A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Business micro-location: factors, preferences and indicators to assess the influence factors

The paper presents a study on business micro-location behaviour as well as corresponding factors of influence, conducted in two metropolitan areas, Bucharest-Ilfov (Romania) and Greater Porto (Portugal). By business micro-location we refer to a specific site such as a building or facility, accommodating a business within a small, compact geographical area (e.g. metropolitan area). At this geographical scale, the macroeconomic layer factors were excluded, applicable when discern between regions or countries. The factors derived from location theory and previous empirical studies were surveyed, completing a cross-sectional analysis in order to find out the specific weights of the location factors and preferences, by region and by industry. Based on already established firms’ feedback on location, the specific weights were granted by each industry to the main location factors, types of areas, and types of accommodation facilities. The authors also suggested a model to integrate these results into a Geographical Information System (GIS).