Importance of implementing smart renewable energy system using heuristic neural decision support system

2021 ◽  
Vol 45 ◽  
pp. 101185
Author(s):  
Wei Zhu ◽  
Da Jiang ◽  
BalaAnand Muthu ◽  
Tamizharasi G. Seetharam
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Energy System ◽  
Renewable Energy System

scholarly journals Decision Support System for a Low Voltage Renewable Energy System

Energies ◽  
2017 ◽  
Vol 10 (1) ◽  
pp. 118 ◽  
Author(s):  
Iulia Stamatescu ◽  
Nicoleta Arghira ◽  
Ioana Făgărăşan ◽  
Grigore Stamatescu ◽  
Sergiu Iliescu ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Low Voltage ◽  
Energy System ◽  
Renewable Energy System

scholarly journals An Innovative Decision Support System to Improve the Energy Efficiency of Buildings in Urban Areas

2020 ◽  
Vol 12 (2) ◽  
pp. 259 ◽  
Author(s):  
Małgorzata Sztubecka ◽  
Marta Skiba ◽  
Maria Mrówczyńska ◽  
Anna Bazan-Krzywoszańska
Keyword(s):  
Energy Efficiency ◽  
Renewable Energy ◽  
Decision Support ◽  
Geographic Information Systems ◽  
Decision Support System ◽  
Support System ◽  
Urban Areas ◽  
Renewable Energy Sources ◽  
Decision Makers ◽  
Energy Sources

Improving in the energy efficiency of urban buildings, and maximizing the savings and the resulting benefits require information support from city decision-makers, planners, and designers. The selection of the appropriate analytical methods will allow them to make optimal design and location decisions. Therefore, the research problem of this article is the development of an innovative decision support system using multi-criteria analysis and Geographic Information Systems (decision support system + Geographic Information Systems = DGIS) for planning urban development. The proposed decision support system provides information to energy consumers about the location of energy efficiency improvement potential. This potential has been identified as the possibility of introducing low-energy buildings and the use of renewable energy sources. DGIS was tested in different construction areas (categories: A, B, C, D), Zielona Góra quarters. The results showed which area among the 53 quarters with a separate dominant building category was the most favorable for increasing energy efficiency, and where energy efficiency could be improved by investing in renewable energy sources, taking into account the decision-maker. The proposed DGIS system can be used by local decision-makers, allowing better action to adapt cities to climate change and to protect the environment. This approach is part of new data processing strategies to build the most favorable energy scenarios in urban areas.

scholarly journals A systematic approach for assessment of renewable energy using analytic hierarchy process

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Gerçek Budak ◽  
Xin Chen ◽  
Serdar Celik ◽  
Berk Ozturk
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Analytic Hierarchy Process ◽  
Support System ◽  
Systematic Approach ◽  
Analytic Hierarchy ◽  
The World ◽  
Hierarchy Process

Abstract Background Cities around the world face a great challenge in establishing a long-term strategy for the development of energy alternatives. Previous research tried to identify renewable energy across many different cities. Because each city has unique characteristics in terms of geographic and environmental conditions, population, economic development, and social and political environment, the most sustainable energy source for one city might be the least sustainable for another. Methods This research develops and implements a systematic approach to assess renewable energy and identify the energy alternatives for a city using the analytic hierarchy process. The methodology integrates experts’ input and data analytics and helps decision-makers form long-term strategies for renewable energy development. Results The decision support system is applied to three cities, Chengdu in China, Eskisehir in Turkey, and Chicago in the United States of America. Results show that improving energy efficiency and development of solar and wind energy are the most preferred energy alternatives whereas nuclear and hydroelectric are the least preferred energy alternatives for these three cities. Conclusions The results of this study are in line with decades of research and development in energy alternatives and show a clear direction for the future development of energy alternatives around the world. There are differences in the rankings of energy alternatives for different cities, indicating that it is necessary to apply the decision support system developed in this study to help form customized energy strategies for cities with unique characteristics.

Evaluation of Renewable Energy potential using a GIS decision support system

1998 ◽  
Vol 13 (3) ◽  
pp. 333-344 ◽  
Author(s):  
D. Voivontas ◽  
D. Assimacopoulos ◽  
A. Mourelatos ◽  
J. Corominas
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Energy Potential
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