INTELLIGENT AND ADAPTIVE FUZZY CONTROL SYSTEM FOR ENERGY EFFICIENT HOMES

“Smart houses” have widely established their position as a research field during the last decade. Nowadays the technical solutions related to energy resource management are being rapidly developed and integrated into the daily lives of people. The energy resource management systems use sensor networks for receiving and processing information during the realia time. Smart house adaptive and intelligent solutions has advanced towards common environment, which can take care of the inhabitants’ well-being in numerous ways. This paper propose to use a context sensitive and proactive fuzzy control system for controlling the automation processes in smart house environment. The designed monitoring system has adaptive and intelligent options, and it can operate using real time information received from sensors. The system is designed to operate fully in the background and can be installed to any exiting working system. This paper describes a central heating boiler control system implemented using the fuzzy control system designed. Author concentrates on the basic operation of such systems and present findings from the design process and initial tests

A Decision Support System for Planning and Operation of Maintenance and Customer Services in Electric Power Distribution Systems

This chapter aims to present the design and development of a decision support system (DSS) for the analysis, simulation, planning, and operation of maintenance and customer services in electric power distribution system (EPDS). The main objective of the DSS is to improve the decision‐making processes through visualization tools and simulation of real cases in the EPDS, in order to allow better planning in the short, medium, and long term. Therefore, the DSS helps managers and decision‐makers to reduce maintenance and operational costs, to improve system reliability, and to analyze new scenarios and conditions for system expansion planning. First, we introduce the key challenges faced by the decision‐makers in the planning and operation of maintenance and customer services in EPDS. Next, we discuss the benefits and the requirements for the DSS design and development, including use cases modeling and the software architecture. Afterwards, we present the capabilities of the DSS and discuss important decisions made during the implementation phases. We conclude the chapter with a discussion about the obtained results, pointing out the possible enhancements of the DSS, future extensions, and new use cases that may be addressed

Business intelligence in the electrical power industry

Nowadays, the electrical power industry has gained tremendous interest from both entrepreneurs and researchers due to its essential roles in everyday life. However, the current sources for generating electricity are astonishing decreasing, which leads to more challenges for the power industry. Based on the viewpoint of sustainable development, the solution should maintain three layers of economically, ecologically, and society; simultaneously, support business decision-making, increases organizational productivity and operational energy efficiency. In the smart and innovative technology context, business intelligence solution is considered as a potential option in the data-rich environment, which is still witnessed disjointed theoretical progress. Therefore, this study aimed to conduct a systematic literature review and build a body of knowledge related to business intelligence in the electrical power sector. The author also built an integrative framework displaying linkages between antecedents and outcomes of business intelligence in the electrical power industry. Finally, the paper depicted the underexplored areas of the literature and shed light on the research objectives in terms of theoretical and practical implications

Business Intelligence aplicado à eficiência energética dos edificios em Portugal

Com o objetivo de promover o desenvolvimento sustentável, diversas entidades internacionais têm adotado diretrizes que buscam equilibrar os aspetos económico, social e ambiental. Entre estas diretrizes, destacam-se a Agenda de Desenvolvimento 2030 da ONU, de 2015, e o Pacto Ecológico Europeu, de 2020, que, entre suas prescrições, estipulam que se tenha atenção com a ação climática, que se busque energia limpa, acessível e segura e que seja promovida a eficiência energética. Em nossa pesquisa, percebemos que, em Portugal, as informações disponíveis nesta temática são escassas e os dados de má qualidade. Desta forma, as ações individuais e coletivas para melhoria da eficiência energética como um todo ficam prejudicadas. Com vista a solucionar esta questão, buscamos identificar se a aplicação de uma abordagem de Business Intelligence & Analytics poderia colaborar para melhorar a tomada de decisões relacionadas à eficiência energética, nos níveis estratégico, tático e operacional. Limitamos a pesquisa aos edifícios residenciais e, após fazer a extração e o tratamento dos dados disponíveis, usamos ferramentas de análise e visualização do Power BI para convertê-los em informações. O resultado foi a obtenção de informações úteis, fiáveis e de fácil compreensão. Atingido este resultado, concluímos que a hipótese levantada se confirma e que uma abordagem de Business Intelligence & Analytics de facto colabora para melhorar a tomada de decisões relacionadas à eficiência energética

An e-business model for the participation of households in the Serbian electricity market based on smart grid technologies

Предмет истраживања дисертације је развој модела електронског пословања заснованог на флексибилном учешћу потрошача на српском тржишту електричне енергије. Циљ је развoj одрживoг и применљивoг моделa електронског пословања који омогућава учешће домаћинстава и појединачних уређаја на балансном тржишту и на берзи електричне енергије коришћењем smart grid технологија и demand-response сервиса. Учествовањем појединачних домаћинстава и уређаја у балансном тржишту омогућава се прецизна контрола фреквенције електроенергетског система, што oтвара могућности за експлоатацију обновљивих извора електричне енергије преко флексибилнијег и тачнијег управљања флуктуацијама. Tржиштa електричне енергије традиционално функционишу по B2B моделу електронског пословања где се пословање врши искључиво између произвођача и оператора тржишта. Дерегулација отвара нове могућности пословања за тржишта електричне енергије, претежно за домаћинства чијом се инклузијом у великој мери може повећати флексибилност и ефикасност механизма балансирања и целокупна стабилност електроенергетске мреже. Пословни модел предложен у овој дисертацији прилагођен је пословном окружењу и регулативи у Републици Србији. Предложена техничка спецификација модела састоји се од дистрибуиране инфраструктуре за повезивање и координацију великог броја корисничких IoT уређаја. За прикупљање, анализу и управљање подацима у реалном времену користе се аналитичке методе и софтверски алати базирани на пословној интелигенцији. Предност предложеног модела је у могућности примене на тржиштима електричне енергије која су у развоју, ниским иницијалним инвестицијама и интеграцији са smart grid технологијама. У дисертацији су приказани истраживање и анализа спремности потрошача и учесника на тржишту, за примену предложеног модела

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference