7results about How to "Solve planning problems" patented technology

The invention relates to the technical field of low-altitude flight management, in particular to a low-altitude flight management method and system, and the method comprises the steps: obtaining to-be-transported logistics information, obtaining logistics transportation point information from the to-be-transported logistics information, and triggering a low-altitude logistics request according to the logistics transportation point information; obtaining a to-be-received goods time range from the low-altitude logistics request, and obtaining a transportation flight permission area according to the to-be-received goods time range; generating a logistics transportation path according to the logistics transportation point information and the transportation fly-allowed area, and calculating a logistics transportation duration according to the logistics transportation path; calculating logistics starting time according to the to-be-received time range and the logistics transportation duration, and generating low-altitude logistics approval information according to the logistics starting time, the logistics receiving time range and the logistics transportation path. The method has the effect of improving the low-altitude flight management efficiency in the logistics field.

The invention discloses a new energy base power supply game optimization planning method and system, and the method is characterized in that the method comprises the steps: building a new energy base power supply operation model containing field station side energy storage and shared energy storage based on the priority of a flexible resource power storage and discharge calling sequence when the new energy power is residual and insufficient; obtaining power supply investment basic parameters of a new energy base to be planned, and establishing participants, strategy space and a revenue function of the new energy base game model; formulating game rules and game equilibrium conditions based on the new energy base game model; solving by adopting a discrete integer genetic algorithm, carrying out game iteration and recording to obtain a Nash equilibrium point of decision capacity of each participant; a strategy space and a revenue function in the game model consider a decision-making mode of configuring station-side exclusive energy storage by a new energy investor; the game planning method provided by the invention can consider the decision-making motivation and benefit demand of each power supply investor, and is used for solving the new energy base power supply planning problem considering the interests of multiple parties.

The present invention discloses a multi-drone-multi-truck collaborative logistics distribution path planning method, which belongs to the field of drone logistics technology. It includes the following steps: Step 1: Establish a mixed integer linear programming model for the multi-drone-multi-truck collaborative logistics distribution path planning problem; Step 2: Perform initial planning of the truck distribution path based on the K-Means algorithm and the genetic algorithm; Step 3: Design a path planning search operator, introduce a variable neighborhood search framework on the basis of the truck distribution route to jointly optimize the distribution paths of drones and trucks, and solve the constructed mixed integer linear programming model. The method provided by the present invention takes into account the different purchase costs of trucks and drones, reasonably optimizes the purchase quantity and use quantity of transportation tools, effectively reduces the total distribution cost, further optimizes the drone-truck distribution plan, and makes up for the shortcomings of the existing joint distribution models and methods.

The invention discloses a cold-chain logistics distribution system based on a refrigerator, and relates to the field of cold-chain logistics, the cold-chain logistics distribution system comprises a data management library, a distribution scheduling module and an optimization processing module, the data management library is used for storing and managing logistics data, the distribution scheduling module is connected with the data management library and is used for receiving and processing distribution tasks from the data management library, and the optimization processing module is connected with the data management library. Scheduling personnel distribution according to the distribution task, and updating the information of the distribution personnel currently executing the distribution task to a data management library; and the optimization processing module is connected with the data management library and the distribution scheduling module, and is used for calculating an optimal distribution scheme through an intelligent optimization algorithm according to the distribution task, the urban map and the vehicle position information, generating navigation information and sending the navigation information to the distribution scheduling module. According to the method, the cold-chain logistics distribution path optimization problem is solved, the time window constraint is considered, the method can be flexibly applied to different types of cold-chain logistics distribution scenes, and continuity and stability of cold-chain logistics distribution are ensured.

This invention provides a method and apparatus for distribution network planning, relating to the field of new energy power generation technology. The method for distribution network planning includes: acquiring current distribution network parameters; determining a two-layer model of the distribution network system based on these parameters; wherein the upper-layer model of the two-layer model is constructed based on new energy investment inputs, green certificate trading costs, and carbon emission trading costs, while the lower-layer model is constructed based on distribution network operation problems; transforming the opportunity constraints of the upper-layer model into deterministic constraints, and constructing KKT conditions based on the lower-layer model; merging the deterministic constraints, KKT conditions, and the original constraints of the lower-layer model into the upper-layer model to generate a solution model; and determining the optimal system planning and operation scheme for the current distribution network based on the solution model, and configuring the distribution network accordingly. This method enables distribution network planning and operation while simultaneously considering new energy unit investment decisions, carbon emission trading, and green electricity certificate trading.

This invention relates to a collaborative configuration method and system for regional integrated energy systems that considers source-load fluctuations and high autonomy, belonging to the field of integrated energy system planning technology. It aims to address the problems of existing technologies failing to effectively handle uncertainties on both the source and load sides, the disconnect between planning and operation phases, and the lack of quantitative consideration of system autonomy capabilities. The technical solution includes constructing a multi-energy coupling architecture, modeling source-load uncertainties and generating multiple typical scenarios, establishing an integrated demand response model for electricity, heat, and cooling, designing a two-level stochastic programming model based on scenario analysis, and employing a hybrid optimization strategy for solution. This invention can significantly improve system robustness and reliability, reduce carbon emissions, enhance energy autonomy, optimize economics, and improve the supply-demand balance of multi-energy loads.

The application discloses to belong to the technical field of power system planning and optimization, and particularly relates to an optimization method for distributed power generation and energy storage joint planning in an active distribution network, comprising: a double-layer robust planning model considering new energy output uncertainty is established, SOT is used to discretize the probability distribution of wind power and photovoltaic into a probability sequence and calculate the expected output, and an uncertainty processing mechanism is embedded to guide DG and energy storage capacity configuration; a DG and energy storage joint optimization model based on a double-layer planning framework is constructed, the upper layer optimizes site selection and capacity determination with the minimum annual total cost as the target, the lower layer optimizes energy storage scheduling with the minimum daily operation cost as the target, and planning and operation are coordinated; an improved BPSO monitoring population fitness variance based on chaos optimization is proposed, and Tent mapping chaos disturbance is dynamically introduced to realize efficient solution and global optimization of the model. On the PG&E 69 bus system, line loss can be reduced, voltage distribution can be improved, and new energy consumption capacity can be significantly improved.