یک سیستم پشتیبانی تصمیم گیری برای بهره برداری بهینه از انرژی باد در مقیاس منطقه ای
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|20394||2012||11 صفحه PDF||سفارش دهید||8251 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Renewable Energy, Volume 37, Issue 1, January 2012, Pages 299–309
Wind is a promising sustainable energy resource that can help in reducing the dependence on fossil fuels. Models and tools can be effectively used to assess the resource availability, the possible exploitation, and the environmental impact. The aim of this work is to propose an Environmental Decision Support System (EDSS) for the sustainable design of wind power plants both in terms of the site selection over a regional territory and of the optimal technology to be installed. Specifically, the proposed EDSS is suited to territories with a complex orography (such as several regions of the Mediterranean coasts), and for the installation of plants in the class of power between 500 kW and 1000 kW. The different EDSS modules are applied to a specific case study, supporting the decision maker on the exploitation of wind power plants in the Savona District, Liguria Region, Italy.
Sustainable energy systems can be defined as systems that can provide energy services to the present generation while ensuring that similar levels of energy services can be provided for future generations . The limited availability of fossil fuel resources makes urgent the adoption of suitable strategies in the energy sectors in order to prevent an economic and social emergency that, in the absence of adequate strategies, will arrive sooner or later. In trend towards the diversification of the energy market, wind power is probably the most promising sustainable energy resource. The wind is a clean and inexhaustible resource available all over the world. Recent progress in wind technology has led to cost levels comparable, in many cases, with conventional methods of electricity generation. Moreover, the number of wind turbines coming into operation increases significantly year after year. Produced energy from wind resources in the European Union (EU15) increased from 417 TOE to 7680 TOE in ten years (1996–2007, Eurostat). Generation of electricity by wind energy has the potential to contribute to a country’s economic growth, especially in developing countries and to reduce environmental impacts caused by the use of fossil fuels to generate electricity because, unlike fossil fuels, wind energy does not generate atmospheric contaminants or thermal pollution, thus being attractive to many governments, organizations, and individuals. As electric power demand increases, it will be necessary to evaluate locations for renewable energy generation . Geographic information systems (GIS) have had an increasingly fast development in the last two decades. A GIS is a system that is able to capture, store, process, analyze and present geo-spatial data and information . The selection of the most adequate location for wind plants is a major and very important task. GIS are often coupled with software systems that integrate models, or databases or other decision aids, in a way that decision makers can be supported in the decisions on a territory and on the related environmental issues. These set of systems are commonly referred to as Environmental Decision Support Systems . In literature, there are several examples of EDSS applied to the exploitation of renewable energy systems. Aran Carrion et al.  developed an EDSS based on multi-criteria analysis and GIS, taking into account environment, orography, location, and climate factors, for selecting optimal sites for grid-connected photovoltaic power plants. Rodman and Meentemeyer  developed an analytic framework using a GIS to evaluate site suitability for wind turbines and to predict the locations and extent of land available for feasible wind power development. Cavallaro and Ciraolo  demonstrated that the multi-criteria analysis can provide a valid tool to aid decision making for achieving targets relating to more sustainable green energy. The geo-spatial multi-criteria analysis is a suitable technique to take into account–at an early stage of the design process–a wide variety of environmental and administrative factors and assign corresponding weights . Several factors, such as technological limitations, environmental conditions, administrative and logistic conditions, have to be taken into account in order to support the decision for best location . Amy et al.  showed that some of the factors like policy support, new technologies, and financial mechanisms do accelerate opportunities of adopting wind power from suitable wind farm. However, some factors such as the disparity of different parties and uncertainty of land usage do have negative impacts. The aim of this work is to propose an EDSS for the sustainable design of wind power plants (WPPs) as regards the identification of the proper sites over a regional territory and the optimal technology to be installed in those sites. Specifically, the proposed framework is suited to territories with a complex orography (such as several regions of the Mediterranean coasts), and for the installation of plants in the class of powers between 500 kW and 1000 kW. The different modules of EDSS are exemplified in a case study, supporting the decision maker on the exploitation of wind power plants in the Savona District, Liguria Region, Italy.
نتیجه گیری انگلیسی
WPP are more and more chosen as the technology to produce renewable energy. In this work, a comprehensive approach to support decisions on wind power exploitation from a topology and a technologic viewpoint has been described and tested on an Italian district (Savona). Despite its “clean” characteristics, a WPP is often subject to some critics (landscape, environmental, noise etc…) which somehow limits their effective exploitation. In this work, these aspects have been taken into account both at GIS level and in a specific final module. Specifically, in the environmental impact assessment module, the CO2 emissions, the impact on the animals, and the noise, are evaluated and compared with a power plant producing the same quantity of energy with traditional fossil fuel. The approach proposed in this paper aims to present a comprehensive practical methodology to support decision makers and local authorities in the sustainable design of wind power plants both in terms of the site selection over a regional territory and of the optimal technology to be installed. The spatial information regarding the eligible areas from a regulation viewpoint should be intersected with areas where wind can be effectively exploited from an energy viewpoint. Furthermore, adequate selection criteria to identify eligible areas are mostly affected by local and regional policies. Thus, the methodology developed here can be applied elsewhere, according to regional and territorial regulations and environmental, social and work constraints restrictions. It is important to reckon that, as it is typical with EDSS, the proposed software system just aims to fill the gap between the great amount of data dealing with the problem and spatially distributed over a complex territory and decision makers. It also suggests possible solutions, which may be accepted or not by the decision maker according direct inspections, additional verifications or according to criteria which are not currently included in the system. Beside this, all the EDSS modules can be easily exploited to case studies different from the one presented in this paper. Some remarks may be added as regards the DSS output, since it is currently limited to specific technologies. Future work will deal with improvements of the optimisation module so that the technology can be optimally specified not according to a set of existing technologies, but the optimal technologic specifications will result as the DSS output (e.g diameter D, hub height Hhub, rotation speed of rotor N, optimal speed of operation Vdes, nominal power of rotor Pn, type of regulation and type of generator) and improvement in site characterization by introducing factors related to accessibility and grid connection. Moreover, a module for interpolating wind speed data in known locations should be added in order to predict wind speed also in areas in which measurements are not available. This is a complex task and is itself a research theme that can be developed both through the use of black-box models and the use of physically-based wind flow models.