Search Results (3)

Lighting is the largest source of electricity consumption. The implementation of new technologies makes it possible to reduce the energy bill as well as the operating costs. In this work, we created a control and management system for exterior lighting using creative, intelligent, and autonomous methods. The project allows control room operators to monitor the system and interact when needed. Our project is subdivided into three major parts, ordering, data processing, and action. The first part is carried out in two modes: manually using an Optocoupler and controlled with a graphical interface by RS232 serial-type communication. The second part is processed by a microcontroller; as for the third part, it controls three poles through an MOC3023 Optotriac IC and BTA16-600B Triac for full and half lighting. For the controlled mode, we used the dimmer principle which works by essentially chopping parts out of the AC voltage. The brightness of the lamp is determined by the power transferred to it, so the more the waveform is chopped, the more it dims. A zero crossing control is needed for phase cutting. The graphical application of our project has a rather rough design. It is divided into two windows: the first consists of a connection window, and the second one is for the main control interface. On this control interface, there are basically three tabs: connection and serial connection status, control, and operating mode. Full article

The decision-making process regarding heating supply system options in a district perspective is extremely challenging. This paper aims to present a new method to support urban energy decisions in real-time processes, which was developed in the context of a European project (DIMMER (District Information Modeling and Management for Energy Reduction, 2013–2016)). The method is composed of three parts: (i) a new web-based spatial decision support system (SDSS), called “Dashboard”; (ii) an ad hoc energy-attribute analysis (EAA) tool to be integrated into Dashboard; and (iii) a multi-criteria decision analysis (MCDA). In contrast to other SDSSs, one of the main strengths of Dashboard is the ability to acquire, store, and manage both geo-referenced and non-geo-referenced data, and perform real-time analyses of spatial problems taking into account a wide range of information. In this sense, Dashboard can formally visualize and assess a potentially infinite number of attributes and information, as it is able to read and process very large web databases. This characteristic makes Dashboard a very effective tool that can be used in real-time during focus groups or workshops to understand how the criterion trade-offs evolve when one, or several, decision parameters change. The paper describes the main procedure of the new method and testing of Dashboard test on a district in Turin (Italy). Full article

Nowadays, there is an increasing concern about sustainable urban energy development taking into account national priorities of each city. Many cities have started to define future strategies and plans to reduce energy consumption and greenhouse gas emissions. Urban energy scenarios involve the consideration of a wide range of conflicting criteria, both socio-economic and environmental ones. Moreover, decision-makers (DMs) require proper tools that can support their choices in a context of multiple stakeholders and a long-term perspective. In this context, Multicriteria Spatial Decision Support Systems (MC-SDSS) are often used in order to define and analyze urban scenarios since they support the comparison of different solutions, based on a combination of multiple factors. The main problem, in relation to urban energy retrofitting scenarios, is the lack of appropriate knowledge and evaluation criteria. The latter are crucial for delivering and assessing urban energy scenarios through a MC-SDSS tool. The main goal of this paper is to analyze and test two different methods for the definition and ranking of the evaluation criteria. More specifically, the paper presents an on-going research study related to the development of a MC-SDSS tool able to identify and evaluate alternative energy urban scenarios in a long-term period perspective. This study refers to two Smart City and Communities research projects, namely: DIMMER (District Information Modeling and Management for Energy Reduction) and EEB (Zero Energy Buildings in Smart Urban Districts). Full article