scholarly journals A Customized Decision Support System for Renewable Energy Application by Housing Association

2019 ◽  
Vol 11 (16) ◽  
pp. 4377 ◽  
Author(s):  
Aleksandra Besser ◽  
Jan K. Kazak ◽  
Małgorzata Świąder ◽  
Szymon Szewrański
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Housing Association ◽  
Local Scale ◽  
Environmental Data ◽  
Housing Associations ◽  
Entire Area

One of the major problems in socio-environmental systems is the growing depletion of non-renewable resources and environmental degradation, resulting from inadequate environmental management and planning. Deepening environmental problems have forced countries to create management instruments that will help repair damage and support environmental protection efforts. The aim of this research is to develop a customized decision support system for the management of renewable energy based on the existing Geographic Information Systems (GIS). The proposed tool enables assessing the potential of solar energy production at the local scale, analyzing each rooftop. Due to the scale of the analyzed area and the details of the assessment, the tool is customized to the needs of housing associations. The system combines an existing GIS tool for calculating the solar radiation potential of rooftops (SOLIS) together with Tableau software that was used to aggregate and analyze data. In order to present the applicability of the developed tool, visualizations were prepared based on housing buildings managed by the “Biskupin” Housing Association in Wrocław (Poland) which is responsible for the management of 3415 residential premises. The created system based on spatial and environmental data will help to decide how to manage the available resources and the environment at the local scale while reducing the pressure on the environment. The tool allows for the aggregation, filtering and presentation of spatial data for the entire area of a housing association, as well as for a single building.

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.

GIS-Based Decision Support System for Village Level

2018 ◽  
pp. 275-295
Author(s):  
Subbu Lakshmi Esakki Pandian ◽  
Kiran Yarrakula ◽  
Probal Chaudhury
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Rural Areas ◽  
Vital Role ◽  
Population Total ◽  
Rural Sector ◽  
Male And Female ◽  
Village Level

Decision support system (DSS) plays a vital role especially in rural areas to develop rural sector for sustainable development and socio-economic uplifting of the country. To make appropriate decisions and to develop village economy, decision support system is useful for the mandal revenue officer, collector, Surpanch, and different administrators. It deals both spatial and non-spatial data at village level and comprises various ancillary information including mandal maps and village-wise information of Anantapur and Kadapa districts of Andhra Pradesh such as number of houses, male and female, SC/ST/OBC/general (or) OC population, literate and illiterate population, total working and non-working population. Datasets are collected from district collector office, mandal revenue officer (MRO) and inserted in GIS database. This chapter makes an attempt to build features of various decisions at Anantapur and Kadapa districts by integrating various layers of information at village level.

scholarly journals Development of a decision support system for tsunami evacuation: application to the Jiyang District of Sanya city in China

2017 ◽  
Vol 17 (3) ◽  
pp. 335-343 ◽  
Author(s):  
Jingming Hou ◽  
Ye Yuan ◽  
Peitao Wang ◽  
Zhiyuan Ren ◽  
Xiaojuan Li
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
High Risk ◽  
Decision Support System ◽  
Travel Time ◽  
Support System ◽  
Spatial Data ◽  
Population Distribution ◽  
Numerical Models ◽  
Tsunami Inundation

Abstract. Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.

Operational Margin From Weather and Motion Database for Heavy Transport Vessels

2011 ◽  
Author(s):  
Jan B. de Jonge ◽  
Onno A. J. Peters
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Ship Motion ◽  
Environmental Data ◽  
Weather Data ◽  
Background Information ◽  
Motion Data ◽  
Design Values ◽  
Wave Heights

While shipping large and heavy cargo like jack-up rigs or semi-submersibles, the Motion Monitoring and Captain Decision Support system is a valuable tool to ensure a safe and economical voyage. Using the dynamic characteristics of the vessel, in combination with 5-day weather forecasts and design limits like maximum accelerations at the cargo location, roll motion and/or leg bending moments, more and better information is available to the Master to choose safe route, heading and speed. This way the best knowledge of what to expect is contributing to the safety of cargo, vessel and crew. The Octopus onboard system gathers a large amount of information about ship position, speed, heading, nowcast weather data and corresponding ship motion data. Reference is made to the paper of Peters [2] for background information of the Octopus Motion Monitoring and Decision Support system and an overview of methods used by the motion measurement system. In May 2008 the first Dockwise vessel started to gather weather and ship motion data. It is estimated that each vessel gathers around 50.000 nautical miles of data in a year, which is all collected in a database. The paper presents how this information is used for general research to environmental data, ship motion data and comparison to design values. Scatter diagrams from nowcast weather data can be produced. After collecting a certain amount of measurements, so called Dockwise scatter diagrams could be used as input for future voyage calculations. With this engineering approach Masters decisions for weather routing and bad weather avoidance is taken into account. This could lead for example to reduced design wave for a passage around the Cape of Good Hope. Now casted weather data and ship motions data is compared to design values from the cargo securing manual. Statistics like maximum difference, average difference give extensive data and insight in the operational margin of Dockwise transports. The calculation of the operational margin is independent of the standard safety margin valid for each transport. The conclusion is that the recorded nowcast significant wave height for the analyzed voyages never exceeded 5.0 [m]. With larger design wave heights the minimum operational margin increases to more than 40%, while the lowest operational margin occurs at design wave heights around 4.5 [m]. The database built by gathering all relevant information from the system and from crew observations, increases insight in the operational margins, which contributes to increased knowledge and safety.

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