48 results about "Sequential monte carlo simulation" patented technology

The invention provides a power supply capability evaluation method of a power distribution network based on confidence capacity of a distributed power supply. The power supply capability evaluation method comprises building output models of the distributed power supply, wherein the output models include a wind turbine output model and a photovoltaic output model; building a power distribution network power supply capability calculating model based on confidence capacity of the distributed power supply, wherein a load in the model is supplied with power by the power distribution network together with the connected distributed power supply; carrying out verification with constraint conditions, wherein reliability of the power distribution network and a calculating method based on the loss of load expectation are taken as the main constraint conditions; evaluating reliability of the power distribution network containing the distributed power supply: using a Sequential Monte Carlo simulation method to evaluate reliability of the power distribution network containing the distributed power supply; optimizing and adjusting the load in the feeder line area: adjusting the load in the feeder line subarea through iteration on the premise of system reliability, thereby obtaining effective load carrying capacity of the distributed power supply; calculating the power supply capability of the system: using Matlab (matrix laboratory) to calculate the maximum power supply capability of the system based on the power distribution network power supply capability calculating model.

The invention discloses an active power distribution network reliability analysis method based on pseudo sequential Monte Carlo simulation and belongs to the technical field of power system control. The method utilizes a pseudo sequential Monte Carlo simulation method to perform reliability analysis on an active power distribution network, the operation time is shortened, and the analysis accuracy is also improved. In addition, characteristics of the active power distribution network are further fully considered in the method, states of a communication system and power electronic devices in power distribution automation are involved in system state sampling, intelligent operation is performed on the system in a normal state, processing is performed through a traditional passive power distribution network during breakdown, the method is consistent with the actual situation of the active power distribution network, and obtained reliability data have confidence level.

The invention discloses a method for evaluating reliability of a large power grid comprising a wind power station, which belongs to the technical field of evaluation on reliability of a power system. The method comprises the following steps of: firstly, establishing a wind power station time sequence power output model; then combining the wind power station time sequence power output model and a large power grid system to establish a wind power station large power grid reliability model; establishing an index system for evaluating the reliability of the large power grid comprising the wind power station; finally, evaluating the reliability of the large power grid comprising the wind power station by applying a sequential Monte Carlo simulation method. According to the invention, the related reliability model and index system are respectively established from the power grid side and the wind power station side for balancing influence of switching-in of the wind power station on reliability of the large power grid; the integral reliability condition of the system and contribution of the wind power station to the adequacy of the large power grid can be more sufficiently reflected.

The invention discloses a wind power plant probability output power calculation method considering a complex wake effect model in the technical field of the wind power plant output power control. The wind power plant probability output power calculation method comprises the following steps of: initializing a parameter; establishing a wind power plant wake effect model; initializing a simulated age limit n; obtaining the operation state curve of each wind power generation set and a connection cable of the wind power plant with a sequential Monte Carlo simulation method; within the simulated age limit n, respectively simulating the wind speed and the wind direction by Weibull distribution and a wind rose to obtain the wind speed and the wind direction sequence of the wind power plant with the scale of M; meanwhile, initializing time t; according to the wind speed and the wind direction of the wind power plant at each moment, calculating the output power of non-failure wind power generation set of the wind power plant at a corresponding time moment so as to calculate the total output power of the wind power plant; and with a clustering method, processing the total output power sequence of the wind power plant so as to obtain a wind power plant probability output power curve. According to the wind power plant probability output power calculation method disclosed by the invention, the precision of the wind power plant output power model is effectively improved, and the accuracy of the wind power plant probability output model is guaranteed.

The invention provides a service life prediction method of a vertical machining center milling cutter updated by Bayesian information on the basis of a state space model. According to the structural features of the vertical machining center milling cutter, a degeneration signal of the vertical machining center milling cutter is collected, and the obtained signal is processed to obtain a degeneration information characteristic quantity; and according to the obtained degeneration information characteristic quantity of the vertical machining center milling cutter, the state space model used for predicting the service life of the vertical machining center milling cutter is established. On the basis of a Bayesian theory under probability statistics, an established service life prediction model of the milling cutter is subjected to information alternation by sequential Monte-Carlo simulation, above parameters are estimated in real time, and the service life predication method is established. A residual life probability density distribution function of the vertical machining center milling cutter is output according to a failure threshold of the milling cutter to obtain a residual life prediction value. The service life prediction method has the beneficial effects that the work reliability of the cutter is improved through the on-line prediction of the residual life of the cutter, sudden accidents are reduced, and heavy losses and casualties are avoided.

Disclosed is a transmission network risk assessment method considering substation influence. The method includes the steps of first collecting reliability parameter data of a local power grid and eachsubstation internal component as well as basic parameter data of the substation internal relay protection; then establishing a Markov state model of the power grid and the substation internal components and a relay protection implicit failure model, and determining the probability of occurrence of the components and relay protection states; then sampling a system state by using an improved non-sequential Monte Carlo simulation method; and finally, analyzing the load loss risk of the system state by using a load shedding optimization model based on the DC flow, calculating a risk index of thetransmission network and assessing the risk of the transmission network according to the risk index. The method in the invention can reflect the influence of the substation on the risk assessment of the transmission network to the greatest extent, further improves the accuracy and real-time performance of risk assessment under the premise of meeting the calculation precision, and can provide a reliable basis for power grid operators to understand the real-time risk of the power grid.

The invention relates to an evaluation method of an intermittent energy generating capacity confidence considering network constraint. The method includes: obtaining a planning year power grid plan typical operation mode; sampling time series data G (t) of annual conventional units, loads, and line commissioning by employing the sequential Monte Carlo simulation technology; performing wind-power annual output time series sampling by employing the sequential Monte Carlo simulation technology; calculating the power flow of a generating system; performing static security analysis and auxiliary decision; calculating the reliability of the generating system; calculating the capacity confidence of newly-increased energy; and calculating the capacity confidence of all the intermittent energies. According to the technical scheme, a planning scheme including generation, load, and a grid structure is obtained via power grid planning data, statistical rules are analyzed with the combination of historical wind speed and historical output information of a wind farm, annual random production and simulation of a sequential Monte Carlo model are performed, network constraint conditions are considered, and the generating capacity confidence of new energy is evaluated.

The invention discloses a method for capacity credit assessment of a photovoltaic power generation system. The method comprises: putting forward four factors that affect the capacity credit of a photovoltaic power generation system, i.e., the photovoltaic permeability, the data sampling time interval, the photovoltaic-load output fluctuation and the time sequence correlation between photovoltaic output and load fluctuation; calculating the reliability of the power system by using sequential Monte Carlo simulation and solving the capacity credit by the Secant Method; establishing a three-layer error back propagation neural network between the four factors and the capacity credit; training the neural network by using input and output data sets which are obtained under different irradiation modes; and obtaining the capacity credit of the photovoltaic power generation system under the given condition by using the generalization ability of the neural network which is already trained. The method for capacity credit assessment of a photovoltaic power generation system can be used for planning and design of photovoltaic composite generation and transmission systems, requires no sequential Monte Carlo simulation individually for each specific photovoltaic power generation system, and solves the problem of poor universality of the prior art.

The invention discloses a distribution network reliability assessment method considering electric vehicle access, which comprises the steps of establishing a distribution network component reliability model; defining an electric vehicle reliability index considering distribution network fault influences; carrying out processing on data by adopting a Latin hypercube sampling based time sequential Monte-Carlo simulation method, and assessing the reliability of a distribution network considering the electric vehicle access. The significant effects are that mutual effects between a circumstance that electric vehicles act as energy storage devices and the isolated distribution network reliability are considered, the number of electric vehicles required to be accessed to the distribution network can be reasonably determined by the method, and configuration of other power supplies of the distribution network containing the electric vehicles can also be reasonably determined, thereby improving the reliability of the distribution network.

The invention discloses an evaluation method of acceptance capability of new energy based on sequential Monte Carlo simulation. The invention provides an acceptance capability analysis model, so that limiting factors of the acceptance capability of the new energy, such as peak regulation, frequency modulation and line power flow restriction, can be analyzed, and a weak link of a system can be recognized according to abandoned electric quantity of the new energy, which is caused by the different limiting factors. According to the evaluation method, an evaluation framework for the acceptance capability of the new energy based on the sequential Monte Carlo simulation is established, the time-dependent factors in the system, such as change of an operation mode, load fluctuation, new energy fluctuation, water and electricity output arrangement, component fault and unit maintenance, are considered, the evaluation indexes, such as the abandoned electric quantity of the new energy, the electric energy production of the new energy and the acceptance capability value of the new energy, can be provided for a planner, the water and electricity output is arranged according to a principle of fully utilizing the water and electricity quantity, the peak regulation effect of water and electricity is fully exerted, and furthermore, in comparison with the previous evaluation method, the evaluation method is more complete.

The invention discloses a distribution system reliability evaluation method based on an equipment life cycle. the method comprises steps: a fault rate model for each operation period in the equipment life cycle is built; influences of a time-varying fault rate of the equipment on system reliability analysis are considered, a sequential simulation method is adopted to generate aging failure time, and the aging unavailability of the equipment under the same aging time distribution is determined; and in a sequential Monte-Carlo simulation method for system reliability, a simulation model for the equipment life cycle fault rate is built, and the distribution system reliability calculation based on the equipment life cycle fault rate is realized. in order to facilitate analysis and comparison on the equipment reliability cost, a reliability investment / reward analysis model is built on the basis of a present value method, the necessity of the equipment life cycle fault rate towards the distribution system reliability planning is expressed through an example, and an important role is played in improving the rationality and the economy of planning of the power system.

The invention discloses a method and an apparatus for assessing the reliability of a new energy power distribution network. The method comprises the steps of obtaining a fault probability distribution function of each component; generating uniformly distributed random numbers between 0 and 1, and obtaining working time and fault time of each component; performing optimization on working time of all components based on a fruit fly optimization algorithm, and obtaining the component with shortest working time as a fault component; judging whether the fault component is a feeder line component or not; if yes, performing fault analysis on a feeder line region, and determining a fault type and load point data; performing statistics on a load point index according to the load point data; and performing statistics on a system reliability index and a load point reliability index according to the load point index. According to the method and the apparatus, a running condition of the new energy power distribution network containing DG, EV and the like can be quickly simulated by improving a conventional sequential Monte Carlo simulation method, and the load point data of the power distribution network can be calculated more quickly, so that the crash is avoided, the memory occupation is reduced, and the user experience is improved.

The invention provides a pre-disaster first-aid repair personnel pre-deployment method for improving the power grid recovery speed, which comprises the following steps: 1) after predicting an imminentdisaster, obtaining the fault probability of each element according to a power grid element vulnerability curve in combination with meteorological prediction and the geographic information of a powergrid, and generating a fault scene under the disaster through sequential Monte Carlo simulation; 2) acquiring information of a power grid, a repair team and deployable positions, establishing a two-stage stochastic programming model, formulating a deployment scheme of first-aid repair personnel in the first stage, and performing repair and recovery collaborative optimization according to a faultscene in the second stage to minimize power failure loss; and 3) carrying out decoupling solution on the two-stage stochastic programming model through a Progressive Hedging (PH) algorithm. Accordingto the invention, before the upcoming meteorological disasters are predicted, emergency maintenance personnel are deployed in the key links of the power grid, so that the emergency response capabilityof the power grid after the disasters is improved, the repair of fault elements is accelerated, and reasonable suggestions are provided for the formulation of power grid emergency plans.

The invention discloses a method for evaluating the importance of a power system element based on restoring force. The method comprises the following steps: 1) determining the type and occurrence property of a disaster; 2) obtaining vulnerable element types and related fault probabilities under disasters; 3) acquiring fault configuration conditions of elements in the system after disasters occur by utilizing non-sequential Monte Carlo simulation; 4) establishing a post-disaster optimal recovery strategy model, and proposing an objective function and constraint conditions; and 5) simulating thepost-disaster recovery process for multiple times to obtain the repair time of each element, and performing sorting by using a Koplan sorting method to obtain the importance sorting of the elements.By utilizing the method, the element importance of the power system under various natural disasters and man-made disasters can be solved, and the disaster type and characteristics are considered in the solving process. The element importance result obtained by the method can provide reference for making a post-disaster recovery strategy and determining a pre-disaster element reinforcement scheme.

The invention discloses a power grid risk assessment method considering component reliability of a photovoltaic power plant. The power grid risk assessment method comprises the steps of: firstly, classifying key components of the photovoltaic power plant according to a component failure mechanism, establishing a two-state model of an inverter and a multi-state model of a photovoltaic array respectively, and generating a photovoltaic power plant output power probability model considering component reliability through state sampling; secondly, extracting a photovoltaic output value according tothe established model, determining shutdown states and system loading states of a conventional generator and a conventional line, and acquiring a deterministic system state of a single sampling; thirdly, calculating a load shedding amount of a one-time deterministic sampling system by adopting a DC power flow optimal load shedding algorithm; and finally, calculating a system loss-of-load probability and an expected energy not supplied risk indicator through non-sequential Monte Carlo simulation. The power grid risk assessment method regards all the components of the photovoltaic array as a whole, classifies the components into a multi-state model according to a cumulative distribution function of the photovoltaic array, effectively alleviates the problems of large memory consumption, slowsampling speed, low calculation efficiency and the like caused by sampling the state of each photovoltaic components, and improve the efficiency of risk assessment for a power grid containing the photovoltaic power plant.

The present invention discloses an active distribution network reliability assessment method. Based on the improved new sequential Monte Carlo simulation method, the regional division method is used to carry out active distribution network reliability assessment, and in order to improve the efficiency and accuracy of the analysis, the present invention innovatively proposes to use the power circleto divide the islands and to analyze and calculate the islands; in the reliability assessment process, the importance of the load is fully considered, and by taking the maximal equivalent load contained in the islands as an objective, continuity of power supply for important loads can be fully guaranteed; and the randomness and active coordination of the distributed energy output power in the active distribution network are fully considered, whether the active distribution network needs to be reconstructed is determined, and according to the reconstructed network structure, the current reliability index of each load point is corrected, so that the efficiency and accuracy of the active distribution network reliability assessment can be effectively improved.

The invention relates to a power distribution system power supply capability evaluation method considering the influence of multiple times of transfer on reliability, which comprises the following steps: establishing a medium-voltage power distribution system power supply capability evaluation model, which specifically includes taking the maximum power supply capability of a medium-voltage power distribution system as an objective function, taking the reliability constraint, the matching constraint of the main transformer and the outgoing feeder, the load rate constraint of the main transformer and the feeder and the contact capacity constraint of the main transformer and the feeder as constraint conditions, and thus establishing the medium-voltage distribution system power supply capability evaluation model; performing reliability evaluation on the medium-voltage power distribution system, including state selection and sampling based on sequential Monte Carlo simulation; analyzing theinfluence of the fault mode of multiple times of transfer; and reducing load needing to be transferred in the fault mode, distributing and transfering same. The margin of the power supply capacity ofthe power distribution system can be released on the premise of meeting the reliability constraint of the power distribution system in a targeted manner, and the power supply potential is mined. Themanagement level of urban power distribution network planning is improved, and reasonable development of urban power grid construction structures and planning technologies is promoted.

The invention relates to a micro-grid reliability evaluation method containing an electric vehicle charging station, which comprises the following steps of: 1) obtaining the state of charge of an electric vehicle power battery at each time point according to the operation characteristics of an electric vehicle in a micro-grid; 2) establishing an interactive response power calculation model according to an internal power interactive strategy of the microgrid; 3) carrying out regional division on the microgrid according to the positions of the network switches and the on-off characteristics of different types of switches; 4) performing fault isolation by adopting different switch action modes according to different areas where internal fault points are located during isolated island operation of the micro-grid; and 5) adopting a sequential Monte Carlo simulation method to evaluate the operation reliability of the microgrid containing the electric vehicle charging station. Compared with the prior art, the micro-grid reliability evaluation method conforms to the development trend that the electric vehicle charging station is connected into a power grid at the present stage and in the future, and is comprehensive in consideration and wide in application.

The invention discloses a method and system for improving the toughness of a power distribution network, and the method comprises the steps of carrying out the importance evaluation of a power distribution network assembly in typhoon weather, building an element fault rate model under the action of storm wind, carrying out the sampling of the state of a wind power generation system through a non-sequential Monte Carlo simulation method, and establishing an optimal recovery strategy model and sorting the importance degrees of the components; when a disaster occurs, a fault condition is obtained, recovering elements with high importance preferentially according to a determined sequence, and improving the robustness of the power distribution network; forming a plurality of micro-grids through pre-deployment of mobile emergency generator cars before disasters and real-time scheduling after disasters, building a target function by taking minimization of power failure time of important loads in different scenes as a target, forming an MILP problem through the target function and constraint conditions, obtaining the real-time distribution condition of the mobile emergency generator cars after disasters by solving the corresponding problem, and completing power distribution network recovery and promotion. According to the invention, the robustness of the power distribution network is improved; the power distribution network fault recovery time is shortened, and the power distribution network recovery rapidness is realized.

The invention discloses a reliability evaluation method, system and device for a direct-current power transmission system, and the method comprises the following steps: carrying out the subsystem division of a back-to-back asynchronous networking hybrid direct-current power transmission system, and obtaining a plurality of subsystems; carrying out reliability evaluation on each subsystem by adopting a non-sequential Monte Carlo simulation method; and according to the reliability evaluation result of each subsystem, obtaining the reliability of the back-to-back asynchronous networking hybrid direct-current power transmission system based on the non-sequential Monte Carlo method. According to the invention, reliability parameters of elements of the back-to-back asynchronous networking hybriddirect-current power transmission system are obtained, the reliability index of the system can be calculated simply and accurately by dividing the subsystems of the back-to-back asynchronous networking hybrid direct-current power transmission system, performing reliability evaluation on the subsystems based on the Monte Carlo simulation method and then performing state sampling on the subsystems,and the calculation efficiency is improved.

The invention discloses a multi-disaster power distribution network elasticity evaluation method considering fault linkage. The method comprises the following steps: S1, modeling a plurality of disaster characteristic fault rates; S2, on the basis of sequential Monte Carlo simulation, reserving time sequence characteristics of elements in the disaster process, and establishing an element operation state model composed of a basic range fault rate and a characteristic fault rate; s3, analyzing the nonlinear correlation degree of the equal trend state representation quantity sequences of the lines and the nodes under the N-1 and N-2 scene sets through a grey theory, and establishing a coupling relationship between fault scenes; s4, establishing an LLD index, an SEDT index and an economic index which comprehensively consider the load loss degree and the maximum frequency change rate at the initial moment of active unbalance, forming a weighted elasticity-economic space evaluation system, and performing elasticity evaluation by measuring the composite entropy weight Euclidean distance between a scene set point cluster center and a perfect elastic point. Fault linkage in the disaster process can be prevented and inhibited, and the elasticity of a power transmission network in extreme weather is improved.

The invention provides a high-medium-low-voltage integrated power distribution network reliability hybrid calculation method. A distribution network integrated model is established by considering themutual influence of a high-voltage distribution network, a medium-voltage distribution network and a low-voltage distribution network, and the method comprises the following steps of: firstly, evaluating the reliability of the high-voltage distribution network based on quasi-sequential Monte Carlo simulation of a state transition sampling method to obtain annual average fault times and annual average power failure time of the high-voltage distribution network; secondly, acquiring a transformer substation outgoing line outage rate and a transformer substation outgoing line repair rate for connecting the high-voltage power distribution network and the medium-voltage power distribution network; and finally, taking the outgoing line outage rate and the repair rate of the transformer substationas the input of reliability calculation of the medium-low voltage distribution network, and calculating the reliability index of the medium-low voltage distribution network by using a minimum path method. The method comprehensively considers the mutual influence between the power distribution networks of high, medium and low voltage levels, improves the accuracy of the evaluation result, relatesto the topology of the low-voltage power distribution network for the evaluation of the power distribution network, and improves the calculation precision of the power supply reliability of a low-voltage user.

The invention discloses a reliability evaluation method for a power distribution network containing a distributed power supply, and belongs to the technical field of energy optimization. The method comprises the following steps: step 1, constructing a wind power generation probability model and a photovoltaic power generation probability model, and constructing a wind-solar hybrid power supply system joint output probability model by adopting a Copula function theory; 2, calculating a power parameter and a probability parameter under a given parameter condition according to the wind-solar complementary power supply system joint output probability model; 3, calculating a reliability index of each load point of the power distribution network in different distributed power supply access typesand / or positions by adopting an improved sequential Monte Carlo simulation method; and 4, analyzing the reliability index to determine the influence of the access type and / or position of the distributed power supply on the reliability of the power distribution network. According to the method, the reliability of the power distribution network containing the distributed power supply can be betterevaluated by introducing the wind-solar hybrid power supply system joint output probability model and combining with the improved sequential Monte Carlo simulation.

The invention discloses a method for solving external characteristics of microgrid based on operating strategy under a multi-microgrid grid-connected scenario. Including: According to the different load characteristics, capacity scale and application situation of micro-grid, the load characteristics and power distribution model of typical micro-grid is established; Based on the constraint conditions of each power supply, the power output optimization model considering the operation strategy of micro-grid is established with the objective function of maximizing the daily operating income. A single-cross-section microgrid operation strategy model is proposed, and the external characteristics are solved based on the single-cross-section microgrid operation strategy. Based on the sequential Monte Carlo simulation method, the calculation method of micro-grid operational reliability is proposed under the micro-grid operation strategy. The method proposed by the invention can effectively improve the convergence speed of reliability calculation, and reduce the complexity of distribution network planning, reactive power optimization and other aspects in the scenario of multi-microgrid access to distribution network.

The invention relates to the field of electrical power system asset management, in particular to an interconnection system reliability assessment method considering a whole life cycle of equipment. The method comprises the steps that (S1) mathematic models are established, wherein a fault rate in each operating period can be modeled considering fault mode characteristics, repair and other factors of the equipment in different operating periods; and (S2) system simulation is performed, wherein during sequential Monte Carlo simulation of system reliability, when the characteristics of the fault rates in the whole life cycle of the equipment are considered, all the operating periods of the equipment need to be determined according to a difference value between a starting moment of a to-be-assessed time period and an equipment commissioning moment, and therefore a fault rate model in the whole life cycle is decided. Through the method, influences of changes of the fault rates in the whole life cycle of the equipment on system reliability assessment can be judged quantitatively.

The invention discloses an active power distribution network information physical system reliability calculation method, which comprises the following steps: sampling by adopting sequential and non-sequential Monte Carlo simulation methods based on information link validity; performing equivalence by using a power distribution network upward equivalence algorithm; and calculating the reliability of the information physical system of the active power distribution network through an analytical algorithm. By analyzing the interactive influence of information and a physical system, an information system reliability model which is based on the hybrid communication network and considers routing transfer and complex fault factors is established, the contribution of distributed energy in fault recovery is considered, the influence of information element failure on the reliability of the active power distribution network is analyzed, the reliability evaluation method of the information physical system of the active power distribution network is provided, and effective technical support is provided for planning and operation of the active power distribution network.

The invention relates to a rapid risk assessment method for a large power grid, and the method comprises the steps: carrying out the important sampling of a row discrete element state variable and a correlation continuous variable of the large power grid through employing an improved cross entropy algorithm, obtaining a system state sample, and obtaining a risk level parameter of the large power grid through non-sequential Monte Carlo simulation based on the system state sample; improving an important sampling method of discrete element state variables in a cross entropy algorithm and a traditional cross entropy algorithm, wherein an important sampling method of correlation continuous variables comprises the steps: a Gaussian mixture model is adopted to carry out density evaluation on joint probability distribution of the correlation continuous variables; taking the Gaussian mixture model as an important sampling function of the correlation continuous variable, iteratively updating parameters of the Gaussian mixture model, and obtaining an approximately optimal important sampling function of the correlation continuous variable; and performing important sampling on the correlation continuous variable to obtain a sample of the correlation continuous variable. The method has the advantages of being convenient, flexible, high in efficiency and precision, wide in application range and the like.

The invention provides a power system rapid operation risk assessment method based on power flow transfer and tracking. The method comprises the following steps: initializing parameters; extracting a system operation state based on non-sequential Monte Carlo simulation; analyzing a system state by adopting an improved load flow calculation method and a load reduction model based on load flow tracking; and calculating an operation risk assessment index. The fast load flow calculation is improved by deducing a node transfer distribution factor and a branch breaking distribution factor suitable for multi-branch breaking; a load reduction model based on power flow tracking is established, a most effective control node set is screened out by adopting a power flow tracking theory, optimization in a whole system range is converted into optimization in a local range, and an improved rapid power flow calculation method and the load reduction model are applied to power system operation risk assessment, so the assessment precision is higher; meanwhile, the evaluation efficiency is greatly improved.

The invention relates to a power distribution network planning method and device considering differentiated reliability requirements. The method comprises the following steps: presetting a budget minF of a distribution network wiring planning scheme; obtaining candidate main line wiring by using an ant colony algorithm, using a branch line combination solving method to obtain branch line wiring connecting the load point and the candidate trunk line wiring, and forming a power distribution network wiring planning scheme in a constraint condition range according to the overall wiring formed by the candidate main line wiring and the branch wiring; calculating the comprehensive cost F of the power distribution network wiring planning scheme by using a power distribution network frame planning cost model; simulating a power supply fault by using a sequential Monte Carlo simulation method to calculate the reliability of the power distribution network wiring planning scheme, judging whether the reliability meets a differentiated reliability constraint and an overall reliability constraint, and if not, performing elimination; comparing whether the comprehensive cost F is less than the minF, if so, determining that the minF is equal to the F, otherwise, abandoning; and judging whether the minF converges or not, and if so, outputting a target distribution network wiring planning scheme.

The invention provides an energy storage-containing power grid interval power supply reliability evaluation method considering supply and demand uncertainty, and the method comprises the steps: determining a reliability model of a generator set and an output model of a wind turbine generator set, and building a reliability interval optimization model with the optimal load shedding amount interval as a target function, the reliability model of the generator set and the output model of the wind turbine generator set are determined based on a sequential Monte Carlo simulation method; converting the reliability interval optimization model into a deterministic probability model by adopting an interval possibility degree method in consideration of an operation strategy that an energy storage system participates in dispatching optimization of the power system, so as to seek a maximum non-shedding load probability; and calculating an interval power supply reliability evaluation index through the deterministic probability model. According to the method, the interval reliability optimization model of the system is established based on the sequential Monte Carlo simulation method, so that the uncertainty of wind power output can be reflected more accurately, and the influence of a scheduling operation strategy on the power supply reliability of the system can be considered.