计及用户满意度的智慧工业园区配能优化策略

随着智能配电网的发展,工业园区也逐步向智慧化迈进。针对智慧工业园区难以充分发挥需求侧用户的响应能力,导致用能水平低、运行经济差的问题,提出一种考虑用户满意度的智慧工业园区配能优化策略。首先,提取园区内用户的负荷特性,基于用户用电行为特征,对园区可响应资源进行评估,实现园区工业用户需求响应的潜力分析及响应意愿评估。然后,引入分布式光伏及用户侧需求响应资源,建立以需求响应成本、电网购电成本、碳排放成本、设备运行维护成本之和最小为目标的工业园区配能优化模型,并采用非支配排序遗传算法对该模型进行求解。最后,选取华北某市的工业园区作为案例,验证了所提方法的有效性。

Configuration optimization model of multi-energy distributed generation system

To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model mainly consists of two parts, the determination of initial configuration schemes according to user preference and the selection of the optimal scheme. The comprehensive evaluation index（CEI）, which is acquired through the analytic hierarchy process（AHP） weight calculation method, is adopted as the evaluation criterion to rank the initial schemes. The optimal scheme is obtained according to the ranking results. The proposed model takes the diversity of different equipment parameters and investment cost into consideration and can give relatively suitable and economical suggestions for system configuration.Additionally, unlike Homer Pro, the proposed model considers the complementation of different renewable energy resources, and thus the rationality of the multi-energy DG system is improved compared with the single evaluation criterion method which only considers the total cost.

Improving the BER performance of turbo codes with short frame size based on union bound

timizing the formula, the energy for every bit of the codeword is optimized to achieve the minimum BER at high SNR region. At last, an adjustable parameter is employed to compensate the degrada- tions of BER at low and moderate SNR regions. Case studies indicate that the improvements of BER for turbo codes with short frame size are significant at a wide range of SNR

A Fairness Resource Allocation Algorithm for Coverage and Capacity Optimization in Wireless Self-Organized Network

To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.

Bacterial graphical user interface oriented by particle swarm optimization strategy for optimization of multiple type DFACTS for power quality enhancement in distribution system

This study proposes a graphical user interface(GUI) based on an enhanced bacterial foraging optimization(EBFO) to find the optimal locations and sizing parameters of multi-type DFACTS in large-scale distribution systems.The proposed GUI based toolbox,allows the user to choose between single and multiple DFACTS allocations,followed by the type and number of them to be allocated.The EBFO is then applied to obtain optimal locations and ratings of the single and multiple DFACTS.This is found to be faster and provides more accurate results compared to the usual PSO and BFO.Results obtained with MATLAB/Simulink simulations are compared with PSO,BFO and enhanced BFO.It reveals that enhanced BFO shows quick convergence to reach the desired solution there by yielding superior solution quality.Simulation results concluded that the EBFO based multiple DFACTS allocation using DSSSC,APC and DSTATCOM is preferable to reduce power losses,improve load balancing and enhance voltage deviation index to 70%,38% and 132% respectively and also it can improve loading factor without additional power loss.

Step-wise synthesis of work exchange networks involving heat integration based on the transshipment model

Due to the deterioration of serious energy dilemma,energy-conservation and emission–reduction have been the strategic target in the past decades,thus people have identified the vital importance of higher energy efficiency and the influence of lower carbon development.Since work exchange network is a significant part of energy recovery system,its optima design will have dramatically significant effect on energy consumption reduction in chemical process system.With an extension of the developed transshipment model in isothermal process,a novel step-wise methodology for synthesis of direct work exchange network(WEN)in adiabatic process involving heat integration is first proposed in this paper,where a nonlinear programming(NLP)model is formulated by regarding the minimum utility consumption as objective function and optimizing the initial WEN in accordance with the presented matching rules to get the optimized WEN configuration at first.Furthermore,we focus on the work exchange network synthesis with heat integration to attain the minimal total annual cost(TAC)with the introduction of heat-exchange equipment that is achieved by the following strategies in sequence:introducing heat-exchange equipment directly,adjusting the work quantity of the adjacent utility compressors or expanders,and approximating upper/lower pressure limits consequently to obtain considerable cost savings of expanders or compressors and work utility.Finally,a case taken from the literature is studied to illustrate the feasibility and effectiveness of the proposed method.

Attitude control allocation strategy of high altitude airship based on synthetic performance optimization

This paper presents a method for solving the attitude control problem of high altitude airship (HAA) with aerodynamic fin and vectored thruster control. The algorithm is based on the synthetic optimization of dynamic performance and energy consumption of airship. Firstly, according to the system overall configuration, the dynamic model of HAA was established and the HAA linearized model of longitudinal plane motion was obtained. Secondly, using the classic PID control theory, the HAA attitude control system was designed. Thirdly, through analyzing the dynamic performance of airship with fin or vectored thruster control, the synthetic performance index function with different weighting functions was determined. By means of optimizing the obtained performance index function, the attitude control of high altitude airship with good dynamic performance and low energy consumption was achieved. Finally, attitude control allocation strategy was designed for the airship station keeping at an altitude of 22 km. The simulation experiment proved the validity of the proposed algorithm.

Productivity prediction model and optimal configuration of herringbone multilateral well

In order to accurately predict the productivity of herringbone multilateral well,a new productivity prediction model was founded.And based on this model,orthogonal test and multiple factor variance analysis were applied to study optimization design of herringbone multilateral well.According to the characteristics of herringbone multilateral well,by using pressure superposition and mirror image reflection theory,the coupled model of herringbone multilateral well was developed on the basis of a three-dimensional pseudo-pressure distribution model for horizontal wells.The model was formulated in consideration of friction loss,acceleration loss of the wellbore and mixed loss at the confluence of main wellbore and branched one.After mathematical simulation on productivity of the herringbone multilateral well with the coupled model,the effects of well configuration on productivity were analyzed.The results show that lateral number is the most important factor,length of main wellbore and length of branched wellbore are the secondary ones,angle between main and branched one has the least influence.

Energy Efficient Resource Allocation in Timesharing Multiuser Systems with Hybrid Energy Harvesting Transmitter

An energy effi cient resource allocation scheme in timesharing multiuser system with a hybrid energy harvesting transmitter is studied in this paper. Specially, the operation energy of system is supplied by constant energy and energy harvesting, which harvests energy from external environment. Our goal is to maximize the energy effi ciency of timesharing multiuser systems by considering jointly allocation of transmission time and power control in an off-line manner. The original nonconvex objective function is transformed into convex optimization problem via the fractional programming approach. Then, we solve the convex problem by Lagrange dual decomposition method. Simulation results show that the proposed energy efficient resource allocation scheme has a better performance than the scheme which decomposes optimization problem into two parts(power allocation, time allocation) to solve iteratively.

Evolutionary Finance： The Case of TEDPIX Tracker Fund Selection

Optimal allocation of financial resources is a critical factor in investment decisions. A proper action in this regard requires the existence of appropriate bases and investing tools and techniques in the capital market. One of these effective methods which is considered as the basis of new investment strategies, in addition to multiple unique features, is called index tracking. By considering the undeniable role of this approach in the future of capital markets, its investigation and implementation have been considered in this research and so the problem of optimal Tehran Exchange Dividend Price Index （TEDPIX） tracker fund selection is studied using a hybrid approach of genetic algorithm and quadratic programming. Neural network was applied to simulate unavailable data. Results illustrate the exactness and acceptable performance of the formed portfolios in several iterations such that achieving similar and even better performance compared to the index is a distinctive characteristic of the proposed algorithm.

Analysis of Methodology for the Application of Stratified Random Sampling with Optimum Allocation： The Case Study of Forest Bioenergy

In this paper, analysis of methodology was realized for the application of stratified random sampling with optimum allocation in the case of a subject of research which concerns the rural population and presents high differentiations among the three strata in which this population could be classified. The rural population of Evros Prefecture （Greece） with criterion the mean altitude of settlements was classified in three strata, the mountainous, semi-mountainous and fiat population for the estimation of mean consumption of forest fuelwood for covering of heating and cooking needs in households of these three strata. The analysis of this methodology includes： （1） the determination of total size of sample for entire the rural population and its allocation to the various strata; （2） the investigation of effectiveness of stratification with the technique of analysis of variance （One-Way ANOVA）; （3） the conduct of sampling research with the realization of face-to-face interviews in selected households and （4） the control of forms of the questionnaire and the analysis of data by using the statistical package for social sciences, SPSS for Windows. All data for the analysis of this methodology and its practical application were taken by the pilot sampling which was realized in each stratum. Relative paper was not found by the review of literature.

The optimal power distribution in cooperative communication relay system

In order to optimize power utilization of relay nodes in cooperative communication,a power allocation algorithm with objective function to maximize system capacity is proposed.Based on the convex optimization theory,an ellipsoid algorithm is used to solve this problem,which could simplify the subgradient choosing steps and improve convergence stability,so that an optimized power allocation algorithm is presented.Theoretical analysis and simulation results show that the algorithm can effectively distribute the power of each node with lower complexity,and ensure the transmission capability of relay nodes in cooperative communication.

Subcarrier and power allocation in OFDM-based cognitive radio networks

We formulate the subcarrier and power allocation problem in cognitive radio networks employing orthogonal frequency division multiplexing （OFDM） as a non-linear optimization problem with the objective of maximizing sum capacity under constraints of available subcarriers, interference temperature, power budget, etc. A close-to-optimal solution with much reduced complexity is proposed to separate the problem into two steps, which also considers fairness among secondary users. A fair al- gorithm for subcarrier allocation （FA_SA） is firstly presented. Secondly, a fast iterative water-filling algorithm for power allocation （FIWFA_PA） is also proposed to maximize the sum capacity. Exten- sive simulation results show that sum capacity performance of our low-complexity solution is very close to the optimal one, while significantly improving fairness and reducing computation complexity compared with the existing solutions.

Prediction of the lowest energy configuration for Lennard-Jones clusters

Based on the work of previous researchers, a new unbiased optimization algorithm—the dynamic lattice searching method with two-phase local search and interior operation (DLS-TPIO)—is proposed in this paper. This algorithm is applied to the optimization of Lennard-Jones (LJ) clusters with N=2–650, 660, and 665–680. For each case, the putative global minimum reported in the Cambridge Cluster Database (CCD) is successfully found. Furthermore, for LJ533 and LJ536, the potential energies obtained in this study are superior to the previous best results. In DLS-TPIO, a combination of the interior operation, two-phase local search method and dynamic lattice searching method is adopted. At the initial stage of the optimization, the interior operation reduces the energy of the cluster, and gradually makes the configuration ordered by moving some surface atoms with high potential energy to the interior of the cluster. Meanwhile, the two-phase local search method guides the search to the more promising region of the configuration space. In this way the success rate of the algorithm is significantly increased. At the final stage of the optimization, in order to decrease energy of the cluster further, the positions of surface atoms are further optimized by using the dynamic lattice searching method. In addition, a simple new method to identify the central atom of icosahedral configurations is also presented. DLS-TPIO has higher computing speed and success rates than some well-known unbiased optimization methods in the literature.

Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design

Pigeon-inspired optimization(PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. A variant of pigeon-inspired optimization named multi-objective pigeon-inspired optimization(MPIO) is proposed in this paper. It is also adopted to solve the multi-objective optimization problems in designing the parameters of brushless direct current motors, which has two objective variables, five design variables, and five constraint variables. Furthermore, comparative experimental results with the modified non-dominated sorting genetic algorithm are given to show the feasibility, validity and superiority of our proposed MIPO algorithm.