the system and the nodes with high financial loss risk in the system can be found. The power system voltage stability risk assessment method provides powerful basis for carrying out voltage monitoring, load monitoring, network planning and economic evaluation on the power system.

The invention discloses a stack denoising autocoder-based probabilistic power flow online calculation method. The method mainly comprises the following steps of 1) building an SDAE probabilistic powerflow model; 2) obtaining training samples of the SDAE probabilistic power flow model; 3) initializing the SDAE probabilistic power flow model; 4) training the SDAE probabilistic power flow model to obtain a trained SDAE probabilistic power flow model; 5) obtaining calculation samples; 6) inputting calculation sample data obtained in the step 5) to the trained SDAE probabilistic power flow model in the step 4 once, obtaining training targets, thereby judging power flow solvability of all the training samples, and calculating power flow values of the solvable samples; and 7) performing statistics on probabilistic power flow indexes. The method can be widely applied to the probabilistic power flow online calculation of a power system, and is especially suitable for the situation of power system uncertainty enhancement due to high-ratio access of new energy.

The invention relates to the field of planning of power transmission networks of electric power systems. For assisting planning personnel of the power transmission network to evaluate a power grid capacity margin in the future, discriminate system weak link recognition and an unreasonable grid structure, balance reliability and economy of a power grid planning scheme, and the like, the invention provides a calculating method of a utilization rate of an electric transmission line based on probability load flow. The technical scheme includes that the calculating method comprises the following steps: 1), carrying out definition description on the utilization rate of the electric transmission line; 2), building a probability distribution model of loads of N years in the future and a generator shut-down probability model; 3), generating random loads and generator random shut-down states; 4), serving lowest cost of total output of each generator set as an economic distribution objective function, and satisfying constraint conditions at the same time; 5), calculating line load flow values through a direct current load flow method or an alternate current load flow method; and 6), recoding the line load flow values, obtained by simulation everytime, of the line. The calculating method is mainly applied to the planning of the power transmission networks of the electric power systems.

The invention discloses a rapid probabilistic load flow calculation method considering the static power frequency characteristics of an electric power system. The rapid probabilistic load flow calculation method comprises the steps that electric power system parameters needed by conventional load flow calculation are extracted from the electric power system and are initialized; a frequency variable to be solved is added to a conventional load flow calculation model, an improved rapid decoupling load flow module is established, and the normal state of the node voltage, the system frequency and the branch power of the variable to be solved are worked out; cumulants of each order of the node voltage, the system frequency and the branch power are worked out; through Gram-Charlier series expansion, the cumulative probability distribution function and the probability density function of the node voltage, the system frequency and the branch power of the variable to be solved are worked out. According to the rapid probabilistic load flow calculation method, the influence of uncertain factors on the system frequency in the electric power system and the distribution characteristics of the system frequency are considered in the process of probabilistic load flow analysis, the calculation speed is high, and a complete comprehensive assessment can be provided for the safe and economical operation analysis and the stability analysis of the electric power system.

The invention discloses an electric power system static safety assessment method based on a probabilistic tide. Statistical information of the random quantity in a system is obtained according to historical data; mutual conversion between a relevant non-normal random variable and an independent normal distribution random variable is achieved by improving Nataf conversion. By means of the electric power system static safety assessment method based on the probabilistic tide, arbitrary probability distribution of many random factors in the electric power system can be coped with, the correlation among the random factors is considered, the processing difficulty of the correlation is reduced, and the electric power system static safety assessment method is suitable for assessing the influence of all kinds of uncertain factors in the electric power system on the static safety of the electric power system.

The invention discloses a Latin hypercube sampling method probabilistic power flow calculation method based on a normal Copula function. The method is characterized by comprising the following steps: 1) according to the correlation coefficient matrix of a new energy generated output variable, utilizing the normal Copula function to generate a random number matrix which meets the correlation of the new energy generated output variable; 2) utilizing the Latin hypercube sampling method to sample the random number matrix generated in the 1), and establishing a sample matrix of the new energy generated output variable according to the inverse function of the cumulative distribution function of the new energy generated output variable; and 3) taking the sample matrix, which is established in the 2), of the new energy generated output variable as an input quantity to carry out probabilistic power flow calculation, obtaining a discrete result of an output variable, and utilizing nuclear density estimation to fit the discrete result of the output variable to obtain the probability density function of the output variable. Calculation time is shortened while calculation precision is improved.

The invention discloses a probability load flow calculation method for a photovoltaic power contained distribution network. The method comprises the steps as follows: firstly, obtaining the actual testing data of the output power of the photovoltaic power and the parameters of a grid line and a load; secondly, estimating the probability density function of the output power of the photovoltaic power based on a nonparametric kernel density estimation theory, as well as estimating the probability density function of the load through utilizing normal distribution; thirdly, selecting a distribution point based on a linear independence principle; fourthly, establishing a chaos polynomial between the voltage of the distribution point and that of a node; fifthly, calculating the mean value of the node voltage. The invention has the advantages that the method is simple, strong in practicability, high in estimating accuracy, strong in universality, and convenient for wide application, so that the method can be widely applied to the electrical power system probability analysis of the photovoltaic power contained distribution network.

The invention discloses a probabilistic load flow algorithm based on a semi invariant and series expansion method. By the probabilistic load flow algorithm, the uncertainty of a system under access of large-scale new energy sources can be reflected, a Monte Carlo sampling technology is introduced based on the analysis of a traditional semi invariant method to calculate the output of a wind power generator set, complicated mathematical analysis and calculation are prevented, and the probabilistic load flow algorithm can be applicable to a new energy output model with arbitrary random distribution; and relatively high adaptability and favorable convergence can be achieved when photovoltaic or other new energy sources are accessed to the system except wind and power.

The invention discloses a probabilistic load flow calculation method, giving consideration to photovoltaic non-linear correlation, for a power system, and the method comprises the following steps: building a photovoltaic power station probability model; building a power sample space of a photovoltaic power station, carrying out the sampling of an output probability density function of a photovoltaic electric field through employing an LHS algorithm, and then obtaining a power sample space of the photovoltaic power station; calculating the probabilistic load flow of a photovoltaic grid-connected system, enabling all groups of sample values in the generated photovoltaic output sample space to be sequentially substituted into a load flow equation for common load flow calculation, obtaining load flow samples of all nodes and branch circuits comprising a photovoltaic grid-connected node, and obtaining a sample space of an output random variable; carrying out the probability assessment of aload flow calculation index, and obtaining the probability statistics characteristics of an output variable needed by photovoltaic grid connection and an index through a probability statistics method.The method provided by the invention enables a probability calculating result to be more accurate, and achieves the accurate description of the uncertainty of the grid-connected system under the condition that the sampling scale is smaller.

The invention relates to a power distribution network single photovoltaic digestion capability evaluation method in consideration of voltage out-of -limit risk, which comprises the following steps: (1) the parameter information of a target power distribution network is acquired; (2) a N<d>-day historical load data sample of each distribution transformer of the target power distribution network iscollected, and with the distribution transformer as a unit, a load time sequence model based on multi-parameter normal distribution is created; (3) a N-day historical output data sample of a photovoltaic power station of a target region is collected, and a photovoltaic relative output time sequence model based on multi-parameter beta distribution is established; (4) according to the load time sequence model based on multi-parameter normal distribution and the photovoltaic relative output time sequence model based on multi-parameter beta distribution, a semi-invariant-based probabilistic load flow method is adopted to calculate a voltage out-of -limit risk evaluation index; (5) a voltage out-of -limit risk limit Rvs_limit is set, and a mixed approximation method is adopted to evaluate the photovoltaic digestion capability of the power distribution network. The method takes the time sequence and uncertainty of distributed loads and photovoltaic output into full consideration, and by quantitatively evaluating the voltage out-of -limit risk of the power distribution network, the method provides a reference for the evaluation of the capacity of the photovoltaic-connected power distribution network.

The invention discloses a quantitative optimal configuration method of a wind-solar hybrid power system based on a discrete probability model. The method is characterized in that discrete probability distribution is utilized to show random variation factors in the system, and a multi-objective optimization model is established with maximum electric energy adequacy and minimum power supply system total investment and voltage out-of-limit probability being optimization objectives; then, a probabilistic load flow algorithm is subjected to partial improvement, expectation value and increment of a discrete random variable are studied separately, and through moment calculation and semi-invariant conversion, and by applying series approximation, probability distribution of the node voltage and the system electric energy adequacy is obtained, and furthermore, objective functions can be calculated more efficiently and quickly; and finally, the method adopts a parallel-acceleration non-dominated sorting genetic algorithm having an elitist strategy to solve a Pareto optimal solution set of the optimization objectives. Compared with a conventional optimal configuration method, the method can reflect the running state of the system comprehensively, and provides more complete information for policy makers.

The invention discloses an RBF neural network-based probability power flow online calculation method. The calculation method mainly comprises the following steps of 1) establishing an RBF neural network probability power flow model; 2) obtaining a training sample x of the RBF neural network probability power flow model; 3) performing processing on data x of the training sample; 4) performing training on the RBF neural network probability power flow model; 5) obtaining a calculation sample; 6) inputting the calculation sample data obtained in the step 5 into the RBF neural network probability power flow model completely trained in the step 4 in one time to obtain a training object, so as to judge the power flow solvability of the training sample, calculating the power flow value of the solvable sample, and performing counter normalization processing on the calculation sample data; and 7) performing statistics on a probability power flow index. The calculation method can be widely applied to probability power flow online calculation of the power system, particularly suitable for a condition of the power system with reinforced uncertainty caused by high proportion access of new energies.

The invention provides a power grid power transmission margin control method suitable for large-scale wind power access. The method includes the steps that (1), security constraint unit commitment optimal computation is carried out by adopting a mixed integer planning method to obtain starting and stopping states and power output plans of a conventional power generation unit meeting an objective function and constraint conditions; (2), the influence on power transmission margin by multi-period wind power randomness is quantized by adopting a probability power flow method to obtain a power flow probability distribution range of a power grid branch or a power transmission fracture surface; (3), whether the power flow probability distribution range meets the requirement of a confidence interval or not is judged, if not, the step (1) is executed again, unit commitment optimal computation is carried out again, and the power output plans are adjusted. Compared with the prior art, the power grid power transmission margin control method suitable for large-scale wind power access fully considers randomness of wind power, improves the using effect of short-period security constraint dispatching plans in a wind power access area and enhances performability of the short-period plans.

The invention provides a power distribution network transformer planning method considering uncertainty of photovoltaic power generation output and a total life cycle cost, and belongs to the field of power distribution network planning. The power distribution network transformer planning method comprises the following steps: firstly providing a power distribution network transformer risk constant volume method based on the opportunity constraint theory by considering the output uncertainty of distributed photovoltaic power generation; calculating a distribution network probability trend after the access of the distributed photovoltaic power generation by using a three-point estimation method on this basis, meanwhile constructing a target function based on the total life cycle cost, and finally providing an uncertain power distribution network transformer planning model based on the total life cycle theory. An example simulation result indicates that, compared with the traditional deterministic power distribution network transformer planning method, the method provided by the invention has the advantages that all costs within a total life cycle of the equipment are accurately measured, the influence of the uncertainty of the distributed power supply to the constant volume and model selection of the equipment is accurately calculated, and the limits of the constant volume and model selection of the power distribution network transformer are compensated, thereby effectively improving the economical efficiency of the power distribution network transformer planning, and the method provided by the invention is more scientific.

The invention discloses a probabilistic power flow calculation method considering distributed power supply and electric vehicle access. The method comprises steps: a probability model of a distributedpower supply node and an electric vehicle node is established; according to conventional power flow calculation, a power grid connection topology, line impedance, node injection power and other powergrid basic data are obtained; a Latin hypercube sampling method based on a random walk theory is adopted to sample input variables to obtain a sample matrix; according to the relationship between thesample matrix and semi-invariants and an origin matrix, the each-order semi-invariant of the input variable is calculated; a cumulative distribution function of a state variable and a branch power flow is solved through series expansion; and a semi-invariant method is used to calculate the probabilistic power flow. Uncertain power injection of photovoltaic and wind power in the distribution network is considered, random load with the electric vehicle as an example is also considered, the result is more accurate, the calculation precision is high, the sampling speed is quick, and the new energy acceptance ability of the power system is enhanced.

The invention provides a spatio-temporal correlation day-ahead plan load flow analysis method with uncertainty being taken into consideration. The spatio-temporal correlation day-ahead plan load flow analysis method comprises the following steps: obtaining next-day forecast wind speed of wind power plants in 96 time period within 24 hours; obtaining next-day output of the wind power plants; obtaining forecast error distribution of the next-day output of the wind power plants; carrying out independence conversion on random variables having spatio-temporal correlation; calculating semi-invariant of a load flow in each line; and determining relevant information for dispatching. The method carries out engineering algorithm processing on the forecast error distribution having correlation, thereby solving the problem that probability distribution having correlation cannot be obtained by utilizing a series expansion method directly. Analysis is carried out on the next-day load flow of each line in each time period through a Gram-Charlier series expansion method ; through such analysis method, probabilistic load flow problem can be solved conveniently and effectively; the method has a practical value; and the present series expansion method commonly used in medium / long-term probabilistic load flow analysis is expanded to short-term plan load flow analysis, thereby providing more data support for economic dispatching.

The invention discloses a probabilistic power flow analysis method considering primary frequency modulation uncertainty. A dynamic power flow model considering primary frequency modulation characteristics is established, the problem of uncertainty in the model is handled by applying a point estimation method, a Newton-Raphson's method is adopted to solve the certainty power flow problem, and accordingly statistical characteristic values of the primary frequency modulation characteristics of a system and system frequency, node voltage and other state variables during coefficient uncertainty are considered under the situation of disturbance uncertainty. Due to the fact that the necessarily existing uncertainty of a power generator and load unit regulation power is considered in the dynamic power flow model design considering primary frequency modulation characteristics, the state variables closer to the actual conditions can be obtained, and more accurate data can be provided for relevant analytical calculation. By means of the probabilistic power flow analysis method, the operating state of the system can be more effectively and accurately described, and a foundation is laid for further analytical calculation of the power system. In addition, the point estimation method has the advantages of being high in speed and low-order accuracy rate and the like, and an effective way is provided for achievement of the method.

The invention discloses a probability load flow calculation method based on multi-zone interactive iteration. The probability load flow calculation method comprises the following steps: firstly, sampling new energy electricity generation power variable by using an improved Latin hypercube sampling method, and establishing a sample matrix of the new energy electricity generation power variable; partitioning a power grid by using a node tearing method, and establishing a multi-zone interactive iteration calculation model; finally performing probability load flow calculation. According to the probability load flow calculation method disclosed by the invention, the tail characteristics of random variable probability distribution can be considered, and the new energy electricity generation power variable is sampled by using the improved Latin hypercube sampling method, so that the validity of samples is improved; as the power grid is partitioned by using the node tearing method, and the multi-zone interactive iteration calculation model is established, parallel computing can be achieved, Jacobian matrix dimensions of load flow calculation can be reduced, and multi-zone probability load flow calculation can be achieved.

The invention discloses an active distribution grid load flow calculation method. The method comprises the steps that network parameters of a power distribution system, nodal load power and relevant parameters of a probabilistic model of the power distribution system are obtained, and a dynamic reactive optimization model of a distribution grid containing intermittent DG is built according to the chance-constrained programming method; according to the load flow calculation method based on the cumulant method, the probabilistic load flow of the model is calculated; according to the configuration information of a compensating capacitor set, the number of control variables is determined, and the control variables are encoded in an integer encoding mode; a genetic algorithm with an elitist strategy is adopted to conduct optimization solution on the reactive optimization model, and node voltages, the phase angle, the branch circuit power and the power loss of the distribution power system are obtained. According to the method, the compensating capacitor set serves as reactive-load compensation equipment, the nodal load power and the time-varying characteristics of the intermittent DG output are taken into full consideration through the reactive optimization method, so that the load flow distribution of the power distribution system tends to be stable, and the running benefit and the voltage quality achieve comprehensive optimization.

The invention discloses a regional power grid carbon emission management method suitable for a new energy connection background. The method comprises the steps that S1, a regional carbon emission management model is established; S2, probabilistic flow based on a stochastic response surface method (SRSM) is adopted to calculate power grid flow distribution containing multiple associated new energy power stations; S3, an imperialistic competitive algorithm is adopted to solve the multi-target regional carbon emission management model to obtain a Pareto non-inferior solution set; S4, a penalty function is introduced to check and adjust obtained Pareto solutions, and node voltage limit exceeding or branch overloading is avoided; S5, an interactive satisfaction decision making method is utilized to select an ''optimal solution'' of the model from the Pareto solution set according to different demands of system operating personnel; and S6, comprehensive benefits of different schemes are evaluated by changing settings of new energy power station connection locations and all objective function reference memberships. Through the method, comprehensive management of practical power system carbon emission can be realized, and a new thought is provided for evaluation of address selection schemes of new energy stations.

The invention discloses a probability load flow calculation method considering the admitting ability of a power grid. The method comprises the following steps that 1, a cumulative distribution function of a new energy power generation power variable is built according to the admitting ability of the power grid to new energy power generation power, wherein the cumulative distribution function is described in the form of a piecewise function; 2, the sampling frequency between all sections of the new energy power generation variable is calculated according to the cumulative distribution function F(pk) of the built new energy power generation power variable based on the proportional distribution principle, then a Latin hypercube sampling method is utilized for sampling all the sections of the new energy power generation power variable, and a sample matrix of the new energy power generation power variable is built; 3, the sample matrix of the new energy power generation power variable is adopted as an input variable for probability load flow calculation, a disperse result of an output variable is obtained, an empirical distribution function is utilized for fitting, and a probability distribution function of the output variable is obtained. The application range of the Latin hypercube sampling method is widened, and calculating precision is guaranteed.

The invention discloses a probabilistic load flow calculation method considering static frequency characteristic uncertainty. The method comprises the steps of establishing a probabilistic load flow calculation model considering static frequency characteristic uncertainty of a generator set and a load by combining an idea of a dynamic load flow according to a characteristic of primary frequency modulation performance uncertainty of load generation in a power system; performing analytical calculation by combining Monte Carlo sampling and a cumulant method as well as Gram-Charlier expansion series; and providing probability distribution of active power output of the load and a generator and probability distribution of active power load flows of lines after a fault of the system. Therefore, a calculated result is accurate and close to a running status of an actual power grid.

The invention discloses a TCSC optimal configuration method based on probabilistic load flow control. The TCSC optimal configuration method is applied to an electric power system and is characterized by including the following steps of acquiring original data, acquiring uncertain factor values, conducting sampling and load flow calculation on the uncertain factor values, acquiring the load rates of all branch circuits, selecting the branch circuits with the load rates exceeding heavy load rates to be used as the branch circuits for mounting TCSCs, obtaining series compensation branch circuits, establishing an improved optimal load flow model, conducting sampling and optimal load flow calculation on the uncertain factor values again, acquiring the optimized values of TCSC reactance values, and mounting the TCSCs with the reactance values being the optimizing values at the series compensation branch circuits. Accordingly, the TCSC optimal configuration method is achieved. According to the TCSC optimal configuration method, the influence of uncertain factors in the electric power system can be considered more comprehensively, the load flow of the electric power system can be controlled more effectively, and therefore the safe operation of the electric power system can be better facilitated.

The invention provides an electrical interconnection integral energy system optimization operation analysis method based on probability trend; the method comprises the following steps: modeling, considering couplings between models, analyzing operation modes, wherein the modes include a fixed hot point FTL mode, a fixed electric heat FEL mode, and a mixed operation FHL mode; analyzing uncertain factors, wherein the uncertain factors comprise load, wind power plant output and photovoltaic power plant output randomness; using a point estimation method to build sampling points according to distribution conditions of each random variable; using a heredity algorithm to solve the generating cost minimum cost under various operation modes, thus obtaining the generating cost statistics amount. The method applies three operation modes under the integral energy system probability trend, parses the whole system generating cost changes caused by the state variable changes under the three operation modes, calculates the whole integral energy system generating cost, searches the optimal operation mode according to the generating cost probability distribution curve under the three operation modes, and thus providing references for electric power scheduling personnel.

The invention provides a method and a system for calculating a probabilistic load flow considering unbalanced power distribution. The method comprises the following steps: acquiring basic data; calculating the half invariant of a bus load and the half invariant of new energy unit output according to the acquired basic data; and obtaining the probability distribution of voltage and branch power flow considering injection power fluctuation and unbalanced power distribution according to the half invariant of the bus load and the half invariant of the new energy unit output. Through the technicalscheme provided by the invention, the unreasonable problem that unbalanced power in the probabilistic load flow in a traditional half invariant method is undertaken by balancing bus is solved, and theaccuracy and practicability of the probabilistic load flow in the half invariant method are improved.