89 results about "Capacity planning" patented technology

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The invention relates to a source network load storage collaborative planning optimization method and system. The method comprises the steps of abstracting physical entities of a source side, a power grid side, a load side and an energy storage side into virtual energy units with energy attributes, dynamic response functions and coupling weight parameters, establishing a cross-layer energy interaction relationship based on an energy flow and information flow mapping rule, and constructing a coupling graph reflecting a source-grid-load-storage multilayer structure. And performing time sequence correlation analysis on the coupling graph to obtain the coupling strength among the virtual energy units, and dividing a local optimization unit and a collaborative optimization unit according to the coupling strength to form a global collaborative planning scheme. And collecting an operation result in a scheme execution process, carrying out online correction on virtual energy unit attributes and coupling weight parameters, iteratively updating a coupling graph and a collaborative planning scheme until a preset stop condition is met, and outputting a source side capacity configuration scheme, a power grid side topology adjustment scheme, a load side adjustable resource configuration scheme and an energy storage capacity planning scheme. And the precision and the adaptability of the source-network load-storage collaborative planning can be improved.

This invention discloses a hierarchical evaluation method for new energy resources based on clustering algorithms, specifically including the following steps: Step 1, calculating the theoretical monthly power generation hours for each new energy power station; Step 2, analyzing and correcting the data obtained in Step 1, constructing evaluation indicators for each new energy power station; Step 3, analyzing the evaluation indicators for each new energy power station obtained in Step 2 to obtain substation-level new energy evaluation indicators; Step 4, aggregating the substation-level evaluation indicators obtained in Step 3 to obtain and output provincial-level new energy evaluation indicators. This invention can provide theoretical basis and engineering guidance for new energy installed capacity planning, and is conducive to promoting the high-quality development of new energy.

This invention belongs to the field of electrical engineering technology, specifically relating to a comprehensive planning method and system based on mobile hydrogen energy storage vehicles and energy storage power stations. The method first constructs a spatiotemporal interaction model—an electro-hydrogen energy model. Then, based on this model, a two-stage comprehensive capacity planning model is built. In the two-stage comprehensive capacity planning, the planning stage model is constructed with the objective of minimizing the sum of system operating costs and energy storage construction costs, while the operation stage model is constructed with the objective of minimizing system operating costs. Finally, the two-stage comprehensive capacity planning model is solved to obtain the optimal energy storage planning scheme, which includes the number of mobile hydrogen energy storage vehicles, the construction location and capacity of the energy storage power station. This invention, through the spatiotemporal interaction model—an electro-hydrogen energy model, enables more accurate comprehensive planning of mobile hydrogen energy storage vehicles and energy storage power stations, reducing the total energy storage construction cost while ensuring system operational reliability.

A request to perform scalability analysis of a constituent service of an application at a first deployment environment is received. The constituent service is deployed to a plurality of host groups of the deployment environment. A data set which indicates a collection of front end request routers configured to distribute service requests among hosts of a collection of deployment environments including the first deployment environment is obtained. Analysis of the data set is used to identify a resource scaling unit which indicates a set of host groups, including a particular host group of the plurality of host groups, such that individual hosts within the set of host groups have the same estimated workload level as other hosts within the set of host groups. A representation of the resource scaling unit is stored.

A network device determines at least one of throughput variation and latency variation associated with at least one flow transiting a network slice of a mobile network. The network device compares the at least one of the throughput variation and the latency variation with performance requirements of the network slice, and determines, based on the comparing, network slice resources needed for capacity planning of the network slice. The network device adds or removes network slice resources from the network slice based on the determined network slice resources.

The invention relates to the technical field of power system optimization and energy storage investment, in particular to an energy storage joint line capacity planning method and system based on an improved gravitation optimization algorithm, and the method comprises the steps: obtaining the basic operation data of a regional power system; in the first stage, an investment planning model with the aim of minimizing the annual comprehensive cost of the system is established; in the second stage, a regional power grid operation model based on node electricity price clearing is established; constructing a target function based on the two-stage model, setting a low-cost scheme to generate gravitation for a high-cost scheme by taking the total annual cost of the scheme as gravitation mass, and iteratively optimizing a scheme vector through a dynamic update formula of gravitation and displacement to obtain an energy storage capacity configuration and line expansion scheme with the lowest annual comprehensive cost of the system; and performing comparative analysis of economy, peak regulation capability and new energy consumption rate on the optimal energy storage scheme and the line capacity expansion scheme, and calculating the utility value of the energy storage scheme. According to the invention, system economy and flexibility are considered; and the method has higher interpretability and convergence.

The application provides a zero-carbon park energy equipment capacity intelligent planning method based on energy-carbon collaborative optimization, and relates to the technical field of energy optimization, wherein the method comprises the following steps: constructing a multi-energy flow-carbon flow collaborative comprehensive energy physical model; constructing a energy equipment's flatness resource model for each energy equipment of the zero-carbon park; constructing a multi-energy flow-carbon flow collaborative capacity intelligent planning model based on the comprehensive energy physical model and the flatness resource model of each energy equipment; constructing a low-carbon operation strategy and sensitivity evaluation model; taking the minimum total resource quantity as the target, solving the capacity intelligent planning model based on the comprehensive energy physical model, the flatness resource model and the low-carbon operation strategy and sensitivity evaluation model, and obtaining the optimal capacity planning of each energy equipment, so that the capacity intelligent planning of different energy equipment in the zero-carbon park is realized with the minimum total resource quantity as the target.

The invention discloses a multi-tenant resource dynamic arrangement and elastic scaling method and system based on intelligent prediction. The method comprises the steps of multi-dimensional data acquisition and monitoring, tenant behavior analysis and resource portrait construction, intelligent prediction and capacity planning, dynamic routing and resource scheduling and elastic scaling execution and optimization. The system part comprises a data acquisition layer, an analysis and prediction layer, a decision execution layer and a resource storage layer. The data acquisition layer is responsible for full-link data acquisition and provides a data footstone for upper-layer decision making; the analysis and prediction layer constructs tenant portraits based on the collected data and predicts future resource demands; the decision execution layer makes an optimal resource scheduling decision according to the prediction result and the real-time state; and the resource storage layer is used for executing the scheduling instruction and providing a heterogeneous and elastically telescopic resource pool. According to the invention, the intelligent resource arrangement system is formed through mutual association and synergistic effect of the modules, and refined, automatic and intelligent multi-tenant resource management can be realized.

The invention relates to the technical field of information and network security, and discloses a certificate capacity planning method based on time sequence prediction, which comprises the following steps: S1, multi-dimensional data acquisition and preprocessing: acquiring multi-dimensional data related to certificate capacity planning, and preprocessing the multi-dimensional data; s2, constructing and training a time sequence prediction model: constructing and training a mixed time sequence prediction model, and predicting the certificate demand quantity in a specific period in the future; s3, capacity planning optimization solution: establishing a multi-objective optimization model to obtain an optimal capacity configuration scheme; and S4, intelligent early warning and decision support: executing intelligent early warning based on the optimal capacity configuration scheme and the real-time monitoring data. According to the method, multiple models are fused, and the advantages of the models in the aspects of capture trend, seasonality, volatility and nonlinear relation are fully exerted; the prediction accuracy can be greatly improved; by establishing the multi-objective optimization model, the cost optimal configuration under the condition of satisfying multiple constraints is realized, and the resource utilization rate is effectively improved.

The invention relates to the technical field of power distribution networks, and discloses a mountainous area power distribution network new energy installed capacity planning method, system, device and medium, and the method comprises the steps: firstly collecting the network structure, climate and new energy and load historical operation data of a mountainous area power distribution network; performing region division on the nodes based on a principal component analysis method, and extracting time sequence characteristics of new energy output of each region by using an improved spectral clustering algorithm fusing graph structure information; a multi-scene new energy output model covering normal and extreme meteorological conditions is constructed; on the basis, establishing a distribution network operation constraint system comprising power flow, voltage, current and equipment output constraints, and constructing a comprehensive objective function taking full life cycle economy as an objective; and finally, solving a new energy installed capacity configuration scheme which meets the constraint and is optimal in economical efficiency through iterative optimization. According to the method, the planning robustness, the power supply reliability and the new energy consumption capability of the mountain area power distribution network under extreme conditions are effectively improved.

This invention relates to the field of power system technology, specifically providing a method for optimizing the configuration of wind-storage systems based on source-grid-load-storage interaction. The method includes constructing a data acquisition and situational awareness layer to acquire multi-source data from sources (source, grid, load, and storage) in real time and calculate grid regulation demand and load response potential; constructing a three-layer collaborative optimization architecture consisting of a day-ahead planning layer, an intraday rolling layer, and a real-time control layer, respectively performing capacity planning, rolling scheduling, and real-time control; constructing a bottom-up collaborative feedback loop to feed back real-time execution deviations and the actual operating status of energy storage to the upper-level correction model; and iteratively solving to output the optimal configuration scheme and operating strategy. This invention achieves deep coupling and dynamic correction of sources, grid, load, and storage through a three-layer architecture and feedback loop, solving the problems of poor coordination and low energy storage utilization caused by the fragmentation of each link.

The application provides a kind of integrated energy system capacity planning method and system, belong to integrated energy station capacity configuration technical field, including: the reversible solid oxide cell power generation / hydrogen production system model and integrated energy system model are constructed;The mixed integer linear programming model of the integrated energy system model is established, the objective function is system thermal power total cost, constraint condition includes energy balance, mass balance, reversible solid oxide cell full working condition constraint and each component constraint;Input renewable energy output time series data, user demand time series data and component technical and economic parameters;Solve the solution of objective function under constraint condition, output integrated energy system each component optimal capacity configuration and each typical day under different time scene operation optimization result. By considering the dynamic change of reversible solid oxide cell efficiency with its load in capacity planning process, it is favorable to improve the accuracy of capacity optimization and economic analysis of system components.

This invention provides a method and apparatus for collaborative optimization of energy storage capacity in an auxiliary unit frequency regulation system. The method includes: determining an energy balance capability index of the energy storage system to characterize its response capability; determining a two-layer collaborative optimization model for energy storage capacity corresponding to the auxiliary unit frequency regulation system; the two-layer collaborative optimization model includes an outer optimization model constrained by the energy balance capability index of the energy storage system and used to optimize the cost of energy storage configuration strategies, and an inner optimization model used to optimize the frequency regulation performance of the auxiliary unit frequency regulation system; based on the characteristics of the two-layer collaborative optimization model, analysis and processing are performed using a preset model optimization analysis method to determine the optimal energy storage configuration strategy corresponding to the energy storage system. This invention fully considers the impact of uncertainties on energy storage capacity demand, while also taking into account the coupling relationship between energy storage capacity planning and system optimization operation, thus improving the robustness of system configuration.

This application discloses a method and system for stable hydrogen supply planning in a hydrogen production system considering electrolyzer failures, relating to the field of new energy hydrogen production. The method includes acquiring parameter data, historical new energy output data, and historical hydrogen load data of a new energy hydrogen production system containing multiple electrolyzers; constructing multi-state switching models for the electrolyzers, an electrolyzer operation model, an energy storage battery operation model, and a hydrogen storage tank operation model; then constructing a mathematical model for planning the new energy hydrogen production system; and finally, using clustering algorithms and a two-layer iterative solution algorithm to solve the mathematical model for planning the new energy hydrogen production system, determining the optimal capacity planning scheme for each electrolyzer, energy storage battery, and hydrogen storage tank in the new energy hydrogen production system. This application can incorporate the uncertainty of electrolyzer failures into the hydrogen production system planning model, improve the multi-state characterization of the electrolyzers, achieve optimal capacity planning for each device in the new energy hydrogen production system, and ensure a stable and reliable supply of green hydrogen.

The present application relates to the technical field of micro-grid energy storage configuration, and discloses a micro-grid energy storage configuration method, device, computer equipment and storage medium, the method comprising: obtaining the full life cycle cost of the energy storage system in the micro-grid; obtaining the energy storage income and the wind and light utilization rate of the energy storage system within a preset time period, and determining a target function based on the energy storage income and the wind and light utilization rate; establishing an energy storage capacity planning model based on the full life cycle cost; solving the energy storage capacity planning model based on the target function and a preset constraint condition set, to obtain a target micro-grid energy storage configuration result. The present application considers the full life cycle cost of the energy storage system, takes the energy storage income and the wind and light utilization rate as the target function, optimizes the energy utilization rate of the energy storage system within the preset time period to obtain the target micro-grid energy storage configuration result, and guarantees the energy storage economy. Furthermore, under the configuration of the target micro-grid energy storage configuration result, the energy storage utilization rate of the micro-grid can be improved.