249 results about "Optimal management" patented technology

The invention described herein is a system, method, and computer program product for optimization of a scene graph. The system includes an optimization base that contains a set of specific atomic optimizations. The system also includes an optimization registry that lists each atomic optimization, parameters associated with each optimization, and priority information relating to the necessary order in which optimizations must be performed. The system also includes an optimization manager which creates, configures, and applies an optimization process to an input scene graph. The system further includes an optimization configuration module for accepting user input to the optimization process. The method includes the steps of receiving an input scene graph, creating the optimization process, applying the optimization process to the input scene graph, and post-optimization processing. The optimization process can be performed for any of a number of purposes, such as the enhancement of scene graph traversal time, the enhancement of drawing time, the reduction of memory usage, improved efficiency of data manipulation, and the targeting of a specific rendering platform.

A treatment algorithm for managing hemodynamically unstable patients is provided. Specifically, measurements of arterial pressure and stroke volume can be used to calculate pulse pressure variation, stroke volume variation, mean arterial pressure, elastance and cardiac power, the values of which guide treatment decisions and allow optimal management of critically ill patients. In an additional embodiment, a computer system implementing the treatment algorithm is provided.

The invention relates to the management of large stationary batteries. The invention is a comprehensive process for the management of stationary batteries that are used for backup power and are deployed in widely dispersed locations. The OMS™ (Optimization Management System) solution is comprised of Mega-Tags (preferably serialized bar-coded identification labels), a battery testing and data acquisition device, and web-based software. The OMS™ system employs algorithmic testing to determine whether a particular battery unit needs to be replaced or whether it can be advantageously redeployed. These components work together to provide a platform for managing a large number of perishable, expensive, and geographically dispersed assets.

The invention relates to a plug-in hybrid electric vehicle energy optimization management method realizing real-time working condition adaption. The plug-in hybrid electric vehicle energy optimization management method includes the steps of (1), acquiring real-time working condition information of each section of each path; (2), setting the optimization target of minimizing accumulated equivalent fuel consumption of each section of each path, building the plug-in hybrid electric vehicle energy optimization management strategy based on the dynamic planning by taking the speed limit of each section of each path, the traffic flow velocity and the limit of power battery working current; (3), acquiring corresponding target economical speed of each section of each path and sending the same to a vehicular controller; (4), by the vehicular controller, acquiring demanded torque sequence of each moment within a predicted time scale; (5), taking the minimum accumulated equivalent fuel consumption within the predicted time scale as the target, and tracking the target economic speed in real time. Compared with the prior art, the method has the advantages of combining the global optimum and the real-time optimum of the plug-in hybrid electric vehicle energy consumption according to the real-time working condition information, and the like.

A refrigerator and/or freezer unit and system for storing, monitoring, and maintaining a supply of temperature sensitive pharmaceutical products in compliance with regulatory requirements. The unit contains compartments for each product type in multiple controlled temperature zones with sensors and readers to track product status and content. A user interface device in communication with an application service provider provides the user with a secure access to the content of the unit and product information. The application service provider provides the user with web accessed optimal management of product inventory.

A system and method for optimized management of pharmacy workflow, specifically, workflow associated with fulfillment of prescription orders for medications and health-related products in a pharmacy environment. A computer-controlled system coordinates and controls pharmacy workflow to sequence prescriptions for fulfillment in a most efficient path thereby minimizing a cost function associated with fulfillment of the prescription order. The system coordinates and controls prescription order fulfillment from automated and non-automated storage locations and can be easily adapted to the specific layout and level of automation desired by the operator.

A distributed processing system, program product and method of executing a computer program distributed across a plurality of computers. First, interested participants register and provide a commitment for available excess computer capacity. Participants may enter a number of available hours and machine characteristics. A normalized capacity may be derived from the machine characteristics and a normalized excess capacity may be derived from the number of hours committed for the participant. New registrants may be assigned benchmark tasks to indicate likely performance. Parties may purchase capacity for executing large computer programs and searches. The computer program is partitioned into multiple independent tasks of approximately equal size and the tasks are distributed to participants according to available excess capacity. A determination is made whether each distributed task will execute within a selected range of other distributed tasks and, if not, tasks may be reassigned. The likelihood that a task will complete may be based on the participant's past performance. As each task is completed, the completing participant is checked to determine if the task is on schedule. Any task assigned to computers that are found to be behind schedule may be reassigned to other participants. A check is made to determined whether each task is assigned to at least one participant and several tasks may be assigned to multiple participants. Once all tasks are complete, the best result is selected for each task. Each participant may be compensated for normalized excess capacity and that compensation and charges to requesting parties may be based on total available normalized capacity.

The present invention discloses a model predictive control-based home integrated energy intelligent optimization and management system. According to the technical scheme of the invention, the structural features of a home energy local area network and the operating characteristics of all devices are analyzed, and then an economic operation scheme for the optimal energy management of the system is constructed. The system comprises a data acquisition module, a prediction module, an energy management and optimization module, a real-time scheduling optimization module, and a control and communication terminal module. Based on the model predictive control method, the online rolling optimized solution is conducted according to the energy consumption requirements of a load within different time periods, the real-time price of energy, and the state information of distributed power generation equipment and energy storage equipment. Therefore, the optimum allocation of the energy, and the economic and safe operation of the system are realized. Based on the internet technology, a network service platform is set up. Through a handset app, the functions of on-line monitoring, remote control and the like are realized. In this way, a user can know the energy consumption condition of home energy and the operating states of all intelligent devices at any time, so that the remote monitoring is realized for the user. The system provides a novel economic energy management mode for the user.

The invention relates to a multi-time scale microgrid energy optimizing management system structure and method. The system adopts an MAS (Mobile Agent Server) system framework which comprises a plurality of distributive power agents (Agent), a plurality of distributive power Agents, a plurality of demand response agents (Agent), a plurality of user Agents and a main electric grid dispatching Agents, wherein the Agents are collaborated and coordinated with an MAS system served as a frame based on the real-time capacity of a dynamic contract net protocol and ultra-short-term microgrid energy optimization; in case an important even that the Agents are triggered via an electric grid, the Agents are internally collaborated and collaborated with different Agents based on a set contract net coordination strategy, so as to ensure a microgrid system can run in an optimal mode under the rules of safety and speed. By adopting the structure and method provided by the invention, the gaps of the distributive power generation caused by the intermittency and the discontinuity can be filled, the robustness of the system can be improved, the response time can be reduced, the environmental benefit can be ensured as well as the economy of the electric grid in a full running period.

Methods and system to control the data processing workflows in distributed environment with asynchronous message driven mechanism. A production workflow includes an ordered sequence of tasks to be executed that needs to be distributed on multiple computational nodes. Each task is assigned by a sender application to a receiver application running on a computational node through a message. On receiving the message, the receiver application sends and sends an acknowledgment to the message and schedules the sub tasks associated with the task. The sender application on receiving the acknowledgment removes the message from the queue otherwise the messages are stored in the database. On completion of the sub tasks the receiver application generates a message and the sender application on receipt of the message takes up the next task in the sequence and generates a message to another application. The sender application keeps on generating messages till all the tasks are completed in the sequence. The methods adopted in this invention provides persistence and guaranteed delivery of messages thereby improving the quality of service in transaction processing systems that are managing complex workflows.

The invention discloses an integrated power grid optimization auxiliary decision analysis system comprising an external data server, a system database, a data extraction service module, a data transformation service module, a data management service module, a graphics generation engine module, a graphics editing engine module, a topological analysis engine module, a grid rack data management module, a grid rack analysis evaluation module, a grid rack optimization management module and a business expansion auxiliary decision module. According to the integrated power grid optimization auxiliary decision analysis system, a whole network contact map of power grid racks is generated, the existing grid racks are analyzed by utilizing grid rack device data and real-time operating data, operations are carried out on the whole network contact map to simulate optimization, change and business expansion access of the grid racks, and the simulated grid racks are analyzed for solving the problem that various technical specifications, typical design guidelines and the like are not effectively applied to construction and renovation of a power grid so that the construction and the renovation of the power grid have blindness and the problems of insufficient analysis to the current situation of the power grid by a business expansion access scheme and unreasonable selection of an accesses point.

The invention proposes an optimization scheduling method for a large-scale building CCHP (combined cold heat and power supply) system. Through giving comprehensive consideration to the characteristics of a gas turbine, a gas boiler, an absorbing chiller and an electric refrigerating machine according to the characteristics of a cold load, a heat load and an electric load of a building and combining with the operation characteristics of a gas CCHP system, an optimization scheduling model for the large-scale building CCHP system is built, and an improved particle swarm algorithm is used for solving the optimization scheduling model to obtain an optimization scheduling capacity curve of former days, thereby promoting the optimization management of the large-scale building CCHP system. The method achieves the optimization calculation of the former scheduling of the large-scale building CCHP system, and achieves the optimal utilization of energy.

A method for managing metadata file layout of a parallel file system belongs to the field of file system and is characterized in that the file system organizes the files by an extension block distribution way; after receiving a user request, a metadata server quickly carries out the operations of distribution, division, combination, release, and the like to the extension block in the corresponding file layout, thus achieving the requirements of the file layout on obtaining, submission or adjustment and realizing the optimum management to the file layout. The method adopts a principle of meeting the lowest requirement, responds to the request on the corresponding minimum extension block set, thereby meeting the simultaneous operation of multi-user on the same file to the maximum extent and improving the parallelism of the system; and simultaneously, the method adopts an extension block real-time combination strategy to ensure the maximum continuity of the file layout, optimizes the memory, reduces the seek time of the file layout and improves the performance of the file system.

The invention discloses a microgrid multi-time scale self-adaption energy dispatching method under a source-grid-load interaction mode. The invention starts from the aspect of microgrid multi-time scale optimal management, and provides a self-adaption energy management method comprising basic day conventional dispatching and control day rolling dispatching. According to the method, labor is contributed for an energy storage device and a diesel generator according to a global object function and a global constraint condition, active power consumption of power and controllable and respectable load interactive with a large power grid is optimized, and the magnitude of the contributed labor can be predicted according to wind power and photovoltaic power generation systems, self-adaption adjustment for energy storage SOC penalty factors and control day rolling optimization time duration is realized, the influence of the error of the contributed labor predicted by the wind power and photovoltaic power generation systems on microgrid energy management is reduced, and economic and environmentally-friendly coordinated operation of a microgrid is realized.

Techniques and mechanisms provide a storage optimization manager. Data may be optimized and maintained on various nodes in a cluster. Particular nodes may be overburdened while other nodes remain relatively unused. Techniques are provided to efficiently optimize data onto nodes to enhance operational efficiency. Data access requests for optimized data are monitored and managed to allow for intelligent maintenance of optimized data.

The invention relates to a method for performing power optimized scheduling on controllable loads comprising air conditioning loads. The controllable loads comprise the air conditioner loads with adjustable power as well as transferrable loads; an air conditioner operation optimization target model is established for the air conditioner loads, and a transferrable load optimization target model is established for the transferrable loads; the air conditioner operation optimization target model is optimized with a non-dominated sorting genetic algorithm; the transferrable load optimization target model is optimized with a self-adaptive genetic algorithm. On the premise that power utilization habits and power utilization comfort of a user are considered, electric equipment is classified as electric equipment with controllable loads and electric equipment with fixed loads, the air conditioner loads and the transferrable loads in the controllable loads are modeled, the power utilization modes are optimized with the corresponding intelligent algorithms respectively, and the controllable loads are effectively optimized and managed on the premise that the power utilization comfort of the user is realized.

The invention relates to an operation optimum management control system and a method of a thermal generator set. The control system comprises a data collection module, a data effectiveness checking module, a data storage module, a fault analysis module and a warning and display module, wherein the data effectiveness checking module is connected with the data collection module and is used for carrying out the effectiveness checking on original values of real-time operation work condition information of the thermal generator set in the power generation site collected by the data collection module, thus obtaining the effective value of the real-time operation work condition information, the data storage module is connected with the data effectiveness checking module, and is used for storing the effective value of the real-time operation work condition information of the thermal generator set in the power generation site, the fault analysis module is connected with the data storage module, and the warning and display module is connected with the data storage module and the fault analysis module. The invention has the advantages that the thermal generator set in the power generation site can be effectively monitored and managed in a remote way, the labor cost can be reduced, the times for in-site maintenance can be reduced, or the in-site maintenance can be avoided, the maintenance cost and the fault processing time can be saved, and in addition, the safety and the reliability are high.

A method, apparatus and computer-usable medium for improved load testing of subsystems comprising a larger system by intelligently and stochastically distracting virtual users from healthy subsystems such that they collaboratively converge on a subsystem exhibiting operating health problems. Virtual users are progressively targeted at a degraded subsystem to force it to sustain its respective share of a test workload, thereby exacerbating its behavior to facilitate problem determination and resolution. Virtual users that have failed or terminated in an unhealthy subsystem are replaced by selectively and intelligently redistributing virtual users from healthy systems. As virtual users are redistributed to the degraded subsystem and fail or terminate, additional performance and behavior data is generated as the subsystem degrades to an unusable or non-operational state. By accelerating time-to-failure, test cycle intervals are reduced and the number of identified performance defects are maximized.

The invention discloses a memory management method and device for a multiprocess system. The memory management method and device for the multiprocess system are used for optimizing a memory management mode of the system and improving the memory utilization rate and the success rate of memory distribution. The memory management method for the multiprocess system comprises the steps that integrated planning of memory blocks is carried out by the memory management device by means of a shared memory pool, application and release of the memory blocks in the memory pool by multiple processes are distinguished according to identification information and mutually exclusive semaphore of the processes, the multiple processes can have access to memory blocks with the same specification without mutual interference, therefore, optimized memory management can be achieved, resource consumption caused by repeated application to an operation system due to the fact that the memory is not sufficient is avoided, a large amount of memory fragmentation is prevented from being generated in the operation system, and the memory utilization rate and the success rate of memory distribution of the system are effectively improved.

The invention discloses energy router topology and control for source storage load optimal management. The topology comprises an energy management and control center, an AC/DC converter, a first DC/DCconverter, a second DC/DC converter, a third DC/DC converter, a direct-current bus and four ports; the device is connected into a power distribution network with an alternating current load, the device is directly connected to a direct current output device, an energy storage battery and a direct current load of a distributed power supply such as a photovoltaic module or wind power, and maximum power control is carried out on the distributed power supply such as photovoltaic power generation or wind power, so that the grid-connected inverter link of the distributed power supply is omitted; energy storage charge-discharge control is carried out, and the difference between peak and valley is stabilized; when a power distribution network is out of order, automatic off-grid and grid-connectedswitching is carried out on the device, and power supply is carried out on the alternating current load; the energy management and control center is used for taking charge of the energy management ofeach port and is used for carrying out power control on each port, so that optimal router management of source storage load energy sources is realized. The energy management and control center is used for receiving a dispatching command of a superior power distribution network, and the power of the energy router to the power distribution network is controlled so as to meet the dispatching requirement. The energy router topology has significant practical application values.

The invention discloses an energy optimization and control method of a four-engine double-paddle hybrid power propelling system used for carrying out energy optimization and control on the four-engine double-paddle hybrid power propelling system so as to select and switch 8 station modes. The energy optimization and control method comprises a shipping station recognition process, a load status recognition process and a dynamic energy control process, wherein the shipping station recognition process is to obtain an existing shipping station R by adopting a fuzzy neuroid method, the load status recognition process is to compare an existing load with a light load, a middle load and a heavy load to obtain an existing load status L, and the dynamic energy control process is to preliminarily select control parameters of parts according to the existing shipping station R and the load status L, and optimally distribute system energy and switching to an optimal shipping station by adopting energy management based on a dynamic programming method, so as to realize optimal management and control of energy, and reduce fuel oil consumption and exhaust gas emission furthest when the performance of a dynamical system of the ship is ensured.