146 results about "Capacity provisioning" patented technology

An automated system obtains performance data of a computer system having partitioned servers. The performance data includes a performance rating and a current measured utilization of each server, actual workload (e.g. transaction arrival rate), and actual service levels (e.g. response time or transaction processing rate). From the data, automated system normalizes a utilization value for each server over time and generates a weighted average for each and expected service levels for various times and workloads. Automated system receives a service level objective (SLO) for each server and future time and automatically determines a policy based on the weighted average normalized utilization values, past performance information, and received SLOs. The policy can include rules for provisioning required servers to meet the SLOs, a throughput for each server, and a potential service level for each server. Based on the generated policy, the system automatically provisions operation of the servers across partitions.

The invention discloses a dual-layer optimization method for power distribution network expansion planning and light storage locating and sizing. The method comprises the steps of building an upper-layer optimization model for active power distribution network expansion planning: determining a target function and constraint conditions of the upper-layer model; building a lower-layer optimization model for light storage capacity configuration: determining a target function and constraint conditions of the lower-layer model; and solving the upper-layer model and the lower-layer model: executing an upper-layer model optimization method, a lower-layer model optimization method and a dual-layer optimization method. According to the method, the built dual-layer optimization models taking a distribution network enterprise and users as subjects and taking calculation of optimal economic cost as a target comprehensively analyze economic influence of light storage system access and power distribution network expansion planning on the distribution network enterprise and the users; a planning model taking annual cost expense as a target function can well assess the economy of a power distribution network; and the light storage system can be reasonably configured, so that the power purchase costs of the users are effectively reduced, the on-spot consumption of photovoltaic energy is increased, and the network loss of a power distribution system can be effectively reduced.

Systems, methods and computer products for DVR management and scheduling. In exemplary embodiments, a system is provided that includes DVR management and scheduling services including, but not limited to: DVR capacity indication; recorded and viewed programs indication; cancellation options for recorded and viewed programs; deletion priority for recorded and viewed programs; schedule change conflict resolution; DVR scheduling; remote and local DVR interface management; DVR searching and programming; multi-level DVR content searching, storage and management; search saving and favorite channel management; DVR management alerts and notifications; offsite DVR recovery; and DVR capacity provisioning.

The embodiment of the invention discloses a minimum life cycle net cost-based microgrid system optimal design method, which is used for confirming the optimum capacity configuration of each distributed power source and accumulation energy in the microgrid system in accordance with an operating strategy of a microgrid system and according to the conditions of the renewable energy sources resources, the load demands and the like in the microgrid system to guarantee the net cost to be within the life cycle, i.e. the cost is minimum. The method disclosed by the embodiment of the invention comprises the steps of: building a life cycle net cost-based target function of the microgrid system; confirming the optimal variable quantity of the target function according to the operating strategy of the microgrid system; confirming a constraint condition of the target function according to the operating strategy of the microgrid system; performing the quasi-steady-state emulation on the target function according to the constraint condition, and generating an optimal variable quantity combination to obtain an optimal computation result by means of the intersection and variation operations of a standard genetic algorithm; and confirming system parameters of the microgrid system according to the optimal computation result.

The invention relates to a storing and accessing method of a tree implemented by 2D tables, including: (1) building 2D tables, including: a capacity allocation table, describing the capacity of tables in the system; a tree-structure relation table, describing the relation of the tree structure; several data storage area tables, recording the node attribute values in the tree structure; (2) loading and maintaining the data, including adding, deleting, amending and searching as well as the relative operations; (3) managing the data, including loading, synchronizing, changing and observing. It achieves the effects of flexibly configuring data and of making maximum use of the original mechanisms of the object-oriented database and enhances processing efficiency, flexibility and stability.

An automated system obtains performance data of a computer system having partitioned servers. The performance data includes a performance rating and a current measured utilization of each server, actual workload (e.g. transaction arrival rate), and actual service levels (e.g. response time or transaction processing rate). From the data, automated system normalizes a utilization value for each server over time and generates a weighted average for each and expected service levels for various times and workloads. Automated system receives a service level objective (SLO) for each server and future time and automatically determines a policy based on the weighted average normalized utilization values, past performance information, and received SLOs. The policy can include rules for provisioning required servers to meet the SLOs, a throughput for each server, and a potential service level for each server. Based on the generated policy, the system automatically provisions operation of the servers across partitions.

The invention discloses an energy storage system capacity configuration method considering capacity electricity prices and a load prediction error, and belongs to the technical field of electric power systems. The method is based on a distributed energy management system, a local energy storage system battery includes an optimization scheduling part used for performing optimization scheduling on a day-ahead predicted load and an emergency part used for performing optimization compensation on an uncertain load caused by a load prediction error, and through introduction of a capacity electricity price charging system, an energy storage system economy model and an optimal charging and discharging scheduling strategy, taking minimization of overall average daily cost of single users as an optimization goal to perform energy storage system optimal capacity configuration. The invention proposes an optimization algorithm combining a traversal iteration theory and a double-stage optimization theory, and adopts a mixed integer linear planning model to describe battery capacity optimization solutions of two stages separately. For users, scientificity and accuracy of the energy storage system capacity configuration method are improved, and the method has important scientific meaning and application value to research and popularization of an energy storage system.

The invention provides a micro-grid power supply capacity optimization configuration method. An island micro-grid is taken as a research object, the influences of the charge and discharge depth and frequency of a lead acid battery on life are analyzed, the influence of the energy storage life of the lead acid battery on micro-grid power supply capacity optimization configuration and the influence of wind curtailment punitive cost, reliability constraints and the like on the micro-grid power supply capacity optimization configuration are taken into consideration, an established model is more comprehensive, and a micro-grid power supply capacity optimal configuration scheme obtained through solving the established micro-grid power supply capacity optimal configuration model by use of a genetic algorithm of linearity weight can help to improve utilization rate of power supply capacity configuration of a micro-grid system, reduce power supply configuration waste and decrease investment cost and operation cost of the micro-grid system; and at the same time, the operation process of the micro-grid power supply capacity optimization configuration method is quite simple, the versatility is quite good, and the method can be widely applied to micro-grid power supply configuration planning on different application occasions and has quite good market popularization and application values.

The invention provides a wind power plant energy storage volume configuration method capable of improving the dispatching economy of an electric power system. The method is characterized by comprising the contents of the definition of prediction errors and the error rate, the relationship among the system wind power standby volume, the energy storage system volume and the wind-power power prediction errors, wind power standby volume determination, energy storage volume determination, confidence degree definition and the like. An energy storage system is used for compensating the time period power shortage with greater wind-power power prediction errors for power and energy time transfer features and fast response capability, a target function with the minimum sum of the system standby volume cost and the configured energy storage volume cost is built, matlab programming is utilized for solving the energy storage system volume in the target function, the goal of greatly reducing the wind-power standby volume of the system at less energy storage volume configuration can be realized, and the operation economy of the system can be improved.

The invention discloses an addressing and capacity configuration method used for a UPFC. A UPFC addressing and capacity configuration model with transient stability constraints is established, a difference evolution algorithm serves as a framework, and the installation position and the capacity of the UPFC are optimized; in addition, a centrality correction interior point method is adopted for carrying out optimization and fitness assessment on continuous variables of each difference evolution unit. The difference evolution algorithm is simple in operation, high in searching capability, fewer in adjusting parameters and suitable for mixed optimization, and the interior point method is good in convergence and strong in robustness, so that the provided mixed algorithm can well solve the problems of UPFC addressing and capacity configuration, the method is highly efficient and convenient, and the application prospect is good.

The invention discloses a method for the fault treatment of an access session control server, which comprises the following steps that: a user data server performs fault detection of the access session controller server in a network; when the user data server detects that the access session control server goes wrong, the user data server selects at least one access session control server not goingwrong; and the selected access session control server performs access treatment of the original user bound to the access session control server going wrong. The invention also discloses the user dataserver, the access session control server and a network system. The method, the user data server, the access session control server and the network system can discover the faults of the access session control server in the network in time, and switch services to other access session control servers not going wrong in the network, reduce the service delay, improve the user experience, can fully utilize the access session control server in the network to perform the access treatment on the user, and have high utilization rate of network resources, flexible capacity configuration and good expandability.

A system and method for managing licensed and non-licensed resources in a grid network is provided. A license server receives and processes requests for a license and determines whether a license is available and, if necessary, causes a new configuration to be created on a server for satisfying the request. A new grid node may also be created and configured to be added to the grid for creating additional capacity for grid processing. The configuration may be performed at a time prior to an actual need by the grid, perhaps due to a faulted node, and quickly brought on-line with a simple configuration update. The new grid node may also have a virtual IP address reassigned to quickly redirect processing from the faulted node to the newly configured node. Also, an external resource dispatcher may add new resources such as storage or processing capacity to the grid and may coordinate the new resources with the license server.

The embodiment of the invention discloses a link load balancing method of an SDN network and an SDN controller, and relates to the field of communication. The link load balancing method can makes fulluse of the link resources of the SDN network and can improve the network overall performance. The link load balancing method of the SDN network comprises the steps of, by the SDN controller, calculating data links which can be used by the SDN network based on link information reported by a switch, wherein the link information comprises a link capacity; adding ports which have the same target address and correspond to the data links into a load port group and configuring the weight of a corresponding port in the load port group based on the link capacity of each data link, wherein the weight of the corresponding port is the number of the ports; obtaining a first message of a data flow sent by the switch, and obtaining the head information of the first message; performing Hash operation based on the head information to obtain a load balancing factor; selecting a forwarding port based on the load balancing factor and the weight of each port in the load port group; and generating a forwarding flow table based on the forwarding port and sending the forwarding flow table to the switch.

An apparatus and method for identifying unused storage capacity of a number of network storage devices, and configuring at least a portion of the unused storage capacity as a logical storage device. The invention is preferably embodied in computer readable program code. The unused storage capacity may be identified by monitoring the number of network storage devices and automatically determining the unused storage capacity thereof. Alternatively, user-defined parameters may be used for identifying the unused storage capacity. At least a portion of the identified storage capacity is allocated for common use as at least one logical device. The allocated storage capacity is managed according to a management policy so that the allocated memory is not overwritten, data is not backed up to the same physical device, etc.

The present invention discloses an electric taxi charging station planning method based on demand analysis. The method comprises the steps of: employing a cluster analysis method and a P-median modelto perform analysis of demands of taxis in a region, and determining construction distribution sites of charging stations in the region; and employing a logit model to simulate probability behaviors of the taxis selecting the charging stations, employing a queuing theory model to calculate average queuing waiting time of each charging station, and determining one construction scale of each charging station according to the average queuing waiting time of each charging station. The charging station planning method based on the demands of electric taxis employs the P-median model to perform optimization addressing of the distribution sites of the charging stations and employs an M / G / c model, configured to more accurately reflect charging features of the taxis in the stations, in the queuingtheory to solve the charging station capacity configuration problem so as to determine a charging station optimization planning scheme, and therefore the method provided by the invention is effectiveand practical.

The invention provides a capacity allocation method of a multi-wind power plant energy storage device for dealing with wind power fluctuation. The method includes the steps that firstly, a minimum energy storage power demand optimization model is established with the minimum energy storage power demand of all nodes of an electric system as a target; secondly, according to the minimum energy storage power demand optimization model, a wind power plant energy storage minimum capacity value within the largest wind power fluctuation range is acquired in combination with a robust linear optimization method; thirdly, when the minimum capacity value is zero, the energy storage device does not need to be arranged; when the minimum capacity value is not zero, the energy storage device is arranged at a non-zero node according to the wind power plant energy storage minimum capacity value. According to the device, layout of multiple wind power plants in the electric system and a network topology structure connected into the system are taken into consideration, and the objective fact that the multiple wind power plants are connected into the current electric system can be reflected; with the introduced robust linear optimization method on the basis of distribution information of random variables, power fluctuation of the multiple wind power plants can be taken into consideration at the same time, and a stochastic programming model difficult to solve is converted into a deterministic linear programming model.

The invention discloses a method for configuring capacity of hybrid energy storage in a micro-grid based on mathematical statistic and a wavelet decomposition algorithm. The method comprises the steps of obtaining a theoretical power demand signal of an energy storage unit according to a small hydropower unit, a photovoltaic unit, a wind power generation unit and load of a micro-grid system, adopting the wavelet decomposition algorithm to analyze the frequency spectrum feature of the theoretical power demand signal, preliminarily determining the dividing frequency fN of hybrid energy storage, obtaining the power and capacity of the hybrid energy storage according to the dividing frequency fN, conducting confidence level and economical evaluation on an energy storage configuration result based on the mathematical statistic, determining the dividing frequency fN of the hybrid energy storage if an evaluation result does not meet the requirement and completing the step if the evaluation result meets the requirement. The method has practical significance on saving of one-time investment and improvement of power supply reliability of the micro-grid.

The invention discloses an energy storage capacity allocation method considering schedulability of an electric vehicle charging station, and can give a corresponding energy storage capacity allocation scheme according to a confidence level of the schedulability of the electric vehicle charging station. In order to compromise the schedulability and energy storage investment cost of the electric vehicle charging station, a method for defining and calculating the charging power schedulability of the electric vehicle charging station is proposed, consumed stored energy-electric vehicle charging station combined system dispatching scheme of an energy storage system is proposed on the basis of charging power forecast data of the charging station, and an optimal power and capacity allocation scheme of the energy storage system is acquired. By the method, minimum investment cost and minimum charge-discharge loss cost of the energy storage system are selected as target functions, a constraint condition comprises residual lifetime of the energy storage system and the confidence level of the power schedulability of the charging station, and a model is solved by a genetic algorithm according to model characteristic. The method can be applied to the field of allocation of the energy storage system of the electric vehicle charging station.

The invention discloses a reactive power grid capacity configuration method for a random inertia factor particle swarm optimization algorithm. The reactive power grid capacity configuration method includes steps that I, acquiring system parameters of a WAMS system in real time and setting particle boundary conditions; II, initializing a swarm and determining an adaptive value of the particle; III, dividing iterative stages; IV, updating the speed and position of the particle; V, judging whether the iteration times arrives at the maximum iteration times of a global search stage; VI, judging whether the iteration times arrives at the maximum iteration times of a primary solution stabilization stage; VII, judging whether the iteration times arrives at the upper iteration limit; VIII, iterating till arriving at the maximum times, and outputting an online reactive capacity configuration method. Compared with a standard algorithm and an adaptive mutation algorithm, the reactive power grid capacity configuration method for the random inertia factor particle swarm optimization algorithm enables the optimization precision to be improved and realizes to improve the early global search capability and the late local search precision based on guaranteeing a convergence rate through combining with actual situations of reactive optimization, and the global optimal solution is ultimately obtained.

The invention relates to a power distribution network energy storage system configuration method based on active management and cost-benefit analysis, and the method comprises the following steps: S1, an active management system is established for actively managing a power distribution network, and a cost-benefit analysis system is also established and comprises an energy storage configuration model; S2, a power distribution system module reads time series data of annual load and photovoltaic power generation output, records a real-time SVR / OLTC running state and transmits to the cost-benefit analysis system and an EMS control module; S3, the EMS module compares the present voltage level data with a set voltage index and transmits charge-discharge power information to an energy storage system module to control the present voltage level in a normal range; and S4, the cost-benefit analysis system performs cost-benefit calculation on the energy storage system and optimizes the energy storage capacity configuration. According to the invention, the power distribution network active management system is established to perform the active management of the power distribution network; and the energy storage cost-benefit analysis system can accurately describe the energy storage configuration model.

The present invention pertaining to the computer network communication technology field provides a SDH network planning and designing method of multi-module fibers, concretely relates to the fiber SDH network planning and designing and also relates to resource management and maintenance of the optical SDH network. According to the present invention, the cost of network fiber is made the minimum after the planning and designing under the condition that communication state between nodes, node positions and service requirements are known, and the given modularized fiber type is STM model. The method comprises the steps of service ordering, routing for each service and performing fiber resource configuration from the high service to the low service, and optimizing the fiber module cost to all the links. The present invention realizes that under the condition that the network topology and service requirements are known, whole planning of SDH mesh network with un-given upper limit of link capability is performed, and routing distribution and LSP resources are optimized through the multi-modularized weighting set, resource distribution and multi-modularized fiber cost optimization, under the condition that the network devices and the like are satisfied, finally, the configuration of the network link capability is close to the minimum.

The invention relates to a user side light storage integrated system demand charge capacity configuration software algorithm. The algorithm comprises the following steps that software inputting is performed, and a user annual time-sharing curve is obtained as computing input; 2, according to a user annual time-sharing load curve, the best photovoltaic configuration capacity and the investment cost are calculated according to the photovoltaic capacity optimized configuration under local consumption, and the best capacity configuration and the investment cost of a storage battery are calculated according to the battery type of an arranged energy storage system, the DOD discharging depth, the battery efficiency and other information and the requirement for charging and discharging time of peak shaving; if a user pays the capacity fee according to the needed electric charge, the electricity consumption in daytime is larger than that at night, the maximum demand occurrence time is short and shorter than 1 h, the maximum demand can be lowered through stored energy, and the demand electric charge can be lowered. According to energy storage, the charging valley time at night is 0 a.m. to 8 a.m., and discharging is performed during maximum demand occurrence. According to discharging power, discharging can be performed is performed when the electric supply P is larger than target power P, and discharging is stopped when electric supply P is equal to Ptn*40%. According to the monthly income, Cin=(P set power-Ptn*40%)*40 yuan per month, and electric supply P=P load-P photovoltaic.

The invention discloses an establishment method of a configuration model of a multi-regional comprehensive energy system in combination with a thermal network model. The method comprises following steps: step 10), respectively establishing the Establishment method of configuration model of multi-regional comprehensive energy system in combination with the thermal network model and a CCHP model; step 20), combining the thermal network model and the CCHP model established to establish the configuration model. The method is capable of well utilizing obvious peak valley alternating occurrences existing cooling heating and power loads in all regions in order to achieve supply-demand complementarities of multiple energies and reducing capacity configuration. The problems such as configuration waste and low utilization rate of equipment during independent planning are solved. Overall cost-effectiveness of the system is effectively improved.

The invention discloses a two-stage capacity allocation method of an integrated energy system considering node heat price, which comprises the following steps of establishing a regional heating network operation constraint model; in the first stage, based on the system parameters and load data, establishing the objective function and corresponding constraint conditions of optimal capacity allocation of multiple cogeneration subsystems; establishing the temperature correction equation of regional heating network, and establishing the nodal heat price equation based on the power flow tracing method; in the second stage, based on the electricity price and node heat price, establishing the annual energy purchase cost objective function and corresponding constraint conditions considering the demand side response; establishing the iterative solution process of two-stage planning method for integrated energy system, and iteratively obtaining the optimal allocation capacity. At first, the method of the invention proposes a calculation method of the node heat price, and is used in the demand-side response, so that the influence of the optimization operation of the system and the demand-sideresponse can be fully considered in the planning stage.

The invention discloses a method and device for forecasting the flow and configuring the capacity of a network equipment interface. The method comprises the following steps of: acquiring user behavior data in the Internet; performing user clustering analysis on the acquired user behavior data, and determining access proportions of user types of users accessing Internet services; performing service clustering analysis on the acquired user behavior data, and determining the probability that each user type accesses each service type in the Internet services; determining the use probability of each service type according to the probability that each user type accesses each service type in the Internet services and the access proportions of the user types; and determining a flow forecast value of the network equipment interface according to the use probability of each service type, a corresponding service quality restraint index and the determined service use concentration degree. By the method, the flow of the network equipment interface can be effectively forecast; and long-relevance flow forecasting can be realized in consideration of user behaviors and demands on the service quality.

The invention relates to a comprehensive energy microgrid energy storage capacity allocation method by considering energy storage participation. The technical features thereof comprise the following steps of: the step 1, inputting electric heat load data, a real-time electricity price, an optimized convergence determination threshold and a pollution treatment price of an integrated energy microgrid; the step 2, according to the real-time electricity price input in the step 1, generating an energy storage participation degree; the step 3, establishing a comprehensive energy optimization scheduling model capable of considering the energy storage participation, ensuring the reliability and taking economic and environmental benefits as a target; the step 4, selecting n energy storage capacityvalues to solve the comprehensive energy optimization scheduling model in different energy storage capacities; and the step 5, comparing the index values obtained by different energy storage capacities to select an optimal index value and give a comprehensive energy system energy storage capacity configuration suggestive value. By employing the energy storage participation and considering the influences of the real-time electricity price and the peak and valley electric prices, the capacity of the energy storage system participate in peak shaving is effectively evaluated.

Example implementations described herein facilitate a drive unit to share physical mediums (e.g. solid state drives) among multiple storage controllers or storage nodes in a distributed storage system, while keeping them physically independent in a redundancy group to avoid single point of failure, by providing an interface to notify redundancy group to the drive unit.

Systems, methods and computer products for DVR management and scheduling. In exemplary embodiments, a system is provided that includes DVR management and scheduling services including, but not limited to: DVR capacity indication; recorded and viewed programs indication; cancellation options for recorded and viewed programs; deletion priority for recorded and viewed programs; schedule change conflict resolution; DVR scheduling; remote and local DVR interface management; DVR searching and programming; multi-level DVR content searching, storage and management; search saving and favorite channel management; DVR management alerts and notifications; offsite DVR recovery; and DVR capacity provisioning.

The invention relates to a wind storage capacity configuration method based on a genetic algorithm, and belongs to the technical field of automated analysis of an electricity system. The method includes acquiring network parameters and system parameters of the system, and defining algorithm parameters; coding decision variables; randomly generating a population including M initial individuals, and performing feasibility detection on the randomly generated population including the M initial individuals, wherein each individual comprises codes of the decision variables; substituting all individuals in the feasible population and tide solutions into a fitness function, and calculating fitness of each individual; performing heritable variation calculation on the current feasible population to form a next generation of population; judging whether or not a current genetic algebra is identical to a maximum genetic algebra N, and if yes, finishing calculation and taking the value of the decision variable contained in the individual, with the highest fitness, in the last generation of population as a final calculation result. The wind storage capacity configuration method has the advantages that the problem of difficulty in large-scale concentrated grid connection of wind power is solved, a calculation method is simple and application of the actual system is facilitated.