Methodological issues in applying Location Models to Rural areas

Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases.  In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.

Distance measure and the p-median problem in rural areas

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

Photovoltaic System Design for a Contaminated Area in Falun – Comparison of South and East- West Layout

In this thesis the solar part of a large grid-connected photovoltaic system design has been done. The main purpose was to size and optimize the system and to present figures helping to evaluate the prospective project rationality, which can potentially be constructed on a contaminated area in Falun. The methodology consisted in PV market study and component selection, site analysis and defining suitable area for solar installation; and system configuration optimization based on PVsyst simulations and Levelized Cost of Energy calculations. The procedure was mainly divided on two parts, preliminary and detailed sizing. In the first part the objective was complex, which included the investigation of the most profitable component combination and system optimization due to tilt and row distance. It was done by simulating systems with different components and orientations, which were sized for the same 100kW inverter in order to make a fair comparison. For each simulated result a simplified LCOE calculation procedure was applied. The main results of this part show that with the price of 0.43 €/Wp thin-film modules were the most cost effective solution for the case with a great advantage over crystalline type in terms of financial attractiveness. From the results of the preliminary study it was possible to select the optimal system configuration, which was used in the detailed sizing as a starting point. In this part the PVsyst simulations were run, which included full scale system design considering near shadings created by factory buildings. Additionally, more complex procedure of LCOE calculation has been used here considered insurances, maintenance, time value of money and possible cost reduction due to the system size. Two system options were proposed in final results; both cover the same area of 66000 m2. The first one represents an ordinary South faced design with 1.1 MW nominal power, which was optimized for the highest performance. According to PVsyst simulations, this system should produce 1108 MWh/year with the initial investment of 835,000 € and 0.056 €/kWh LCOE. The second option has an alternative East-West orientation, which allows to cover 80% of occupied ground and consequently have 6.6 MW PV nominal power. The system produces 5388 MWh/year costs about 4500,000 € and delivers electricity with the same price of 0.056 €/kWh. Even though the EW solution has 20% lower specific energy production, it benefits mainly from lower relative costs for inverters, mounting and annual maintenance expenses. After analyzing the performance results, among the two alternatives none of the systems showed a clear superiority so there was no optimal system proposed. Both, South and East-West solutions have own advantages and disadvantages in terms of energy production profile, configuration, installation and maintenance. Furthermore, the uncertainty due to cost figures assumptions restricted the results veracity.

How does the use of different road networks effect the optimal location of facilities in rural areas?

The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.