Capacitor placement of distribution systems using particle swarm optimization approaches

Capacitor placement plays an important role in distribution system planning and operation. In distribution systems of electrical energy, banks of capacitors are widely installed to compensate the reactive power, reduce the energy loss in system, voltage profile improvement, and feeder capacity release. The capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. Recently, many approaches have been proposed to solve the capacitor placement problem as a mixed integer programming problem. This paper presents a new capacitor placement method which employs particle swarm optimization (PSO) approaches with operators based on Gaussian and Cauchy probability distribution functions and also in chaotic sequences for a given load pattern of distribution systems. The proposed approaches are demonstrated by two examples of application. Simulation results show that the proposed method can achieve an optimal solution as the exhaustive search can but with much less computational time.     

Effect of process parameters on the quality of aluminium alloy Al5Si deposits in wire and arc additive manufacturing using a cold metal transfer process

A 3D print device using a cold metal transfer arc welding station to melt a metallic filler wire is developed to build aluminium part by optimising the process parameters. First tests achieved using standard pre-recorded process parameters allow to study the effect of the travel speed and the average welding power on the geometrical characteristics of mono-layer deposits and on walls built by layers superposition. Finally, a parametric study of the effect of each process parameter controlling the shape of the arc current or voltage and the filler wire feeding is carried out in order to try to improve the geometrical regularity of the deposits, and to better understand the effect of each parameter on the melting of the filler wire, its transfer on the support plate, and the geometry of the formed bead.     

广东地区遗址博物馆展厅天窗优化设计初探

我国博物馆能源消耗巨大,在博物馆中合理设置采光天窗能有效降低照明能耗。遗址博物馆作为博物馆的一种类型,对其自然采光需求和遗址保护之间的矛盾亟需进一步研究。通过对广东地区遗址博物馆实地调研和对其中两个博物馆展厅的光环境测量,梳理了这一类型博物馆中展厅天窗导致局部出现眩光、整体照度过高或采光不均匀的采光现状,然后利用日光模拟软件VELUX Daylight Visualizer 2进行模拟分析,提出广东地区遗址博物馆展厅的天窗优化设计方法——天窗遮阳整合设计。例如全玻璃顶天窗设计可整合发光天棚、条形天窗可整合漫反射结构优化设计的策略,以期为广东地区遗址博物馆展厅天窗优化设计提供借鉴。     

Optimisation models to enhance resilience in evacuation planning

We argue that the concepts of resilience in engineering science and robustness in mathematical optimisation are strongly related. Using evacuation planning as an example application, we demonstrate optimisation techniques to improve solution resilience. These include a direct modelling of the uncertainty for stochastic or robust optimisation as well as taking multiple objective functions into account.     

Studies on long-term storage stability of biodiesel (B100) and its blend (B20) using Box-Behnken response surface method

The gradual depletion of fossil fuels has greatly enhanced the necessity to look for alternative fuels for automobile engines. In response to this, biodiesel is being considered as a promising and potential alternative substitute to conventional petroleum diesel. However, long-term storage stability of biodiesel is poorer compared to conventional petroleum diesel. The aim of the project work is to study the long-term storage stability of biodiesel (B100) and its blend (B20) prepared from used frying oil in different conditions of storage. In this work, the effect of antioxidants and temperature on long storage stability of biodiesel obtained from with respect to storage period is analysed using response surface methodology (RSM). The long storage of biodiesel obtained from used frying oils were optimised by varying parameters such as antioxidant concentration, storage period by Box-Behnken RSM. The properties such as the acid value and the viscosity of biodiesel were initially measured. The results of the investigation showed that the addition of sufficient concentration of antioxidant (pyrogallol) significantly maintains the acid value and viscosity of biodiesel and helps to store for a longer storage period at the given storage temperature.     

Distributed modifier-adaptation schemes for the real-time optimisation of uncertain interconnected systems

This paper proposes a set of distributed real-time optimisation schemes for the steady-state optimisation of parametrically and structurally uncertain systems that are composed of multiple interconnected subsystems. These schemes are derived in the framework of modifier adaptation and use uncertain system models of varying complexity. Consequently, each distributed modifier-adaptation scheme imposes different requirements on the available plant measurements, the communication network, and the control architecture. We prove that every scheme can converge to the plant optimum despite model uncertainty and compare the main features of each approach. Finally, we illustrate our findings via a numerical example.     

A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility

The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but not worker flexibility. Given the influence and potential of human factors in improving production efficiency and decreasing the cost in practical production systems, we propose a mathematical model of an extended FJSP with worker flexibility (FJSPW). A hybrid artificial bee colony algorithm (HABCA) is presented to solve the proposed FJSPW. For the HABCA, effective encoding, decoding, crossover and mutation operators are designed, and a new effective local search method is developed to improve the speed and exploitation ability of the algorithm. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the HABCA. Extensive computational experiments carried out to compare the HABCA with some well-performing algorithms from the literature confirm that the proposed HABCA is more effective than these algorithms, especially on large-scale FJSPW instances.     

Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS

It is of great practical significance to optimise the decision-making of cloud manufacturing service providers, which can ensure the efficient operation of the cloud manufacturing services. In order to effectively optimise, this paper constructs the evaluation index system, sorts out 7 important evaluation indexes. A method is proposed on the basis of the TOPSIS method and Grey Correlation Analysis (GRA), which is a decision-making method combining static distance and dynamic trend, and make the evaluation results more reasonable. In addition, in order to reflect the true weight of the high dimensional index, the evaluation model of projection pursuit index is established. The improved Particle Swarm Optimisation (PSO) algorithm is used to optimise the projection index function and model parameters, and to obtain the objective weights of evaluation indexes. Then the objective weights combine with the subjective weights obtained by the Analytic hierarchy process (AHP), which makes the weights of the evaluation indexes achieve the unity of subjective and objective. Finally, 20 sets of simulation examples are given to illustrate the feasibility and effectiveness of the proposed method.     

An optimal integrated lot sizing and maintenance strategy for multi-machines system with energy consumption

This paper proposes an integrated model for multi-machines dynamic lot sizing aiming to produce a single item, considering the energy consumption during the production horizon. The objective is to find, firstly, the optimal lot size as well as the number of machines that satisfy a random demand under given service level and secondly, maintenance plan depended to production planning to minimise the total production, energy and maintenance costs. In fact, the problem of energy consumption is one of the most evoked topics especially with the decision of many governments to reduce theirs (For example France is willing to reduce the total consumption by 20% by 2020). The keys of this study are to consider, firstly, the correlation between the forecasting of demand, the variation of the working machines as well as their production rates under energy constraint and secondly the correlation between the production cadences and the maintenance strategy of all machines.     

Estimation of fog utility pricing: a bio-inspired optimisation techniques' perspective

ABSTRACT

Due to the limited data storage capacity available to Internet service providers and large-scale enterprises, the concept of resource sharing arises. The services can be given on lease to enterprises through Service Level Agreements. Being the extension of the cloud computing, fog computing architecture brings the resources near end users. In order to get the services on lease, the enterprises are supposed to pay for the resources or services which are being used by them. In this paper, four nature inspired algorithms are analysed in order to determine the efficient management of services or resources so that the cost of resources can be reduced and the billing can be attained through calculation of the utilised resources. Pigeon inspired optimization, enhanced differential evolution, binary bat algorithm and simple human learning optimization are used to evaluate the energy consumed by the edge nodes or cloudlets that in turn can be used for estimating the bill through the Time of Use pricing variable. We evaluate the aforementioned techniques to analyse their performance regarding the bill calculation on the basis of fog servers usage. Simulation results demonstrate that BAT algorithm gives significantly better results than other three algorithms in terms of resource utilisation and bill reduction.