77 results about "Capacity provisioning" patented technology

The invention relates to the technical field of energy scheduling, in particular to an energy system capacity optimization and mobile resource space-time decoupling cooperative scheduling method, system and device under extreme disaster disturbance and a medium. Load change parameters are coupled to form a disaster-causing response database; renewable energy output fluctuation and user load demand deviation are converted into fuzzy variables, and a capacity configuration optimization model is established in combination with a disaster-causing response database to generate multi-energy complementary capacity configuration; mobile resources are introduced to establish an elastic lifting scheduling model, and an elastic lifting scheme is generated by implementing damaged road network topology reconstruction of the mobile resources, space-time transfer chain modeling and action state coordinated regulation and control. According to the method, collaborative decision-making of capacity optimization of equipment and dynamic scheduling of mobile resources is driven through the disaster-causing response database, and dual elastic gains of fixed resource optimization and after-disaster quick response of the mobile resources under extreme disaster events are achieved.

The invention discloses a virtual power plant capacity configuration and regulation operation optimization method, which comprises the following steps: constructing an aggregation model and physically consistent digital twinning, establishing a linearized power distribution network model containing voltage and power flow constraints, and depicting resource efficiency and time delay characteristics; forming a time-varying uncertainty set through quantile calibration and set drift constraint; establishing a capacity-operation joint double-layer optimization model, realizing capacity configuration under the constraint of the whole life cycle cost, and obtaining a rolling scheduling strategy through distributed robust optimization; before issuing, control shielding and formalized constraint are adopted to ensure the safety of the power grid; a multi-variety collaborative quotation is generated on the market side through opportunity constraint and risk measurement; hierarchical adaptive re-optimization is realized based on a trigger criterion, and a twin model is continuously calibrated by using a hardware-in-the-loop experiment; model updating is realized by adopting federated learning and differential privacy; executing degradation control under an abnormal condition, and performing smooth rollback after recovery; and finally, the capacity and operation parameters are evaluated and corrected through performance and service life linkage.

The invention relates to the technical field of power systems, in particular to a capacity configuration optimization method and system for a multi-energy power system. The method comprises the following steps: acquiring historical load data, meteorological data and renewable energy output data of M regions in power grid operation, and constructing a load and meteorological association model and a meteorological and renewable energy output association model according to the acquired data; generating a future load scene according to results of the load and weather association model and the weather and renewable energy output association model; constructing a risk assessment model to carry out risk exposure assessment on the future load scene to obtain a risk score of the future load scene, and carrying out risk grade division; obtaining an initial redundancy capacity configuration scheme, constructing a multi-objective optimization model, establishing an optimization objective function in combination with the global redundancy capacity and the regional redundancy capacity, and iteratively updating the optimization objective function to obtain an optimal redundancy capacity configuration scheme; and according to the optimal redundancy capacity configuration scheme, dynamically configuring the redundancy capacity according to expert experience.

The invention relates to the technical field of electric storage capacity configuration, in particular to a capacity configuration method and system based on source network load storage integration. The method comprises the following steps: acquiring power utilization data, power generation data and environment temperature, and analyzing and predicting a load demand by using an ARI MA model in combination with a linear regression model; preliminarily calculating and analyzing energy storage capacity configuration based on actual load requirements, and establishing a source network load storage capacity configuration optimization model in which the source network load storage capacity and the energy storage capacity are mutually restrained; introducing an environment temperature change factor, and redesigning an energy storage capacity configuration strategy; and evaluating the stability of the capacity configuration strategy by using a phase space analysis algorithm, and introducing the Lyapunov index into the source network load storage capacity configuration optimization model to determine the capacity configuration strategy. According to the capacity configuration method and system based on source-network load storage integration, an energy storage capacity configuration strategy is adjusted based on dynamic changes of actual load requirements and environmental factors, and energy storage capacity configuration is stably optimized by combining a Lyapunov index analysis system.

The invention relates to a source network load storage capacity planning method and system based on a multi-agent game, and the method comprises the steps: constructing a multi-agent game behavior data set, analyzing the dynamic interaction of a strategy through employing a game theory model, and obtaining the strategy preference and interaction mode of each agent; constructing a source network load storage collaborative planning model, and determining an initial capacity configuration scheme of each main body; extracting a benefit distribution proportion of each main body from the initial capacity configuration scheme, and adjusting capacity configuration by adopting a multi-objective optimization algorithm to obtain an optimized capacity planning scheme; analyzing the influence of peak demand fluctuation and transmission capacity limitation on the scheme by adopting a Monte Carlo simulation method to obtain a dynamic adaptability index of the scheme; and adjusting game theory model parameters to obtain updated strategy preferences and interaction modes, adjusting capacity configuration through iterative calculation, and generating a new capacity planning scheme. Compared with the prior art, the method has the advantages of comprehensively considering multi-main-body strategy dynamic interaction, improving the feasibility of the planning scheme and the like.

The invention discloses an electronic flexible soft switch interface position site selection and capacity configuration method and device, relates to the technical field of power systems, and is used for solving the technical problem of poor overall reliability of a power distribution network caused by the existing electronic flexible soft switch interface position site selection and capacity configuration method. The method comprises the following steps: acquiring wind and light output historical data and power distribution network historical fault data, and constructing a wind and light output fuzzy set by adopting a preset measurement tool according to the wind and light output historical data; adopting a Monte Carlo sampling method to construct a power distribution network fault scene according to the historical fault data of the power distribution network; taking the minimum sum of the annual investment cost of the electronic flexible soft switch and the annual load loss cost of the power distribution network as a target, and constructing upper and lower layer models according to upper and lower layer planning operation constraint conditions; and based on a power distribution network fault scene, solving the upper-layer model and the lower-layer model by adopting a particle swarm algorithm and a column and constraint generation algorithm according to the wind-light output fuzzy set, and generating an electronic flexible soft switch interface location selection and capacity configuration scheme.

Provided are a container scheduling method, an electronic device, and a storage medium. The method includes: classifying task containers corresponding to a service job into at least one customized description resource object according to task types of the task containers; determining an adaptability and a capacity of a cluster node to each of the task containers in the at least one customized description resource object; and configuring a scheduling relationship between the cluster node and the task containers according to the adaptability and the capacity.

The invention discloses a capacity configuration method and system based on participation of energy storage in spot joint market income, and the method comprises the steps: building a capacity planning model framework based on participation of an energy storage power station in electric power spot joint market income based on consideration of uncertainty conditions of wind power output; establishing a bidding model that the energy storage power station participates in the day-ahead energy-frequency modulation combined market under a master-slave game bidding strategy, and calculating the optimal configuration of an economic benefit guide energy storage power station capacity planning model; converting the bidding model into a single-layer equilibrium constraint mathematical programming problem according to a strong duality theory and a KKT condition; and solving the global energy storage power station capacity planning model by adopting a mode of nesting a CPLEX solver in a particle swarm algorithm. The method has the beneficial effects that the economic benefit of the energy storage power station can be maximized through scientific capacity configuration and a market bidding strategy, the market competitiveness of the energy storage power station is effectively improved, and wide application of an energy storage technology in a modern power system is promoted.

The invention relates to a capacity configuration and scheduling strategy optimization method and device and a readable storage medium. The method comprises the following steps: obtaining an uncertainty description set according to a prediction characteristic curve of an uncertainty parameter; wherein the uncertainty description set represents an uncertainty set of source-load double-side photovoltaic output and an uncertainty set of load demand; constructing a two-stage robust optimization model based on the uncertainty description set; converting the two-stage robust optimization model into a main problem and a sub-problem by using a decomposition algorithm; and iteratively solving the main problem and the sub-problems to obtain a target capacity configuration result and an operation scheduling strategy. By adopting the method, a configuration scheme and an operation scheduling scheme with robustness and economic low-carbon property can be formed under the uncertain condition, and the application range of the optimization method is effectively expanded.

The invention relates to a source network load storage capacity dynamic planning method and system based on digital twinning, and the method comprises the steps: obtaining the operation parameter data of all equipment, and obtaining a final equipment operation parameter set; performing mathematical abstraction on each device by adopting a unified modeling mode to obtain a unified device model; equipment heterogeneous characteristic parameters are extracted from the unified equipment model, and the energy storage capacity is adjusted through a dynamic allocation mechanism; performing real-time capacity allocation according to the energy storage capacity allocation scheme and the real-time load change data by adopting an optimal scheduling algorithm to obtain an equipment operation instruction set; obtaining an equipment cooperative operation state, and obtaining a resource utilization efficiency evaluation result based on the equipment cooperative operation state; and readjusting unified equipment model parameters based on a resource utilization efficiency evaluation result to obtain an optimized capacity configuration scheme. Compared with the prior art, unified modeling and dynamic allocation of different types of equipment are realized, and the method has the advantages of improving the collaborative efficiency and the resource utilization rate of the source network load storage system and the like.

The invention is suitable for the technical field of converter configuration, and provides a capacity configuration optimization method and related equipment for a network tracking / constructing hybrid energy storage power station, and the method comprises the steps: constructing a capacity optimization objective function based on a short-circuit ratio; constructing a number constraint condition, an alternating current power flow constraint condition and a system stability constraint condition of the network tracking / constructing hybrid energy storage power station; and taking the capacity optimization objective function as a fitness function of a particle swarm optimization algorithm, and optimizing the capacity ratio of the tracking / networking hybrid energy storage power station by using the particle swarm optimization algorithm to obtain an optimal capacity ratio which has the minimum fitness function and meets a quantity constraint condition, an alternating current power flow constraint condition and a system stability constraint condition. According to the invention, an operable capacity ratio can be provided for the following / networking hybrid energy storage power station, so that the power station can meet engineering requirements.

The invention relates to the technical field of power system energy storage and automatic control, and discloses a capacity optimization method, system and device for a multi-time-scale hybrid energy storage system, and the method comprises the steps: building and solving an initial capacity optimization model based on a multi-time-scale decomposition result of new energy power fluctuation, obtaining an initial capacity configuration parameter and a multi-time scale division parameter; controlling the hybrid energy storage system to participate in power grid frequency modulation based on the initial parameters, and collecting operation performance and equipment state data; generating a performance feedback index according to the data, dynamically correcting an adjustable parameter of the capacity optimization model based on the index, re-solving the model, and processing a division parameter and a capacity configuration parameter as associated variables in the process to obtain an updated parameter; and applying the updated parameters to the system and returning to the frequency modulation operation step to form closed-loop optimization. According to the invention, collaborative dynamic optimization of the energy storage capacity and the labor division strategy is realized, the system economy is improved, the service life of equipment is prolonged, and the operation robustness is improved.

The invention discloses a resource scheduling method and device of a kubernetes cluster, a storage medium and electronic equipment. The method comprises the steps that in response to a resource scheduling request, a first persistent volume declaration and a second persistent volume declaration of a predefined type are created, the first persistent volume declaration and the second persistent volume declaration are associated with a storage pool, the first persistent volume declaration is a native persistent volume declaration of a kubernetes cluster, and the second persistent volume declaration is a non-native persistent volume declaration of the kubernetes cluster. Capacity configuration information is set in the first persistent volume declaration and the second persistent volume declaration respectively, and the second persistent volume declaration supports increase and decrease of the capacity configuration information; associating a pre-created pod node with the first persistent volume declaration; and creating a storage volume based on the first persistent volume declaration, and mounting the storage volume to the pod node. A new Kubertes custom resource type is introduced, a second persistent volume declaration of a predefined type is created, the second persistent volume declaration supports increase adjustment and decrease adjustment of capacity configuration information, and capacity expansion and capacity reduction of the created storage volume are further supported.

This invention relates to the field of power system technology and discloses a capacity configuration optimization method, apparatus, equipment, medium, and program product. By acquiring multiple operating models and multiple installed capacity values, this invention establishes a synthetic ammonia production capacity relationship, enabling a comprehensive understanding of the operating characteristics and possible configurations of each part of the system. This, in turn, allows for the quantification of the relationship between synthetic ammonia production capacity and various system factors. Furthermore, by establishing total investment cost and total operation and maintenance cost relationships, the cost composition of the system in terms of investment and operation and maintenance can be clearly understood. Moreover, by establishing an objective function with the goal of minimizing the sales value of synthetic ammonia and solving it using a genetic algorithm, the capacity configuration of the system can be optimized as a whole. Therefore, the capacity configuration optimization result obtained in this way can achieve optimal economic efficiency for a renewable energy hydrogen production, synthetic ammonia, and hydrogen power generation system while ensuring system safety and reliability.

The invention relates to the technical field of reactive compensation of a power grid, and discloses a load fluctuation-based dynamic capacity setting and site selection method for a network construction type SVG (Static Var Generator). The method comprises the following steps: acquiring real-time load data and historical reactive demand data in a power grid system to form a load fluctuation feature sequence and a reactive compensation demand feature sequence; performing multi-time scale correlation analysis on the two sequences, identifying a dynamic coupling mode between load fluctuation and reactive power demand, and generating a reactive power compensation priority evaluation result; according to the load fluctuation characteristic sequence and the reactive compensation priority evaluation result, establishing a dynamic capacity optimization model of the network construction type SVG, and adaptively adjusting model parameters; carrying out matching analysis on power grid operation data collected in real time and the dynamic capacity optimization model, determining a potential installation position and a capacity configuration range of the network construction type SVG, and generating a preliminary addressing and sizing scheme; based on the preliminary scheme, the technical economy comprehensive evaluation is executed, and the optimal network construction type SVG configuration scheme is selected, so that the dynamic operation requirements of the power grid can be better adapted.

The invention relates to the technical field of electronics, and discloses a capacity configuration method and device of an integrated energy system, equipment, a medium and a product, and the method comprises the steps: obtaining a pre-constructed capacity configuration optimization model which comprises an objective function and a constraint condition, the objective function is constructed by taking the maximum return on investment of the integrated energy system in the operation period as an objective, the return on investment is the ratio of the net income of the integrated energy system in the operation period to the total investment, and the net income is calculated according to the electricity selling income of the integrated energy system and the total cost; the capacity configuration optimization model is solved, and optimal installed capacity configurations corresponding to different power generation units in the integrated energy system are solved; and capacity configuration is performed on the integrated energy system based on the target installed capacities corresponding to different power generation units, so that the utilization rate of the direct current delivery channel is improved, and the economic benefits of the integrated energy system are ensured.

The invention relates to a source network load storage collaborative planning optimization method and system. The method comprises the steps of abstracting physical entities of a source side, a power grid side, a load side and an energy storage side into virtual energy units with energy attributes, dynamic response functions and coupling weight parameters, establishing a cross-layer energy interaction relationship based on an energy flow and information flow mapping rule, and constructing a coupling graph reflecting a source-grid-load-storage multilayer structure. And performing time sequence correlation analysis on the coupling graph to obtain the coupling strength among the virtual energy units, and dividing a local optimization unit and a collaborative optimization unit according to the coupling strength to form a global collaborative planning scheme. And collecting an operation result in a scheme execution process, carrying out online correction on virtual energy unit attributes and coupling weight parameters, iteratively updating a coupling graph and a collaborative planning scheme until a preset stop condition is met, and outputting a source side capacity configuration scheme, a power grid side topology adjustment scheme, a load side adjustable resource configuration scheme and an energy storage capacity planning scheme. And the precision and the adaptability of the source-network load-storage collaborative planning can be improved.

The invention provides a nonvolatile memory capacity configurable method and device and a storage medium, and the method comprises the steps: obtaining a capacity configuration request, and recognizing a capacity configuration type; determining the position of a to-be-configured storage block according to the capacity configuration type; and according to the capacity configuration type and the position of the to-be-configured storage block, executing capacity configuration processing of the storage unit in the to-be-configured storage block. The method has the beneficial effects that the flexible configuration of the memory capacity is realized, and the use efficiency of the memory is improved.

This invention discloses a capacity configuration method for wind power-to-hydrogen systems based on VMD-MOPSO, relating to the technical field of capacity configuration for grid-connected wind power-to-hydrogen systems. The method involves obtaining a coupled mathematical model of the wind power-to-hydrogen system; decomposing the output power of the wind power generation equipment using the Variational Mode Decomposition (VMD) algorithm to determine the net load power of the energy storage system; determining the energy management strategy for the wind power-to-hydrogen system based on the operating characteristics of each device; and optimizing the system with the minimum present value of cost and the highest power supply reliability as the optimization objectives. Under the constraints of the coupled mathematical model and the energy management strategy, and with the requirement of meeting the net load power of the energy storage system, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the number of installations for each device to determine the target capacity configuration scheme. This method improves the system's economic efficiency and grid service capability.

The invention relates to the technical field of wind and light storage load capacity matching, in particular to a wind and light storage load capacity matching optimization system based on source network load storage integration, which comprises a data acquisition module, a data processing module, a source network load storage modeling module, a capacity matching optimization module, a real-time monitoring and scheduling module, a simulation and evaluation module and a user interface and interaction module. In a capacity matching optimization module, a particle swarm optimization algorithm and rolling time domain control optimization are fused, wind and light storage capacity configuration calculation is carried out, a PSO-RHC hierarchical fusion framework and PSO are adopted for global optimization of wind and light storage capacity configuration, and a five-dimensional weight is fused in an objective function; and the RHC executes second-level scheduling by taking the energy storage power as a single variable to obtain an optimal solution matched with the wind and light storage load capacity of the whole system, so that efficient coordination of cross-time scale optimization is realized.

The embodiment of the invention provides a storage space allocation method, an FM management unit and a computing system, and belongs to the field of computing equipment. An FM management unit applied to a CXL storage pool receives a storage space application request from a first node, the storage space application request comprises a configuration capacity, the configuration capacity indicates a capacity corresponding to a storage space which needs to be allocated for the first node from the CXL storage pool by the FM management unit, and the CXL storage pool comprises a plurality of storage devices; determining an allocation proportion based on the configuration capacity and the capacity parameter of each storage device in the plurality of storage devices; and allocating the storage space of the CXL storage pool to the first node according to the allocation proportion. The storage space of the storage pool formed by the multiple storage devices is distributed to the nodes according to the proportion, so that the nodes can use the storage space provided by the multiple storage devices, and the performance is improved.

The invention relates to the technical field of information and network security, and discloses a certificate capacity planning method based on time sequence prediction, which comprises the following steps: S1, multi-dimensional data acquisition and preprocessing: acquiring multi-dimensional data related to certificate capacity planning, and preprocessing the multi-dimensional data; s2, constructing and training a time sequence prediction model: constructing and training a mixed time sequence prediction model, and predicting the certificate demand quantity in a specific period in the future; s3, capacity planning optimization solution: establishing a multi-objective optimization model to obtain an optimal capacity configuration scheme; and S4, intelligent early warning and decision support: executing intelligent early warning based on the optimal capacity configuration scheme and the real-time monitoring data. According to the method, multiple models are fused, and the advantages of the models in the aspects of capture trend, seasonality, volatility and nonlinear relation are fully exerted; the prediction accuracy can be greatly improved; by establishing the multi-objective optimization model, the cost optimal configuration under the condition of satisfying multiple constraints is realized, and the resource utilization rate is effectively improved.

The embodiment of the invention provides a capacity configuration optimization method and device for energy storage equipment, and the method comprises the steps: taking the minimum resource consumption of the energy storage equipment as a target; combining the resource input amount, the power resource consumption amount and the demand resource consumption amount of the energy storage equipment in the target period to construct a corresponding target function; constructing a first linear constraint condition based on the charging and discharging states, the charging and discharging power and the upper and lower limit values of the charging and discharging power of the energy storage equipment in different time periods in the target period; constructing a second linear constraint condition based on the energy storage charge states of the energy storage equipment in different time periods in the target period and the upper and lower limit values of the electric quantity of the energy storage equipment; constructing a third linear constraint condition based on the upper and lower limit values of the power grid electricity purchasing and selling power and the electricity purchasing and selling state; and determining an energy storage capacity configuration result of the energy storage equipment in the target time period according to the target function, the first linear constraint condition, the second linear constraint condition and the third linear constraint condition.

The invention relates to a capacity configuration method and device of a hydrogen production system, computer equipment, a computer readable storage medium and a computer program product, relates to the technical field of energy system optimization, and can improve the operation efficiency of the hydrogen production system. The method comprises the following steps: establishing a system operation model for representing the operation state of the hydrogen production system; obtaining an optimization target of capacity configuration according to operation resources consumed in the operation process of the hydrogen production system; according to the system operation model and the optimization target, determining candidate capacity configuration of each unit; according to the target quantized values of the plurality of candidate capacity configurations relative to the optimization target of the capacity configuration, determining the quality degrees corresponding to the plurality of candidate capacity configurations, and according to the quality degrees, determining the adjustment directions corresponding to the plurality of candidate capacity configurations; and performing configuration iteration adjustment of different adjustment degrees on the plurality of candidate capacity configurations according to each adjustment direction until an iteration ending condition is met, and determining respective target capacity configurations of the units.

The invention relates to the technical field of informatization management, and discloses a continuous education informatization management system based on a cloud platform, a honeycomb unit topology is constructed, each honeycomb unit is adjacent to six units, course identifiers are mapped to G course groups through a Hash algorithm and modulo operation, and each course group is divided into G groups; dividing request moments according to a sliding time window and a time slice width to generate a time slice identifier, and distributing a course selection request to a unique honeycomb unit; and adaptively adjusting the processing capacity of the honeycomb unit based on the historical request mean value, the standard deviation and the preset lower limit, controlling the request processing rhythm through a token bucket mechanism, and transferring the overflow request to an adjacent unit according to a polling mode when the queue exceeds a preset threshold value. And after the flood peak processing is finished, updating the historical request parameters according to the processing data to optimize the subsequent capacity configuration. The problems of space-time traffic imbalance and low resource allocation efficiency of a traditional system are solved, and space-time decentralized processing, dynamic load balancing and high-concurrency stability improvement of course selection requests are achieved.

Systems and methods are provided for determining an optical bypass for an inter-regional wide area network (WAN) for regions of server facilities of a cloud service provider. In particular, the optical bypass connects non-adjacent regional server centers of the WAN by eliminating needs of data conversions at intermediate regional server centers. The determining the optical bypass includes receiving a WAN topology data, capacity and demand information about the WAN. The determining includes an objective function to maximize a number of network resources to free up by determining a revised data flow and bandwidth allocations by introducing the optical bypass in the WAN. The disclosed technology transmits the determined data traffic flow and resource allocation information of the optical bypass, causing a network traffic enforcers to reconfigure the WAN.

According to the micro-grid system planning capacity configuration method and system based on double-layer optimization, a deep Q network reinforcement learning method is adopted, and a capacity configuration scheme of each decision period is determined according to a state space and an action space; forming a capacity configuration scheme of the long-term planning period by the capacity configuration schemes of all decision periods in the long-term planning period; determining a capacity configuration scheme of each short-term planning period in the current decision period according to the target model by adopting a mathematical planning method under the constraint condition of the target model and the constraint of the upper limit of the configuration capacity of each short-term planning period in the current decision period; using the updated decision period reward function to update the economic index of the long-term planning period capacity configuration scheme; and when the updated economic index is smaller than the economic index before updating, feeding back the updated reward function of which the decision cycle is implemented so as to update the capacity configuration scheme of the long-term planning cycle, and solving the problem of planning capacity configuration of the micro-grid system under the uncertainty of multiple time scales.

Mechanisms are provided for controlling docking of an edge capacity with a cloud computing system. A bill of materials (BOM) enabled agent, executing on the edge capacity, sends a BOM data structure specifying components of a configuration of the edge capacity. A lookup operation of components of the BOM data structure is performed in a BOM controls mapping data structure to identify controls or policies applicable to the components of the BOM data structure. The identified controls / policies are transmitted to the BOM enabled agent for execution to determine if there are any violations. Results of the identified controls or policies are received which specify whether there are any violations of the controls / policies. In response to at least one violation being detected, docking of the edge capacity with the cloud computing system is denied. In response to no violations, the edge capacity docks with the cloud computing system.

The application discloses a kind of unit capacity configuration method and device considering supply contribution, terminal equipment and storage medium, belong to electric power system technical field, the method is: based on the rated installed capacity of each unit, the load curve of each period in typical day and the unit on-line state of each unit in each period in typical day, the standby rate of each period in typical day is calculated;Based on the rated installed capacity of each unit, the standby rate of each period in typical day and the output curve of each unit in each period in typical day, the contribution coefficient of each unit is calculated Supply, and combining capacity redundancy coefficient, the rated installed capacity of each unit and the load curve of each period in typical day, under each constraint, with the minimum capacity compensation cost as the goal, an optimization model is constructed and solved, to obtain the installed capacity declaration value of each unit, according to which the capacity configuration of each unit is determined. Through the implementation of the present application, the problem of mismatch between unit capacity configuration and power system demand in the prior art can be solved.

The invention relates to the technical field of power system power distribution network planning and operation, and discloses a flexible power distribution network dynamic capacity configuration method and system considering power supply reliability constraint, equipment and a medium, and the method comprises the steps: collecting the basic data of a power distribution network, and building an equipment fault rate database; constructing a system state space model based on the Markov chain theory, and establishing a reliability evaluation index system; probability distribution is adopted to describe uncertainty factors, and a random scene is generated and reduced through Monte Carlo simulation; establishing a multi-objective optimization model, and solving a Pareto optimal solution set by adopting an improved genetic algorithm; and dynamic capacity configuration is implemented based on a rolling optimization strategy, a trigger adjustment mechanism is established, a configuration scheme is adjusted in real time according to a system operation state, and an optimization configuration strategy is evaluated. According to the method, the capacity dynamic optimization configuration is realized on the premise of ensuring the power supply reliability, and the economy and the operation reliability of the power distribution network planning are remarkably improved.