Cláudio Monteiro

Fuzzy inference in spatial load forecasting

Forecasting electric demand and its geographical distribution is a prerequisite to generate expansion planning scenarios for distribution planning. This paper presents a comprehensive methodology that uses a fuzzy inference model over a GIS support, to capture the behavior of influence factors on load growth patterns and map the potential for development. The load growth is spread over maps with cellular automata. The interaction with a scenario generator inputs data into a graph generator, which will serve as a basis for more classic network planning tools.

GIS spatial analysis applied to electric line routing optimization

This paper presents a new methodology for automated route selection for the construction of new power lines, based on geographic information systems (GIS). It uses a dynamic programming model for route optimization. Environmental restrictions are taken into account together with all of the operating, maintenance, and equipment installation costs, including a new approach to the costs associated with the slope of the terrain crossed by the power lines. The computing and visual representation capacities of GIS are exploited for the selection of economic corridors, keeping the total costs under a threshold imposed by the user. Intensive simulation examples illustrate the power and flexibility of the proposed methodology.

Compromise seeking for power line path selection based on economic and environmental corridors

This paper presents a new multicriteria decision aid system (DAS) to obtain acceptable power line paths integrating the diverse socioeconomic interests of the different groups involved in the planning process, such as utilities, environmental agents, or local and regional authorities. The DAS is based on the intensive use of geographic information systems, as well as multicriteria weighting techniques reflecting all group interests. This new DAS can be used to overcome the problems raised by initially opposing positions among different groups stemming from diverse technological, economic, environmental, and/or social interests. The technique is illustrated by an intensive simulation example from a case study reproducing some of the phases of a negotiation process.

Training a FIS with EPSO under an Entropy Criterion for Wind Power prediction

This paper summarizes efforts in understanding the possible application of information theoretic learning principles to power systems. It presents the application of Renyis entropy combined with Parzen windows as a measure of information content of the error distribution in model parameter estimation in supervised learning. It illustrates the concept with an application to the prediction of power generated in a wind park, made by Takagi-Sugeno fuzzy inference systems, whose parameters are discovered with an EPSO-evolutionary particle swarm optimization algorithm

Powerful planning tools

Distributed power generation offers a solution to the limitations in the capacity of distributed systems and, at the same time, improves the reliability of the overall power system by increasing its generation capacity reserves. The planning process to integrate dispersed generation in power networks must take into account multiple factors such as the existing resources, the technology used in the generator, economic costs, and the environmental impact. Geographic information systems (GIS), software technologies developed for spatial data analysis, are suitable tools for solving these problems, and they allow the simultaneous evaluation of key technical, economic and environmental factors. The development of new techniques under the GIS platforms has increased the capabilities of GIS, allowing the systems to adapt to optimal DG planning studies. Using adequate software under the GIS platform, users can obtain useful information on the economic or technical viability of any distributed power generation facility. Governments, environmental agencies, utilities, private investors, financial corporations, and local authorities can become users of these tools and active players in the field of distributed power generation planning.

Negotiation aid system for promotion of distributed generation and renewables

This paper describes a new concept of a negotiation aid system, developed over a GIS (geographic information system) and designed to facilitate reaching compromises among agents such as investors, environmental groups and governmental agencies, when deciding the location and sizing of new renewable energy sources in a region. The core model of an actor is similar to a fuzzy inference system of the Takagi-Sugeno type, built from a definition of preferences and levels of acceptability. An outranking method is employed to define geographical places of less conflict among the several actors negotiating. An application to the region of La Rioja, in Spain, is described.

Spatial decision support system for site permitting of distributed generation facilities

Distributed generation (DG) facilities require, like other energy projects, a sitting review process to acquire the permits and approval needs for construction and operation. In this process, different groups and individuals with different roles, interests and priorities are involved. This paper presents a spatial decision support system (SDSS) that helps to identify permissible areas to install DG facilities. Wind energy facilities are used in this paper to exemplify the use of the SDSS.

Evaluation of electrification alternatives in developing countries-the SOLARGIS tool

This paper presents a methodology developed within the SOLARGIS project-a Joule project-aiming at evaluating the potential of integrating renewable forms of energy into dispersed electricity production. With this project, the authors also wanted to demonstrate the efficiency of GIS-geographical information systems-as a tool to analyse the integration of renewable forms of energy. In this paper, the authors present the methodologies developed to identify renewable resources in a given geographic region, to detect high potential areas for wind farm siting and to evaluate the efficiency and market of isolated systems to be used for dispersed rural electrification. In this last methodology, the authors used fuzzy models to describe the uncertainties in demand and cost values.

Negotiation aid system to define priority maps for wind farm development

This paper presents the structure of a negotiation aid system (NAS) to select the best locations for new DG facilities, using sophisticated spatial techniques [based on geographical information systems (GISs)] and decision aid methodologies for negotiation, based on consensus among groups that may have conflicting interests. This system helps to overcome the problems posed by initially opposing positions stemming from diverse technological, economic, environmental and/or social interests. The NAS use is illustrated with results from a negotiation process between two groups to select locations for new wind farms in the region of La Rioja, Spain.

Spatial offer and demand forecasting with neuro-fuzzy inference systems in GIS

This paper presents an overview of the basic concepts of a neuro-fuzzy inference system for spatial offer-and-demand forecasting of electric power on a geographical basis, over GIS (geographical information systems).