55results about How to "Achieve co-optimization" patented technology

The invention relates to a regional energy internet multi-source coordinated optimization operation strategy considering time-of-use power price. The strategy is technically characterized by comprising the following steps that step 1, the initial data parameter of a regional energy internet system is inputted; step 2, cold/heat/electric flexible load response under the time-of-use power price is analyzed, and two classes of response models of cold/heat/electric flexible load are constructed; step 3, a regional energy internet system optimization scheduling model of the minimal economic cost and the operation constraint conditions thereof are constructed; and step 4, the regional energy internet system optimization scheduling model of the minimal economic cost is solved by using a Hessian interior point method. The regional energy internet renewable energy consumption level can be enhanced, and the strategy is also significant for realizing economic and safe operation of the system.

The invention provides an intelligent traffic light safety dynamic regulating and controlling method based on the alliance block chain technology. A vehicle-mounted unit, a roadside unit, a transportagency and an ACP system are included. The vehicle-mounted unit sends real-time road condition information to the roadside unit, the information is recorded in blocks through pre-selected bookkeepingroadside unit nodes, the transport agency decodes and acquires the road condition information from block chains, an intelligent contract is triggered to be automatically executed, and the duration oftraffic lights is dynamically regulated and controlled by the ACP system through the acquired road condition information. After the traffic lights are regulated and controlled, the reputation value ofthe vehicle-mounted unit is evaluated through the transport agency, and the real-time road condition information and other services can be enjoyed by paying the reputation value. The problem of centralization of traffic light control is solved, high human intervention in the traffic light management and coordination processes is reduced, and financial resources and material resources are saved. Coordination optimization of traffic light management and control is achieved, and the safe and credible communication environment is provided for a vehicle-mounted Ad-Hoc network. Meanwhile, the confidentiality, privacy and non-repudiation of the information are guaranteed.

The invention provides an unbalanced control method for grid-connected inverter multi-target collaborative optimization and belongs to a control method for a grid-connected inverter. The unbalanced control method includes the step of analyzing the amplitude and phase of a negative-sequence current and adjusting a scaling factor k to enable the grid-connected inverter to be smoothly switched among multiple targets, the step of establishing the relation between the amplitude and the phase of the current on the basis of suppressing instantaneous active secondary power fluctuation and instantaneous reactive secondary power fluctuation according to an instantaneous power model of a network side and an instantaneous power model of a convertor side to obtain a negative-sequence directive current generated matrix T, and the step of selecting an appropriate scaling factor k with the condition of balancing three-phase alternating currents and suppressing network side instantaneous active power secondary fluctuation and network side instantaneous reactive power secondary fluctuation as a control target so that coordination control of three targets can be achieved under power grid unbalance. According to the method, the principle is simple, the structure is clear, and the expected optimal working condition of the grid-connected inverter can be obtained as long as the parameter k is adjusted.

The invention relates to a turbosupercharging through-flow matching method for an internal combustion engine, which is characterized by comprising the following steps: 1) clearing the characteristics of cyclic operation conditions and performance parameter target values of the internal combustion engine against the target internal combustion engine, thereby determining the required performance parameter target values of a turbine and a gas compressor in a turbosupercharger; 2) selecting geometric parameters of the gas compressor and the turbine according to the performance parameter target values which are determined in the step 1) of the gas compressor and the turbine in the turbosupercharger, combining with parameters of the internal combustion engine, and calculating performance parameter values of the internal combustion engine; and 3) judging whether the performance parameters calculated in the step 2) of the internal combustion engine reach the target values determined in the step 1) or not, and outputting the geometric parameters of the turbine and a supercharger in the turbosupercharger when achieving the target values; otherwise, adjusting the geometric parameters of the turbine and the supercharger and returning to the step 2). The method has short cycle and low cost, and can improve the all condition performances of the internal combustion engine, and be applicable to the field of design and matching of the turbosuperchargers.

The invention provides an electric-thermal coupled multi-energy-flow system optimization dispatching method considering economic efficiency and energy efficiency, and belongs to the technical fields of operation and control of the power grid comprising multiple kinds of energy forms. According to the method, equality and inequality constraints of steady state safety operation of a power grid and aheat supply network in the electric-thermal coupled multi-energy-flow system are set firstly; an economic efficiency target function and an energy efficiency target function of optimization and dispatching of the electric-thermal coupled multi-energy-flow system are established separately; a dispatching scheme taking economic efficiency as the target and a dispatching scheme taking energy efficiency as the target are solved separately; the two schemes are substituted into corresponding target functions to perform interaction calculation, and an electric-thermal coupled multi-energy-flow system optimization dispatching model considering economic efficiency and energy efficiency is established according to the calculation result; and the model is solved, and finally an electric-thermal coupled multi-energy-flow system optimization dispatching scheme is obtained. By taking tight coupling and mutual influence of the electric-thermal system into consideration, the electric-thermal coupledmulti-energy-flow system optimization dispatching considering economic efficiency and energy efficiency is realized.

The invention provides a low-voltage distribution network line loss and reactive compensation collaborative optimization method. The method comprises the following steps: S1, acquiring accurate measurement data by utilizing user voltage and current data provided by an intelligent electric meter on the low-voltage side of a transformer area and considering the influence of grid connection of a distributed power supply; S2, correcting locally by adopting a Newton method, a sensitivity method and a loop method by taking a forward-backward sweep algorithm as a main body, and establishing an accurate three-phase load flow calculation model; S3, performing accurate analysis and calculation on theoretical line loss by utilizing the data and line parameters after load flow calculation; and S4, establishing a reactive power compensation optimization model of the power distribution network by taking the minimum line loss as an optimization purpose and taking the economy of reactive power compensation as a constraint condition, thereby realizing collaborative optimization of the line loss and the reactive power compensation. Intelligent management and economic and reliable operation of a power distribution area are realized. The method is suitable for being used as a line loss and reactive compensation collaborative optimization method based on multi-dimensional data fusion.

The invention provides an ultra-short-term prediction-based smooth new energy power generation control method for an energy storage system. The method comprises the following steps: reading related operation data of new energy and the energy storage system; building a target function on the basis of an ultra-short-term prediction power and a charged state of the energy storage system; optimizing six control variables in a control strategy by an adaptive chaotic particle swarm optimization algorithm according to the target function; obtaining a power command value of the energy storage system on the basis of the optimal solution of the control variables and carrying out power limitation on the power command value of the energy storage system; updating the control variables in a rolling manner according to the characteristic that ultra-short-term prediction forecasts once every 15 minutes; and outputting the power command value of the energy storage system to an energy storage control system to execute control on the energy storage system, and achieving a smoothing function of new energy output. By the ultra-short-term prediction-based smooth new energy power generation control method for the energy storage system, the charged state of the energy storage system is kept in an appropriate level; the continuous charging and discharging capabilities of the energy storage system are improved; and cooperative optimization of the smoothing capability and the performance index of the energy storage system is achieved.

The invention discloses a delay transmission strategy selection and power distribution method based on an MS-BAS algorithm applied to communication node energy collection and information transmissionperformance optimization of a wireless sensor network, and comprises the steps of performing mathematical modeling on the wireless sensor network based on an energy collection cooperative relay; solving a data model of energy collection and data transmission collaborative optimization by using the MS-BAS algorithm based on fusion learning algorithm; and adjusting a power distribution ratio and a signal transmission strategy of each exclusive EH relay node of the multi-region wireless sensor network system according to the obtained optimal individual search strategy value. Compared with the prior art, the relay transmission strategy of the current link can be autonomously selected based on the manually set signal to noise ratio threshold value of the EH relay, the power distribution problemof multiple relays is effectively solved, the channel link quality is improved, and the algorithm is high in accuracy and high in convergence speed.

The invention relates to an active power distribution network double-layer planning method considering source-load interaction response. The method comprises the following steps: S1, establishing an active power distribution network upper-layer planning model considering the source-load interaction response; S2, establishing an active power distribution network lower-layer planning model considering the source-load interaction response; S3, solving the upper-layer model to obtain a planning scheme and transmitting a result to the lower layer; s4, solving the lower-layer model to obtain an operation scheme, and returning a result to the upper layer; and S5, repeatedly iterating to finally obtain an optimal result. According to the active power distribution network double-layer planning method considering the source-load interaction response, the defect of unreasonable configuration of the active power distribution network is overcome; the coordination between the source side and the user side is enhanced, the collaborative optimization of the two sides of the source load is realized, the interactive response process is considered in the planning stage, a distributed power supply double-layer planning model considering the source load interactive response is established and is solved and analyzed, and deep guidance opinions are provided for the planning and construction of the active power distribution network.

The invention discloses a spatial saturation load forecasting method under a new situation. The method comprises the following steps: forecasting plot total load through a plot load density index method; determining electric car ownership of a region to be detected in the future according to GDP, population size, electric vehicle permeability, road length and private car ownership quantity of the region to be detected in the future; carrying out classification on electric vehicles, and determining the proportion of each type of electric vehicles, and the type and number of electric charging facilities; carrying out analysis on load characteristics of each type of electric vehicles to obtain workday electric vehicle load and holiday electric vehicle load, the larger load being electric vehicle total load of the region to be detected; and superposing the electric vehicle total load and the plot total load, and allocating the load to each plot. The method realizes the purpose of collaborative optimization of electric vehicle load forecasting and urban power load forecasting, and has a greater auxiliary decision making significance to actions of urban distribution network construction and charging station planning, layout and expansion and the like.

The invention provides a preparation method for thermoelectric composite material of polyaniline in-situ polymerization clad PEDOT modified nano-carbon, belongs to the field of thermoelectric polymers, and aims at solving the problem of low thermoelectric performance of existing polyaniline thermoelectric polymer material. The preparation method comprises the steps that firstly, an organic solvent and nano-carbon material are added in a PEDOT:PSS solution, and acid is added and stirring is performed so that suspending liquid is obtained; secondly, aniline is added to the PEDOT modified nano-carbon material suspending liquid, and ultrasonic stirring reaction is performed under temperature of 0-30 DEG C so that the PEDOT modified nano-carbon material suspending liquid having aniline is obtained; and thirdly, a proton acid solution having an oxidizing agent is dropped in the suspending liquid, and compression molding is performed after stirring reaction so that the thermoelectric composite material is obtained. Preparation time of the thermoelectric composite material of polyaniline in-situ polymerization clad PEDOT modified nano-carbon is short, the PEDOT:PSS content is low, the percolation threshold of the nano-carbon particles in the base is low and the thermoelectric performance is great.

The invention discloses an optimal scheduling method based on a multi-energy complementary micro-grid and an active power distribution network. The method comprises the following steps: respectively establishing an optimal scheduling target model of the multi-energy complementary micro-grid and an optimal scheduling target model of the active power distribution network; establishing an optimization scheduling constraint condition; establishing a double-layer optimization model by taking the optimization scheduling target model of the multi-energy complementary micro-grid and the optimization scheduling target model of the active power distribution network as optimization targets and the optimization scheduling constraint conditions as constraint conditions; and solving the double-layer optimization model, and carrying out optimization scheduling operation based on a solving result. According to the method, coordinated optimization of the multi-energy complementary micro-grid and the active power distribution network is realized, various energy requirements in the micro-grid can be met, gradient utilization of different energy sources is realized, the operation state of the active power distribution network can be considered, support is provided for safe operation of the power distribution network, and the energy benefit of a user-side comprehensive energy system can be improved.

The invention provides a collaborative optimization method based on a logistics supply chain. The method comprises the steps of setting labels of various logistics resources in a supply logistics chain, creating a label database, and acquiring mapping logistics information of various logistics resources; based on a label-based database, making logistics label analysis on the mapped logistics information; based on a logistics attribute library, acquiring logistics attributes on mapped logistics information, adopting a target optimization algorithm to perform dynamic tracking monitoring on eachkind of moving logistics resources, and finally, subjecting a logistics label analysis result, a logistics attribute result and a dynamic tracking monitoring result to cooperative processing to realize cooperative optimization of the logistics chain. A three-in-one optimization mode of logistics labels, logistics attributes and dynamic tracking is utilized to achieve collaborative optimization oflogistics supply chains, matching performance among storage, distribution and transfer is achieved based on a target optimization algorithm, and precise monitoring of mobile logistics resources and optimal transportation of the logistics resources are achieved.

The invention belongs to the technical field of mechanical and control system simulation and particularly relates to a mechanical arm control precision collaborative optimization method. The method comprises the steps that firstly, configuration analysis and forward kinematics analysis of a mechanical arm are performed; secondly, inverse kinematics analysis of the mechanical arm is performed; thirdly, the track of the tail end of the mechanical arm is planned; fourthly, the space track of joints of the mechanical arm is planned; fifthly, topological optimization of a mechanical arm rod is performed; sixthly, control parameter collaborative optimization is performed; and seventhly, comparison validation is performed. The mechanical arm control precision collaborative optimization method isused for a series connection six-degree-of-freedom light mechanical arm which is independently researched and developed, on the basis that the configuration and kinematics of the mechanical arm of thetype are analyzed, an inverse kinematics analytical algorithm of the mechanical arm of the type is put forward, and all the joints of the mechanical arm are subjected to working track planning by means of the inverse kinematics calculation method.

The invention discloses a multi-scene power transmission network planning method considering load and wind power randomness under network source coordination. According to the planning method, load prediction and wind power output randomness are comprehensively considered, andthe multi-scene power transmission network planning method under the network source coordination drive is put forward. Themethod comprises the steps that S1, a load and wind speed probability density random model considering randomness is established, then historical data is counted, load and wind speed model parametersare obtained according to data change conditions, and then a load curve and a wind power output curve are fitted through a model Carlo; S2, an annual operation scene is obtained through multi-scene random simulation on the basis of the load curve and the wind power output curve, and a plurality of typical operation scenes are obtained through scene clustering; and S3, a planning model taking the optimal safety and economy as a target is established, and the safety and economy under different planning schemes are calculated and compared through a plurality of typical scenes to obtain an optimalwind power grid-connected point and power transmission network planning scheme.

The invention discloses a power load calculation method and an information system considering the correlation of photovoltaic and cold load. The method comprises the following steps: collecting building simulation model variables; Obtaining a set of input variables and an output variable to be selected according to building simulation model variables and target uses; According to the set of inputvariables and output variables to be selected, the set of input variables of the building simulation model is obtained by the principle of maximum correlation and minimum redundancy. The data of inputvariables and output variables are trained by limit learning machine to obtain the final building simulation model. Through the final building simulation model, the theoretical calculation value of building load with high proportion of air-conditioning load is obtained. The calculation method can effectively improve the abnormal monitoring level of building load with high proportion of air-conditioning load, improve the short-term forecasting accuracy of building load, and realize the cooperative optimization of building and urban power network.

The invention discloses a park comprehensive energy optimization method and device based on an ADMM alternating direction multiplier method, and the method comprises the steps: obtaining the declaration information of a participant, and displaying the real-time demands and output information on a public interface; and according to the declaration information, adopting an ADMM alternating directionmultiplier method to carry out pre-optimization processing, decomposing the electric power and energy system into two optimization sub-problems of the electric power system and the natural gas system, and generating optimization parameters and an optimization result by taking the minimum operating cost of the energy system of the whole park as a target, sending the optimization parameters and theoptimization result to each enterprise in the park; performing safety check according to the optimization parameters; and if the emergency situation occurs, sending an emergency announcement according to the emergency situation, and carrying out emergency optimization processing. According to the invention, the problems of non-transparent information, complex model and the like in the centralizedand unified optimization method of the energy system can be solved, and the collaborative optimization of the comprehensive energy system in the park is realized through the interaction of a small amount of information between the power system and the natural gas system.

The invention discloses an environmental economy scheduling method for a coastal region electricity-gas interconnection system, and the environmental economy scheduling method comprises the followingsteps: 1), building an atmospheric pollutant diffusion model considering local sea-land circulation and a thermal inner boundary layer for the characteristics that the meteorological conditions of thecoastal region are complex and changeable and the atmosphere has regional features; 2) in combination with an atmospheric pollution diffusion model, establishing a multi-objective environmental economic dispatching model of the electricity-gas interconnection system by taking economic cost, carbon emission and pollutant concentration contribution values as optimization objectives; 3) adopting anADMM-based multi-objective distributed optimization algorithm to carry out electricity-gas dispersion collaborative optimization solution, and 4) inputting a scheduling scheme obtained by solution into a power grid scheduling system to obtain a power scheduling plan of the regional power grid.

The invention provides an optimization method and device for an oilfield development scheme, which relate to the technical field of petroleum exploration and development. The method comprises the following steps: coding optimization indexes of the oilfield development scheme respectively and combining the codes obtained to obtain individual codes of the oilfield development scheme; calculating thefitness of individual coding according to the fitness function; carrying out cross and mutation according to that target population in turn to generate the N generation population, wherein N is greater than or equal to 2; judging whether the Nth generation population satisfies the constraint condition, and if not, regenerating the Nth generation population; if yes, judging whether the N generation population satisfies the termination condition; if the termination condition is not satisfied, generating the N+1 generation population; if the termination condition is satisfied, selecting and decoding the optimal individual coding to obtain the optimal oilfield development plan. The invention realizes the collaborative optimization of multi-index oilfield development scheme, and can be flexibly expanded to obtain more optimized oilfield development scheme.

The invention discloses a power system information physical double-layer strategy optimization method considering network attack influence, and belongs to the technical field of power generation, power transformation or power distribution. The method comprises the following steps: modeling an electric power information physical system based on an incidence matrix method; forming a mathematical vector by using a known network attack mechanism, and analyzing attack influence based on a power information physical system association model; on the basis of the influence of attacks on the physical side and the information side of a power system, an existing control strategy is judged firstly for the safety and stability control service of the power system, and if the judgment result is feasible,execution is performed; if the method is not feasible, optimizing a load reduction optimization strategy of a physical side according to the attack influence; and optimizing the strategy transmissionpath on the basis of upper-layer optimization, and finally obtaining an information physical coordination optimal control strategy of the network attack scene. According to the invention, an information physical cooperative control strategy under a network attack can be formed, and a better control effect is realized.

Provided is a population global optimization method for regional dynamic subdivision based on local Lipschitz estimation. The population global optimization method is combined with the Lipschitz estimation theory under the framework of a population evolutionary algorithm and comprises the steps of constructing a Lipschitz estimation lower bound bearing surface by extracting neighborhood information of new individuals to achieve dynamic subdivision of a search region; effectively identifying part of an invalid region by means of lower bound estimation information and guiding population update; performing local reinforcement by means of the general declining direction of a linear fit convex envelope, and performing secondary subdivision on the search region according to evolution information; reinitializing part of poor individuals in a population according to lower bound estimation selection information. The population global optimization method for regional dynamic subdivision based on local Lipschitz estimation is low in computing cost, and high in rate of convergence and reliability.

The invention discloses a regional multi-type rail transit transport capacity resource allocation method, which comprises the following steps of: establishing a regional multi-type rail transit transport capacity resource collaborative allocation model considering influence of interactive passenger flow among different rail transit modes; acquiring a time period in which transport capacity resource distribution is not matched according to current transport capacity resource allocation situations of arterial rail transit and urban rail transit, and determining a time period in which a train needs to be called out and a time period in which the train can be called in for the arterial rail transit according to a time distribution situation of urban rail transit transport capacity resources; determining and adjusting the transfer-in and transfer-out time of the train based on the arrival balance of the main line rail transit according to the adjustment requirement of the time period so asto realize the allocation of the transport capacity resources of the main line rail transit; after the main line rail transit transport capacity resources are adjusted, optimizing the time table of the urban rail transit train with the minimum transfer time of the interactive passenger flow as the target, so that adjustment of the urban rail transit transport capacity resources is achieved, and cooperative allocation of the regional multi-type rail transit transport capacity resources is completed.