Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Optimal Configuration of Fault Location Measurement Points in DC Distribution Networks Based on Improved Particle Swarm Optimization Algorithm

The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.

Allocation optimization of bicycle-sharing stations at scenic spots

Bicycle-sharing system is considered as a green option to provide a better connection between scenic spots and nearby metro/bus stations. Allocating and optimizing the layout of bicycle-sharing system inside the scenic spot and around its influencing area are focused on. It is found that the terrain, land use, nearby transport network and scenery point distribution have significant impact on the allocation of bicycle-sharing system. While the candidate bicycle-sharing stations installed at the inner scenic points, entrances/exits and metro stations are fixed, the ones installed at bus-stations and other passenger concentration buildings are adjustable. Aiming at minimizing the total cycling distance and overlapping rate, an optimization model is proposed and solved based on the idea of cluster concept and greedy heuristic. A revealed preference/stated preference （RP/SP） combined survey was conducted at Xuanwu Lake in Nanjing, China, to get an insight into the touring trip characteristics and bicycle-sharing tendency. The results reveal that 39.81% visitors accept a cycling distance of 1-3 km and 62.50% respondents think that the bicycle-sharing system should charge an appropriate fee. The sttrvey indicates that there is high possibility to carry out a bicycle-sharing system at Xuanwu Lake. Optimizing the allocation problem cluster by cluster rather than using an exhaustive search method significantly reduces the computing amount from O（2^43） to O（43 2）. The 500 m-radius-coverage rate for the alternative optimized by 500 m-radius-cluster and 800 m-radius-cluster is 89.2% and 68.5%, respectively. The final layout scheme will provide decision makers engineering guidelines and theoretical support.

An Improved Genetic Algorithm for Allocation Optimization of Distribution Centers

This paper introduced an integrated allocation model for distribution centers (DCs). The facility cost, inventory cost, transportation cost and service quality were considered in the model. An improved genetic algorithm (IGA) was proposed to solve the problem. The improvement of IGA is based on the idea of adjusting crossover probability and mutation probability. The IGA is supplied by heuristic rules too. The simulation results show that the IGA is better than the standard GA(SGA) in search efficiency and equality.

A Dynamic Memory Allocation Optimization Mechanism Based on Spark

Spark is a distributed data processing framework based on memory.Memory allocation is a focus question of Spark research.A good memory allocation scheme can effectively improve the efficiency of task execution and memory resource utilization of the Spark.Aiming at the memory allocation problem in the Spark2.x version,this paper optimizes the memory allocation strategy by analyzing the Spark memory model,the existing cache replacement algorithms and the memory allocation methods,which is on the basis of minimizing the storage area and allocating the execution area according to the demand.It mainly including two parts:cache replacement optimization and memory allocation optimization.Firstly,in the storage area,the cache replacement algorithm is optimized according to the characteristics of RDD Partition,which is combined with PCA dimension.In this section,the four features of RDD Partition are selected.When the RDD cache is replaced,only two most important features are selected by PCA dimension reduction method each time,thereby ensuring the generalization of the cache replacement strategy.Secondly,the memory allocation strategy of the execution area is optimized according to the memory requirement of Task and the memory space of storage area.In this paper,a series of experiments in Spark on Yarn mode are carried out to verify the effectiveness of the optimization algorithm and improve the cluster performance.

Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints

We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.

The Application of Convex Optimization to Load Optimal Allocation in a Single Workstation System

The service quality of a workstation depends mainly on its service load, ifnot taking into account all kinds of devices' break-downs. In this article, an optimization modelwith inequality constraints is proposed, which aims to minimize the service load. A noveltransformation of optimization variables is also devised and the constraints are properly combinedso as to make this model into a convex one, whose corresponding Lagrange function and the KKTconditions are established afterwards. The interior-point method for convex optimization ispresented here as an efficient computation tool. Finally, this model is evaluated by a real example,from which conclusions are reached that the interior-point method possesses advantages such asfaster convergeoce and fewer iterations and it is possible to make complicated nonlinearoptimization problems exhibit convexity so as to obtain the optimum.

Aircraft Optimal Separation Allocation Based on Global Optimization Algorithm

A dynamic programming-sequential quadratic programming(DP-SQP)combined algorithm is proposed to address the problem that the traditional continuous control method has high computational complexity and is easy to fall into local optimal solution.To solve the globally optimal control law sequence,we use the dynamic programming algorithm to discretize the separation control decision-making process into a series of sub-stages based on the time characteristics of the separation allocation model,and recursion from the end stage to the initial stage.The sequential quadratic programming algorithm is then used to solve the optimal return function and the optimal control law for each sub-stage.Comparative simulations of the combined algorithm and the traditional algorithm are designed to validate the superiority of the combined algorithm.Aircraft-following and cross-conflict simulation examples are created to demonstrate the combined algorithm’s adaptability to various conflict scenarios.The simulation results demonstrate the separation deploy strategy’s effectiveness,efficiency,and adaptability.

Assessment of Climate for Agricultural Suitability and Optimal Allocation of Agricultural Production in the Guanzhong Region, Shaanxi Province

Based on spatial climatic data of agriculture and the experiment data, the models of agro-ecological assessment of climate for agricultural suitability in this study were developed using the fuzzy mathematical method. Three coefficients, in- cluding the resource coefficient （Cr）, the efficiency coefficient （Ce）, and the utility co- efficient （K）, were used in the models, which were calculated based on temperature, moisture, and sunshine duration data of Guanzhong region, Shaanxi Province. The results indicated that resource coefficient was higher in west of the region than that in east, and higher in south （especially in the Central Shaanxi Plain） than that in the Weibei plateau. The value of Cr changed from 6.5 to 9.2 from north to plain area. Spatial change of efficiency coefficient was obvious, lower in the northeast than in the central plain, and the value of Ce changed from 2.3 to 6.5 from the northeast to the central plain. As for utility coefficient, it was lower in northeastern part of the Weibei plateau and in southern mountain areas than that in the central plain, showing significant latitudinal zonality. Furthermore, the value of K increased from 0.35 to 0.78 from northeast to the central plain, and decreased from 0.78 to 0.53 from the central plain to southern mountain areas. These indicated that climate resource in the central plain region was more abundant and potential, compared with other regions. GuanZhong region was classified into three larger agricultural zones and three small independent zones, according to agro-ecological assessment. Light, heat and water resources should be made use of in an efficient way in spatial allo- cation of agricultural production. For example, water facilities should also be im- proved in Weibei plateau region where highly-qualified fruit should be enhanced and fruit processing industrial chain should be shaped. Large-scale production area of wheat should be increased in central irrigation region and more vegetable bases should be developed around large and medium-scale cities. Thanks for outstanding water conservation function, the three-dimensional agriculture including medicine and other sideline production should be developed in Qinling Mountains and the special- ized commercial agriculture should be accelerated in independent small zones, ac- cording to local conditions. In the research, different crop varieties were developed in corresponding regions as per current eco-climatic conditions.

Optimized Allocation Model for Regional Agricultural Fertilizer Resources in Southern Xinjiang from the Perspective of Sustainable Development

[Objective] This study was to establish an optimized model for the allocation of agricultural fertilizer resources in Southern Xinjiang from the perspective of sustainable development.[Method] An optimized model for the allocation of agricultural fertilizer resources was established based on their allocation structure.Combined with the actual agricultural production in Aksu areas of Southern Xinjiang,by establishing a rational evaluation index system,under the premise of considering the planting area constraints,the total water resources constraints and the security constraints of food production,we established the empirical optimal allocation model of the regional agricultural fertilizer resources in Aksu area of Southern Xinjiang.Moreover,we solved the model by using the search algorithm of computer and lingo programming.[Result] The increased economic benefit was near to 1.8 billion Yuan by adopting the optimal allocation methods,with a relative increment of about 34.4%.[Conclusion] Our results provided theoretical basis for achieving the sustainable development of agricultural economy in Southern Xinjiang.

Non-Convex Optimization of Resource Allocation in Fog Computing Using Successive Approximation

Fog computing can deliver low delay and advanced IT services to end users with substantially reduced energy consumption.Nevertheless,with soaring demands for resource service and the limited capability of fog nodes,how to allocate and manage fog computing resources properly and stably has become the bottleneck.Therefore,the paper investigates the utility optimization-based resource allocation problem between fog nodes and end users in fog computing.The authors first introduce four types of utility functions due to the diverse tasks executed by end users and build the resource allocation model aiming at utility maximization.Then,for only the elastic tasks,the convex optimization method is applied to obtain the optimal results;for the elastic and inelastic tasks,with the assistance of Jensen’s inequality,the primal non-convex model is approximated to a sequence of equivalent convex optimization problems using successive approximation method.Moreover,a two-layer algorithm is proposed that globally converges to an optimal solution of the original problem.Finally,numerical simulation results demonstrate its superior performance and effectiveness.Comparing with other works,the authors emphasize the analysis for non-convex optimization problems and the diversity of tasks in fog computing resource allocation.

Interregional compensation for farmland protection:From the perspective of farmland allocation optimization

Interregional compensation for farmland protection(IRCFP)is a policy instrument for encouraging farmland protection through interregional fiscal transfer payments.Previous practices and studies on IRCFP have generally determined the payers and recipients of compensation based on the present distribution of farmland,and the compensation standards did not combine farmland development right value with farmland deficit and surplus,resulting in insignificant effects on farmland protection and even policy failure.Therefore,in this study,we proposed an interregional compensation mechanism for farmland protection based on farmland allocation optimization by considering 31 provincial-level regions in China.The results showed that(1)the determination of farmland surplus or deficit areas based on farmland allocation optimization met the regional construction land demand from the perspective of achieving food security.(2)The combination of the compensation value standard and cropland deficit and surplus had a positive effect on farmland protection.(3)Interregional compensation for farmland protection based on farmland allocation optimization can coordinate economic development,farmland protection,and ecological conservation.Finally,we discussed the rationality of interregional compensation for farmland protection based on farmland allocation optimization and designed the operation mechanism of IRCFP.

GIS-Based Assessment of Land Suitability for Optimal Allocation in the Qinling Mountains, China

A GIS-based method was used to assess land suitability in the Qinling Mountains, Shaanxi Province of China through simultaneous consideration of physical features and current land use. Through interpretation of Landsat TM images and extensive field visits the area was modeled into 40 land types in five altitudinal zones (valleys and gullies, hillsides and terraces, foothills, mid-mountain, and sub-alpine mountain). Then, a suitability score was assigned to five physical factors (climate, hydrology, topography, soil, and vegetation). Next, their integrated overall suitability value scores were compared with the observed land cover to determine whether it should be reallocated a new use. Results showed that the five suitability classes of agriculture, forest, grassland, farmland-woodland, and scrub-pasture had altitudinal stratification and a total of 1151 km2 (8.89%) of lands on the northern slopes of the Qinling Mountains had to be reallocated. To achieve this reallocation, 657 km2 of arable land should be reduced, and forest, grassland and scrub-pasture increased by 615 km2, 131 km2 and 405 km2, respectively. Implementation of these recommended land reallocations should help achieve suitable use of land resources and prevent land degradation.

Structural patterns of land types and optimal allocation of land use in Qinling Mountains

The case study based on Qinling Mountains in Shaanxi Province of China, in virtue of the information from TM image, classifies the land types and analyzes their spatial and temporal differential law, and puts forward three structural patterns of land types in mountainous areas, namely, spatial, quantitative and qualitative structures of mountainous land types. Furthermore, it has been noticed that the analysis of structural patterns can disclose the heterogeneity and orderliness of combination of land types, which can lay the theoretic foundation for comprehensively recognizing ecological characteristics and succession law of structure and function of land types. After the all-around comparative analysis, an optimal allocation of land use in Qinling Mountains has been put forward according to the principle of sustainable development and landscape ecology, which can lay the scientific foundation in practice for the structural adjustment and distribution optimization from the macro level to micro level.

Game theory approach to optimal capital cost allocation in pollution control

This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.

Power Allocation for Cooperative Communications in Non-Orthogonal Cognitive Radio Vehicular Ad-Hoc Networks

To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.

Project of “Three Networks Greening” based on optimal allocation in the Yellow River Delta,China (Dongying section)

We have used the Yellow River Delta （Dongying section） as our study area to address the project of ＂Three Networks Greening＂ （TNG）. With the use of GIS technology and from an ecological point of view, an optimal allocation scheme of land resources is constructed and applied to guide the adjustment of land resources. Given this scheme, we have calculated that the area of land suitable for forest and shrubs without greening is 2256 km^2. Simultaneously, acting on the layout of the TNG project, afforestation site types are prepared and improved. Soil types, microrelief, salinity and underwater levels are combined as major classification factors and irrigation conditions as a reference to classify sites into eight types. In this way, land suitable for forest and grass is afforested given particular planting patterns. Finally, by overlaying this forestry site type map with the TNG plan map, some suggestions and strategies are proposed and used to direct the TNG project. An ecological oasis of the Yellow River Delta should be the result.

The Cloud Manufacturing Resource Scheduling Optimization Method Based on Game Theory

In order to optimize resource integration and optimal scheduling problems in the cloud manufacturing environment,this paper proposes to use load balancing,service cost and service quality as optimization goals for resource scheduling,however,resource providers have resource utilization requirements for cloud manufacturing platforms.In the process of resource optimization scheduling,the interests of all parties have conflicts of interest,which makes it impossible to obtain better optimization results for resource scheduling.Therefore,amultithreaded auto-negotiation method based on the Stackelberg game is proposed to resolve conflicts of interest in the process of resource scheduling.The cloud manufacturing platform first calculates the expected value reduction plan for each round of global optimization,using the negotiation algorithm based on the Stackelberg game,the cloud manufacturing platformnegotiates andmediateswith the participants’agents,to maximize self-interest by constantly changing one’s own plan,iteratively find multiple sets of locally optimized negotiation plans and return to the cloud manufacturing platform.Through multiple rounds of negotiation and calculation,we finally get a target expected value reduction plan that takes into account the benefits of the resource provider and the overall benefits of the completion of the manufacturing task.Finally,through experimental simulation and comparative analysis,the validity and rationality of the model are verified.

Optimal allocation of watershed management cost among different water users

The issue of water scarcity highlights the importance of watershed management. A sound watershed manage- ment should make all water users share the incurred cost. This study analyzes the optimal allocation of watershed management cost among different water users. As a consumable, water should be allocated to different users the amounts in which their marginal utilities (MUs) or marginal products (MPs) of water are equal. The value of MUs or MPs equals the water price that the watershed manager charges. When water is simultaneously used as consumable and non- consumable, the watershed manager produces the quantity of water in which the sum of MUs and/or MPs for the two types of uses equals the marginal cost of water production. Each water user should share the portion of watershed management cost in the percentage that his MU or MP accounts for the sum of MUs and/or MPs. Thus, the price of consumable water does not equal the marginal cost of water production even if there is no public good.