158 results about "Capacity planning" patented technology

The invention relates to the field of low-altitude communication network planning methods, in particular to a 5G three-dimensional coverage and capacity planning design method for low-altitude economy, which comprises the following steps: performing airspace range limitation and application scene division on a target airspace, establishing a mobile model of a low-altitude terminal, and providing dynamic input for simulation; the method comprises the following steps: establishing a dual-frequency heterogeneous network, and determining base station addresses covering targets at different heights and meeting different signal station spacing; performing three-dimensional coverage and quality simulation on the established dual-frequency heterogeneous network, performing network KPI evaluation on the simulation until the standard is reached, and outputting a network deployment planning scheme; deploying according to a network deployment planning scheme, predicting low-altitude service flow, and adjusting a beam direction and a PRB reservation ratio to realize on-demand allocation of resources; and carrying out actual measurement on the deployed network, collecting an air measurement index, comparing a comparison deviation between the air measurement index and a simulation result, and carrying out fine adjustment on the network according to the comparison deviation. According to the invention, diversified communication requirements are met, and the success rate of terminal access is improved.

A data-driven production capacity prediction method and apparatus for an automated production line, relating to the technical field of data processing. On the basis of various types of historical feature data of a surface-mount production line device, key features affecting production capacity are extracted via mutual information, and a PSO-ELM prediction model is constructed, thereby enabling intelligent prediction of production line capacity, and laying a foundation for refined and intelligent scheduling optimization and production capacity planning. The present invention fully takes into account dynamic disturbance event data to correct the prediction model, thereby effectively improving the accuracy of the prediction model.

The invention discloses a power distribution system planning operation collaborative optimization method integrated with multi-flexibility resources. Comprising the steps of obtaining a reference data set of a power distribution system, and fitting wind power and photovoltaic edge distribution to construct a joint probability model; and fitting the relationship between the energy storage discharge depth and the capacity attenuation, establishing a full life cycle cost model, and outputting equivalent operation cost parameters changing along with the operation strategy. Based on wind-solar combined distribution parameters, operation cost parameters and load electricity price prediction, a multi-temporal-spatial-scale scene set is generated by adopting Latin hypercube sampling, and a typical scene is obtained through clustering and scene reduction. And constructing a two-stage robust capacity planning model in combination with the typical scene and the equivalent operation cost. The model is solved through a main-sub problem decomposition coordination strategy, an installation and capacity configuration scheme is obtained, and integrated collaborative optimization of long-term planning and short-term operation of the power distribution system is achieved. According to the invention, the safety, economy and flexibility of the power distribution system in a high-volatility environment can be effectively improved.

The invention relates to an electro-hydrogen conversion new energy base capacity planning configuration optimization method, belongs to the technical field of new energy, and solves the technical problems of seasonal imbalance, excessive conservative traditional robust optimization, imperfect evaluation system and insufficient multi-energy flow coupling optimization in existing new energy base capacity configuration. Comprising the steps of obtaining historical data in a new energy base scheduling period; generating a typical scene set based on the historical operation data, constructing a confidence interval of the wind and light output uncertainty of the new energy base, and obtaining a confidence robustness gamma value; constructing an electricity-hydrogen collaborative capacity optimization model with the goal of maximizing the comprehensive efficiency of the new energy base power system; converting the electricity-hydrogen collaborative capacity optimization model into a robust optimization model based on the confidence interval and the confidence robustness gamma value of the wind-solar output uncertainty; and solving the robust optimization model by using a CPLEX solver to obtain a new energy base capacity planning configuration scheme. And reliable low-carbon operation of the new energy base is realized.

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.

Techniques are disclosed for managing aspects of a dedicated region cloud at a customer location (a “DRCC”). A DRCC may comprise cloud infrastructure components provided by a cloud provider and hosted by computing devices located at the customer's (a “cloud owner's”) location. Services of the central cloud-computing environment may be similarly executed at the DRCC. The DRCC may include a service configured to collect, store, and / or present data corresponding to the cloud infrastructure components via one or more interfaces (e.g., interfaces provided to the cloud provider and / or the cloud owner). Data collected within the DRCC (e.g., capacity and usage data, etc.) may be provided and accessible to the central cloud at any suitable time. Obtaining such data enables the user to ascertain various operational aspects of the DRCC, while enabling the system and / or user to execute various DRCC-specific operations regarding capacity planning, health and performance, change management, and the like.

The invention relates to the technical field of energy storage system-containing ship power control, in particular to a ship hybrid energy storage system capacity planning method based on multilayer power distribution, which comprises the following steps of: S1, establishing a power generation side operation constraint of an all-electric ship hybrid energy storage system; s2, constructing a ship hybrid energy storage system robust capacity planning model with the goal of minimizing the investment cost of the ship hybrid energy storage system and the operation cost of the ship microgrid; s3, solving the robust capacity planning model of the ship hybrid energy storage system to obtain the optimal capacity of the ship hybrid energy storage system; and S4, taking the optimal capacity as the design capacity of the ship hybrid energy storage system, performing power distribution under the multilayer time scale in combination with the actual propulsion power demand to obtain an optimal power distribution scheme, and realizing power distribution of each component of the ship hybrid energy storage system through the optimal power distribution scheme. According to the invention, the safety and stability of all-electric ship navigation can be ensured.

The invention belongs to the technical field of pumped storage, and discloses a comprehensive evaluation method for the operation capability of a pumped storage unit in different power grid forms and a related device. The method comprises the steps of obtaining operation data of a pumped storage power station to be evaluated and data of a power grid where the pumped storage power station is located; based on the operation data of the pumped storage power station and the data of the power grid where the pumped storage power station is located, constructing a pumped storage power station multi-type regulation capability evaluation system in different power grid forms; and based on the pumped storage power station multi-type regulation capability evaluation system in different power grid forms, carrying out comprehensive quantitative evaluation on the regulation capability of the pumped storage power station, and obtaining a dynamic priority score of each unit in the to-be-evaluated pumped storage power station. According to the invention, comprehensive quantitative evaluation of the regulation capability of the power station is realized, and a scientific decision basis is provided for capacity planning, operation strategy optimization and multi-type energy storage collaborative scheduling of the pumped storage power station.

This invention relates to a capacity planning method for microgrid energy storage devices, comprising the following steps: establishing a multi-state transition operation model for a reversible solid oxide battery, wherein the multi-state operation includes the reversible solid oxide battery being in a power generation state, an electrolysis state, a thermal standby state, and a shutdown state; constructing a two-layer capacity planning model for the energy storage device, wherein the upper layer constructs an objective function with the objective of minimizing the sum of the energy storage device investment cost, the equipment replacement cost, and the microgrid's total life cycle operating cost, and the lower layer constructs an objective function with the objective of minimizing the microgrid's total life cycle operating cost; combining the reversible solid oxide battery multi-state transition operation model, setting constraints on the upper-layer objective function and the lower-layer objective function; solving the upper-layer objective function and the lower-layer objective function under the constraints to obtain a capacity planning scheme for the reversible solid oxide battery, hydrogen storage device, and thermal storage device.

The invention provides a hydrogen-electricity hybrid energy storage capacity optimization method and device applied to an integrated energy system, and belongs to the field of integrated energy configuration optimization. The method provided by the invention comprises the following steps: adopting a self-adaptive time sequence compression algorithm to perform self-adaptive grouping, weighted fusion and iterative updating processing on annual original time sequence data of the integrated energy system, and compressing to obtain representative time sequence data; based on the representative time sequence data, constructing a capacity planning model, and solving to obtain a capacity pre-planning value of the system core equipment; the capacity pre-planning value is substituted into the original time sequence data, the capacity planning model is reused, the hydrogen energy storage capacity is checked and corrected through full-time sequence energy balance simulation, and the final capacity configuration of the system core equipment is obtained; and based on the final capacity configuration, simulating system operation, extracting an electric and thermal power unbalance residual sequence, extracting a residual fluctuation scene and a corresponding probability, respectively constructing independent optimization models of electric energy storage and thermal energy storage, and solving to obtain the optimal capacity of the electric energy storage and the thermal energy storage.

The invention relates to a layered and partitioned distributed power supply and energy storage two-stage planning method considering source storage load, belongs to the technical field of distributed power supply and energy storage capacity planning in a power distribution network, and aims at solving the problem of consumption caused by access of high-proportion renewable energy to the power distribution network and improving the power supply reliability of a power system. The power system operation cost is reduced; the method comprises the following steps: firstly, dividing a voltage regulation area of each distributed power supply on the basis of an electrical distance structural index based on active-reactive voltage sensitivity, secondly, carrying out two-stage planning on the basis of partitioning, constructing a two-stage planning model by taking minimum network loss and optimal economical efficiency as targets, and carrying out solving by adopting a distance-based improved ant lion algorithm; and finally, solving based on an IEEE33 node example, and verifying the effectiveness of the two-stage planning. The method has the advantages that the power complementation characteristic is fully played, the two-stage planning model is constructed, and the power distribution network operates economically, safely and reliably.

The invention discloses a self-pick-up distribution method based on customer self-pick-up behavior dynamic modeling and a space-time replenishment strategy, and the method comprises the steps: obtaining customer self-pick-up behavior data, building a model based on truncation normal distribution, and determining a probability density function and a probability function; establishing a self-pickup cabinet available capacity and replenishment model, calculating the residual capacity at each moment, and determining replenishment time and vehicle waiting time and cost; a self-pickup distribution mathematical model with the minimum operation cost as a target function is constructed, and self-pickup cabinet site selection, capacity planning, replenishment decision making and vehicle path optimization are carried out; and designing a two-stage heuristic algorithm for solving, generating self-pickup cabinet site selection, capacity grade configuration, replenishment opportunity decision and vehicle path planning schemes, and realizing operation cost optimization. Through dynamic modeling and a space-time replenishment strategy, the space-time utilization rate of the self-service cabinet is improved, the operation cost is reduced, and an efficient solution is provided for express terminal distribution.

The application discloses a capacity planning method and device of a wind-solar-hydrogen storage micro-grid system, and relates to the technical field of renewable energy micro-grid planning. The method comprises the following steps: obtaining a target function and parameter constraint conditions of the wind-solar-hydrogen storage micro-grid system; the target function is determined according to total fixed costs and total operating costs of the wind-solar-hydrogen storage micro-grid system; the parameter constraint conditions comprise photovoltaic and wind power installed capacity output constraints, energy storage boundary and energy change rate constraints, maximum hydrogen consumption rate constraints, system feasibility constraints, continuous operation constraints and timing consistency constraints, and robustness constraints; the target function and the parameter constraint conditions are solved to obtain the installed capacity of a photovoltaic power generation system and a wind power generation system, and the storage capacity of an electrochemical energy storage system and the rated power capacity of a hydrogen fuel cell system. The method improves the accuracy of micro-grid system capacity planning and realizes the balance between economy and reliability.

The application discloses a multi-dimensional constraint modeling energy storage capacity optimization configuration method, and particularly relates to the technical field of energy storage capacity planning, and is used for solving the problems of feasible solution space fragmentation and low global optimization efficiency caused by heterogeneous constraint conflicts in the prior art; the method is characterized in that: multi-dimensional constraint data of a continuous technical parameter, operation condition and discrete policy rule of an energy storage system are acquired; the conflict intensity between constraints is quantified and a dynamic weight is distributed; the discrete rule is converted into a continuous penalty function to construct a constraint model; the topology structure of a solution space is analyzed and its dynamic change is monitored to generate a connectivity atlas and an evolution trend atlas; an adaptive search strategy is generated based on the atlas; a global optimal solution set is outputted and a verifiable energy storage capacity configuration scheme is generated; and through dynamic weight distribution and solution space connectivity guidance, the multi-constraint collaborative optimization capability is significantly improved.

The invention relates to a fused salt heat storage coupling gas generator set capacity configuration and day-ahead scheduling optimization method, belongs to the technical field of power system optimization scheduling, and aims to solve the problems of capacity configuration and day-ahead scheduling of a fused salt heat storage coupling gas generator set system in a steel mill. According to the method, a double-layer optimization model is established based on day-ahead scheduling and capacity planning of a fused salt heat storage coupled gas generator set system, the maximum net present value of the whole life cycle of a heat storage system serves as a target function on the upper layer, and optimal capacity configuration is screened through a grid search algorithm; and the lower layer takes the maximum daily operation net income of the coupling system as an objective function, adopts a mixed integer linear programming solver, solves an optimal solution on the premise of meeting all physical constraints, and further obtains an optimal day-ahead operation strategy of the coupling system. Reference is provided for construction investment of related projects, decision basis is provided for actual production scheduling of the system, and economic benefits of steel mills are guaranteed.

The application belongs to the technical field of power distribution network planning, and particularly relates to a full-peer power distribution system equipment capacity planning method, device, equipment and storage medium. Data information of a to-be-planned full-peer power distribution system is acquired; based on the data information, a full-peer power distribution system planning model is constructed with the minimum annual comprehensive cost of the full-peer power distribution system as an objective function and the intelligent soft switch, distributed photovoltaic and energy storage capacity as variables; based on multiple power distribution networks and the full-peer power distribution system planning model, a distributed planning model is constructed; and based on the distributed planning model and a preset constraint condition, the planning of the full-peer power distribution system equipment capacity is determined. The capacity of the intelligent soft switch, distributed photovoltaic and energy storage equipment in the full-peer power distribution system is reasonably planned, the operation efficiency and overall stability of the power distribution system are improved, and the solving efficiency of the planning model is improved.

The invention discloses a capacity planning method, apparatus and device, and a storage medium. The method comprises the steps of obtaining current operation data of a data center and a preset capacity application efficiency evaluation factor; scoring each preset candidate capacity planning strategy by adopting a Bellman optimal equation according to the current operation data and the capacity application efficiency evaluation factor to obtain a scoring result; determining a target capacity planning strategy from the candidate capacity planning strategies according to the scoring result; and carrying out capacity planning in the data center by adopting the target capacity planning strategy according to the received capacity planning demand. Based on a Bellman optimal equation, according to the current operation data of the data center and a preset capacity operation efficiency evaluation factor, the candidate capacity planning strategy is comprehensively scored, and based on a scoring result, an optimal target capacity planning strategy is obtained, so that capacity planning requirements of different users can be met according to different user capacity planning requirements. And the optimal capacity planning can be realized in the data center by calling the target capacity planning strategy.

The application discloses a network type energy storage power station capacity planning and configuration optimization method based on multi-source data, relates to the technical field of configuration optimization, and comprises the following steps: calculating the cavity length and cavity height of a subsurface cavity based on the sound wave response signal of a corridor ground surface structure; calculating the cavity risk coefficient of a target corridor based on the cavity length and cavity height; calculating the updated discharge depth based on the cavity risk coefficient and the planning discharge depth in an electric station design parameter table; generating a shadow band section of the target corridor, marking the energy storage units of the energy storage power station as high-risk units or low-risk units based on the shadow band section; calculating the high-risk power sum of all the high-risk units, and calculating the high-risk capacity sum of all the high-risk units based on the updated discharge depth. The application can improve the reliability of the operation safety of the power station.

The invention relates to the technical field of comprehensive energy system planning and operation, and discloses a wind-solar-hydrogen-ammonia-alcohol integrated collaborative optimization planning method, system and equipment and a medium. The method comprises the following steps: constructing an integrated structure comprising a wind-solar power generation unit, an electrolytic hydrogen production unit, an air separation nitrogen production unit, a synthesis ammonia unit, a methanol synthesis unit, a carbon capture unit and a hydrogen storage unit; an electricity-hydrogen-nitrogen-carbon-ammonia-alcohol multi-energy flow network topological structure is established; constructing a capacity planning layer-operation simulation layer double-layer optimization model by taking the lowest total cost of the whole life cycle of the system as a target, and dynamically introducing carbon emission cost in an operation layer; and solving the model by adopting an improved multi-target genetic algorithm, and outputting the optimal planning capacity and the hour-level operation plan of each unit. According to the method, multi-energy flow collaboration, cross-period optimization and economic-low carbon collaboration of the wind-solar-hydrogen-ammonia-alcohol system under multiple uncertainties are realized, and the flexibility, the economical efficiency and the low carbon property of the system are improved.

The application discloses a capacity configuration method of a combined cooling, heating and power system of photovoltaic / photothermal / AA-CAES, which firstly establishes a model of a combined cooling, heating and power system of a micro integrated energy system containing AA-CAES, and then solves the model by adopting a double-layer planning method. In the double-layer planning method, the upper layer plans the configuration of capacity with the minimum sum of capacity configuration cost and scheduling cost of the lower layer as the target, the lower layer uses the parameters of the upper layer to schedule the lower layer model according to seasons, with the minimum sum of energy supply cost and carbon dioxide treatment cost as the target, and returns the scheduling result to the upper layer to assist the decision of the upper layer capacity. The method considers the capacity of the compressed air energy storage system of the combined cooling, heating and power system, and establishes a model suitable for capacity planning and scheduling. Simulation results prove that the double-layer planning method can obtain appropriate capacity configuration and energy scheduling.

The invention relates to the technical field of energy planning and utilization, in particular to an integrated energy system capacity planning optimization method for a zero-carbon park, and the method comprises the steps: obtaining an output power curve and a consumption power curve, and dividing a plurality of dominant time periods on the output power curve and the consumption power curve respectively; a dominant characteristic coefficient of each dominant time period is calculated according to the performance parameter of each dominant time period, and a first profit and loss fluctuation time period and a second profit and loss fluctuation time period are screened according to analysis results of the output power curve and the consumption power curve under the first division comparison mechanism and the second division comparison mechanism; according to the method and the device, the energy storage end equipment is selected to determine the profit and loss fluctuation feature aggregation time periods, and the optimal calling mode of the energy storage end equipment is determined in each profit and loss fluctuation feature aggregation time period, so that the complex energy supply and demand relationship is captured according to a multi-matching mechanism, and energy storage optimal calling is performed in combination with physical constraints such as equipment capacity and geographical distribution. And the overall performance of the energy system is improved.

The invention provides a multi-stage capacitor and power supply management power failure protection method and related equipment. The method comprises the steps of performing parameter extraction and confidence evaluation on a target load system to construct a system electrical parameter set, performing energy demand analysis on the system electrical parameter set to obtain critical energy demand data, and performing graded capacity planning according to multi-stage standby energy network data and the critical energy demand data to generate a standby power supply configuration strategy, when power failure protection is triggered, soft start switching and voltage spike suppression are carried out according to a system electrical parameter set and a standby power supply configuration strategy to generate a power failure switching control strategy set, and data preservation task planning is carried out on the power failure switching control strategy set according to hardware real-time task hierarchical data to generate a hardware task scheduling strategy. According to the invention, the hierarchical planning of the multi-stage standby energy, the smooth switching of soft start and peak suppression and the security planning of the hardware task hierarchical data realize reliable power-down maintenance and integrity guarantee of the key load and the key data.

The invention discloses a micro-grid system energy storage capacity optimal configuration method, system and device adapting to a multi-element power market, and relates to the technical field of power systems, the method comprises the following steps: acquiring and processing an unbalanced power signal in a micro-grid system, and obtaining a corresponding power instruction according to an energy storage characteristic; and based on the power instruction and the optimal capacity planning configuration, solving a dynamic optimization configuration model, and obtaining a multi-power market day-ahead optimal joint bidding strategy of the micro-grid system. According to the method, the day-ahead optimal joint bidding strategy is obtained based on the power instruction and the optimal capacity planning configuration according to the external multi-power market prediction information participated by the micro-grid system, the internal power balance demand of the micro-grid energy storage system is preferably met, the capacity and power configuration of the micro-grid energy storage system is reasonably configured, and the optimal capacity of the micro-grid energy storage system is optimized. Stable operation of the micro-grid energy storage system is guaranteed, and efficient utilization of energy storage resources of the micro-grid energy storage system is achieved.

The invention provides a power supply and power transmission channel capacity optimization method, system, equipment and medium, and the method comprises the steps: carrying out the iteration solving of a long-term capacity planning model and a short-term operation simulation model in a double-layer model through a double-layer dynamic iteration mechanism based on a new energy and load typical power curve of a set region, and obtaining a new energy and load typical power curve; obtaining a power supply and power transmission channel capacity optimization configuration scheme; the long-term capacity planning model is constructed on the basis of optimization targets of the minimum total power supply cost in a planning period, the highest power supply reliability under the uncertainty of new energy power generation and the maximum new energy consumption amount; the short-term operation simulation model considers changes of power generation cost of a power supply in a power system, new energy power abandoning penalty cost and load shedding penalty cost, considers multiple optimization targets, deeply couples medium and long-term capacity planning with short-term operation simulation, can adapt to new energy fluctuation and multi-time scale coupling requirements, and improves the simulation efficiency. And thus, medium-and-long-term planning requirements are met.

The invention discloses a simulation task load dynamic change-oriented end-cloud integrated cluster dynamic container capacity planning method, and relates to the technical field of computer services. Modeling a micro-service, a container, a user and a server; load sensing and triggering judgment, including calculation of micro-service total load and load variation, calculation of load intensity and triggering condition judgment; mDP differential capacity adjustment: constructing an MDP state space, formulating a container capacity expansion and shrinkage strategy, and calculating an adjustment correction coefficient; key index calculation including a response time model, a system total cost model and a fairness index model; and carrying out multi-objective solution and verification, namely constructing an objective function, setting constraint conditions and solving by adopting fusion MDP. Hierarchical modeling is carried out by adopting micro-services, containers, users and servers, MDP decision differentiation adjustment is triggered through load sensing, multi-target solving is carried out, a four-layer technical architecture of modeling-sensing-decision-solving is formed, and dynamic optimization of cluster capacity can be realized.

The invention discloses a capacity planning method and device for a wind-light-hydrogen storage micro-grid system, and relates to the technical field of renewable energy micro-grid planning. The method comprises the steps of obtaining an objective function and a parameter constraint condition of a wind-light-hydrogen storage micro-grid system; the target function is determined according to the total fixed cost and the total operation cost of the wind-light-hydrogen storage micro-grid system; the parameter constraint conditions comprise photovoltaic and wind energy installed capacity output constraint, energy storage boundary and energy change rate constraint, maximum hydrogen consumption rate constraint, system feasibility constraint, continuous operation constraint, time sequence consistency constraint and robustness constraint; and solving through the objective function and the parameter constraint condition to obtain the installed capacity of the photovoltaic power generation system and the wind power generation system, the storage capacity of the electrochemical energy storage system and the rated power capacity of the hydrogen fuel cell system. According to the method, the accuracy of capacity planning of the micro-grid system is improved, and the balance between economy and reliability is realized.

The invention relates to the field of comprehensive utilization and optimization of ocean energy renewable energy sources, in particular to an offshore energy island site selection and constant volume method, which comprises the following steps of: constructing an index system capable of comprehensively diagnosing complementary characteristics of wind energy, photovoltaic and wave energy resources and quantifying system output stability and resource contribution degree by carrying out systematic analysis on a frequency domain level; and a unified comprehensive optimization index is further formed. The comprehensive optimization index can be directly applied to equipment configuration, energy storage capacity planning and operation strategy making of the energy island, so that a scientific and reliable decision basis is provided for planning design and operation management of the energy island.

The invention discloses an order message processing method and device, computer equipment and a storage medium, and the method comprises the steps: introducing time fluctuation trend analysis, priority dynamic calculation, distributed capacity awareness storage planning and a data fragmentation storage mechanism during order message processing; and refined scheduling and efficient storage management of the high-concurrency order messages are realized. Through deep analysis of order message timestamps and concurrency data, the system can adapt to sudden or progressive load changes in advance. By calculating the instant priority score, the system can dynamically determine the processing sequence of various order messages from a global perspective. Meanwhile, by combining a double-layer capacity planning mechanism of the main storage area and the standby storage area, coherence and stability of storage planning can be kept. According to the invention, the stable performance can be kept in a high-concurrency and high-dynamic fluctuation environment, and the throughput capacity, the resource utilization rate and the scheduling efficiency of the system in a large-scale order processing scene are remarkably improved.

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.