How do different densities in a network affect the optimal location of service centers?

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

Use of Photovoltaic on an E-bike? : A Feasibility Study

In recent years the number of bicycles with e-motors has been increased steadily. Within the pedelec – bikes where an e-motor supports the pedaling – a special group of transportation bikes has developed. These bikes have storage boxes in addition to the basic parts of a bike. Due to the space available on top of those boxes it is possible to install a PV system to generate electricity which could be used to recharge the battery of the pedelec. Such a system would lead to grid independent charging of the battery and to the possibility of an increased range of motor support. The feasibility of such a PV system is investigated for a three wheeled pedelec delivered by the company BABBOE NORDIC.The measured data of the electricity generation of this mobile system is compared to the possible electricity generation of a stationary system.To measure the consumption of the pedelec different tracks are covered, and the energy which is necessary to recharge the bike battery is measured using an energy logger. This recharge energy is used as an indirect measure of the electricity consumption. A PV prototype system is installed on the bike. It is a simple PV stand alone system consisting of PV panel, charge controller with MPP tracker and a solar battery. This system has the task to generate as much electricity as possible. The produced PV current and voltage aremeasured and documented using a data logger. Afterwards the average PV power is calculated. To compare the produced electricity of the on-bike system to that of a stationary system, the irradiance on the latter is measured simultaneously. Due to partial shadings on the on-bike PV panel, which are caused by the driver and some other bike parts, the average power output during riding the bike is very low. It is too low to support the motor directly. In case of a similar installation as the PV prototype system and the intention always to park the bike on a sunny spot an on-bike system could generate electricity to at least partly recharge a bike battery during one day. The stationary PV system using the same PV panel could have produced between 1.25 and 8.1 times as much as the on-bike PV system. Even though the investigation is done for a very specific case it can be concluded that anon-bike PV system, using similar components as in the investigation, is not feasible to recharge the battery of a pedelec in an appropriate manner. The biggest barrier is that partial shadings on the PV panel, which can be hardly avoided during operation and parking, result in a significant reduction of generated electricity. Also the installation of the on-bike PV system would lead to increased weight of the whole bike and the need for space which is reducing the storage capacity. To use solar energy for recharging a bike battery an indirect way is giving better results. In this case a stationary PV stand alone system is used which is located in a sunny spot without shadings and adjusted to use the maximum available solar energy. The battery of the bike is charged using the corresponding charger and an inverter which provides AC power using the captured solar energy.

A stopping rule while searching for optimal solution of facility-location

Solutions to combinatorial optimization, such as p-median problems of locating facilities, frequently rely on heuristics to minimize the objective function. The minimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. However, pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small branch of the literature suggests using statistical principles to estimate the minimum and use the estimate for either stopping or evaluating the quality of the solution. In this paper we use test-problems taken from Baesley's OR-library and apply Simulated Annealing on these p-median problems. We do this for the purpose of comparing suggested methods of minimum estimation and, eventually, provide a recommendation for practioners. An illustration ends the paper being a problem of locating some 70 distribution centers of the Swedish Post in a region.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Analyzing the Effect of Soiling on the Performance of a Photovoltaic System of Different Module Technologies in Kalkbult, South Africa

The fact that most of the large scale solar PV plants are built in arid and semi-arid areas where land availability and solar radiation is high, it is expected the performance of the PV plants in such locations will be affected significantly due to high cell temperature as well as due to soiling. Therefore, it is essential to study how the different PV module technologies will perform in such geographical locations to ensure a consistent and reliable power delivery over the lifetime of the PV power plants. As soiling is strongly dependent on the climatic conditions of a particular location a test station, consisted of about 24 PV modules and a well-equipped weather station, was built within the fences of Scatec’s 75 MW Kalkbult solar PV plant in South Africa. This study was performed to a better understand the effect of soiling by comparing the relative power generation by the cleaned modules to the un-cleaned modules. Such knowledge can enable more quantitative evaluations of the cleaning strategies that are going to be implemented in bigger solar PV power plants. The data collected and recorded from the test station has been analyzed at IFE, Norway using a MatLab script written for this thesis project. This thesis work has been done at IFE, Norway in collaboration with Stellenbosch University in South Africa and Scatec Solar a Norwegian independent power producer company. Generally for the polycrystalline modules it is found that the average temperature corrected efficiency during the period of the experiment has been 15.00±0.08 % and for the thin film-CdTe with ARC is 11.52% and for the thin film without ARC is about 11.13% with standard uncertainty of ±0.01 %. Besides, by comparing the initial relative average efficiency of the polycrystalline-Si modules when all the modules have been cleaned for the first time and the final relative efficiency; after the last cleaning schedule which is when all the reference modules E, F, G, and H have been cleaned for the last time it is found that poly3 performs 2 % and 3 % better than poly1 and poly16 respectively, poly13 performs 1 % better than poly15 as well as poly5 and poly12 performs 1 % and 2 % better than poly10 respectively. Besides, poly5 and poly12 performs a 9 % and 11 % better than poly7. Furthermore, there is no change in performance between poly6 and poly9 as well as poly4 and poly15. However, the increase in performance of poly3 to poly1, poly13 to poly15 as well as poly5 and poly12 to poly10 is insignificant. In addition, it is found that TF22 perform 7% better than the reference un-cleaned module TF24 and similarly; TF21 performs 7% higher than TF23. Furthermore, modules with ARC glass (TF17, TF18, TF19, and TF20) shows that cleaning the modules with only distilled water (TF19) or dry-cleaned after cleaned with distilled water(TF20) decreases the performance of the modules by 5 % and 4 % comparing to its respective reference uncleanedmodules TF17 and TF18 respectively.