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This paper presents the methodological approach and findings of a simulation study of advanced energy conservation, generation and management technologies applied to two case study dwellings in the UK, so as to achieve net zero energy (NZE) target that includes a reduction of net regulated energy (HVAC) to 0 kWh/m 2 per year and energy generation of at least 50 kWh/m 2 per year. The performance of the dwellings are also tested for a change in energy use and risk of summertime overheating in future climates in the short (2030s), medium (2050s) and long term (2080s). The findings indicate that to meet the NZE targets, regulated loads need to reduce by about half (over current Building Regulations) with community (rather than building-level) renewables playing a major role. It is also found that the NZE targets, given current regulations, are not particularly difficult to achieve in design with regard to energy efficiency but are highly expectant with regard to renewable energy. Further, summertime overheating is projected to be a risk for net zero energy dwellings by the 2050s. Despite this the regulated energy use of both dwellings is projected to reduce by 11 kWh/m 2 /yr, accompanied by a small increase in renewable generation (2 kWh/m 2 /yr). [ABSTRACT FROM AUTHOR]

This paper proposes a novel Case Based Reasoning (CBR) application for intelligent management of energy resources in residential buildings. The proposed CBR approach enables analyzing the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. The innovations of the proposed CBR model are the application of the k -Nearest Neighbors algorithm (k-NN) clustering algorithm to identify similar past cases, the adaptation of Particle Swarm Optimization (PSO) meta-heuristic optimization method to optimize the choice of the variables that characterize each case, and the development of expert systems to adapt and refine the final solution. A case study is presented, which considers a knowledge base containing a set of scenarios obtained from the consumption of a residential building. In order to provide a response for a new case, the proposed CBR application selects the most similar cases and elaborates a response, which is provided to the SCADA House Intelligent Management (SHIM) system as input data. SHIM uses this specification to determine the loads that should be reduced in order to fulfill the reduction suggested by the CBR approach. Results show that the proposed approach is capable of suggesting the most adequate levels of reduction for the considered house, without compromising the comfort of the users. [ABSTRACT FROM AUTHOR]

Ubiquitous modernization of building energy and management systems brings tendencies for an effective integration of renewables in buildings. This article shows how solar energy can be in charge of energy savings within a building by integration of solar systems with Trombe wall. Numerical calculations of Trombe wall thermal resistance and its performances in comparison with a common wall are considered. Additionally, energy-efficiency gaining by a combination of PV modules and Trombe wall, using simulations by SAM (System Advisor Model) software is discussed. PV module parameters and their impact on its electricity production are observed and analyzed. The PV module parameters, analyzed in the paper are: the tilt angle α of PV modules, incident angle β of direct sunrays on PV modules, normal beam irradiation N and PV cells operating temperature. With bigger incident angle β of direct sunlight on PV modules, the normal beam irradiation is smaller, which brings less electricity production. The impact of PV module operating temperature can be neglected in comparison with the impact of tilt angle on PV module electricity production. The optimal tilt angle of PV modules for generating maximum annual electricity is around latitude angle. It varies with normal beam irradiation to achieve the maximum monthly electricity production. [ABSTRACT FROM AUTHOR]

Heating ventilation and air conditioning (HVAC) systems represent an important amount of the total energy use in office buildings, accounting for near 30%. Moreover, in countries affected by extreme climates HVAC systems’ contribution to energy demand increases up to 50%. Therefore, the automation of energy efficient strategies that act on the Building Energy Management System (BEMS) in order to improve building energy use becomes increasingly relevant. This paper delves into the devising of a novel HVAC optimization framework, coined as Next24h-Energy, which consists on a two-way communication system, an enhanced database management system and a set of machine learning algorithms based on random forest (RF) regression techniques mainly focused on providing an energy-efficient predictive control of the HVAC system. Therefore, the proposed framework achieves optimal HVAC ON/OFF and mechanical ventilation (MV) schedule operation that minimizes the energy consumption while keeps the building between a predefined indoor temperature margins. Simulation results assess the performance of the proposed Next 24 h-Energy framework at a real office building named Mikeletegi 1 (M1) in Donostia-San Sebastian (Spain) yielding to excellent results and significant energy savings by virtue of its capability of adapting the parameters that control the HVAC schedule in a daily basis without affecting user comfort conditions. Specifically, the energy reduction for the test period is estimated in 48% for the heating and 39% for the cooling consumption. [ABSTRACT FROM AUTHOR]

• An overall panorama of the school buildings in Brazil was presented. • Energy billed data and survey evidence were used to build a statistical stock model. • The Weibull distribution was the most adequate to represent the continuous variables. • kWh/student·year was more suitable than kWh/m2·year to model Brazilian school buildings stock. • Thermal performance is an issue to be greatly improved in schools in Brazil. Understanding the actual conditions in school buildings regarding energy usage and environmental satisfaction gives way to the development of consistent building stock modelling. In the Brazilian context, a deep-rooted inefficient structure of energy management implies a lack of mapping the actual conditions of the public schools. Therefore, this paper aimed to assess the actual energy performance of school buildings in Brazil. This paper innovates by integrating questionnaire responses and billed energy data to allow the construction of an evidence-based stock model through a statistical approach, which was never performed for the Brazilian building stock. Moreover, the association of energy use intensity (EUI) with the core aspects of building characteristics, occupancy, environmental satisfaction and necessary improvements mapped the relevance of such aspects in energy usage patterns. Additionally, a discussion of the EUI indicators was addressed. Results showed an unprecedented broad panorama of the school building stock in Brazil and its main features. In terms of statistical analysis, the Weibull distribution was appropriate for representing the continuous variables of the stock. The EUI as a function of the number of students was more suitable than the floor-plan area to achieve a reliable energy performance analysis. Several tests were performed to assess if the energy management, environmental satisfaction and maintenance practices impacted the EUI or not. Finally, the main conclusion was that the stock model obtained was simple and fit the energy management structure in the Brazilian scenario. [ABSTRACT FROM AUTHOR]

Non-residential buildings like healthcare ones contribute to energy consumption and cause a negative environmental impact. This is mainly due to the age of the buildings, their poor level of energy efficiency and the implementation of only a basic maintenance plan. Owing to the very limited budget available for public administrators, Energy Performance Contracting (EPC), that entails the involvement of an Energy Service Company (ESCo), can provide the entire or part of the capital needed for investments aimed at progressively increasing energy efficiency over their service life. In this paper, three acute hospitals and two community clinics built in Italy are analysed, in order to assess the economic feasibility of several energy renovation actions that can be included within EPC contracts. To this purpose, the outcomes of energy audits carried out in 2014 about these buildings are reported, which involved analyses of consumption measured over the previous three years and assessment of use profiles for the development of models to break down the overall consumption and to estimate potential savings. Diverse improvement strategies were assessed, consisting in either isolated or combined renovation actions and tested on the five buildings, whose comparison was carried out in terms of energy saving, pollution reduction and economic feasibility. As a result, the best combined renovation actions per each hospital were recommended, that included – but were not limited to – the improvement of the control and regulation of existing sub-systems without replacement, partial replacement of other sub-systems and integration of renewables. Finally, each scenario was evaluated through the payback period and other economic performance indexes in order to assess the feasibility of the EPC framework when applied to this case study. [ABSTRACT FROM AUTHOR]

University campuses can be considered as small towns due to their size, number of users and mixed and complex activities, including numerous actions usually met in urban environments. The energy and environmental impact of universities could be considerably reduced by applying organizational, technological and energy optimization measures. The aim of the present paper is to present an efficient web based energy management system for Campuses which manages in an energy efficient way the Campus buildings and spaces of public use, monitors the energy load and performs energy analysis per building and for the Campus as a whole, as well as it interacts with each building’s BEMS and each user through questionnaires, e-mails and forms. The existing Campus IP infrastructure is exploited by using sensor networks, where nodes communicate their information using Web services, allowing direct integration in modern IT systems. To guarantee the system scalability and respect consolidated and diffused standards, the logical/architectural level of the whole Campus Energy Management System is linked with the existing infrastructure based on Internet Protocol (IP). The overall installation is tested via on line questionnaires to the building users showing a significant increase of the occupants’ satisfaction. Finally, the energy efficiency achieved by the proposed system is almost 20%. [ABSTRACT FROM AUTHOR]

This paper provides a comparative study of state-of-the-art means of predicting occupancy for smart heating control applications. We focus on approaches that predict the occupancy state of a home using occupancy schedules – that is, past records of the occupancy state. We ran our analysis on actual occupancy schedules covering several months for 45 homes. Our results show that state-of-the-art, schedule-based occupancy prediction algorithms achieve an overall prediction accuracy of over 80%. We also show that the performance of these algorithms is close to the theoretical upper bound expressed by the predictability of the input schedules. Building upon these results, we used ISO 13790-standard modelling techniques to analyse the energy savings that can be achieved by smart heating controllers that use occupancy predictors. Furthermore, we investigated the trade-off between achievable savings (typically 6–17% on average) and the risk of comfort loss for household residents. [ABSTRACT FROM AUTHOR]

[Display omitted] • Distributed real-time optimal control was developed for typical HVAC systems. • Physical meaning in decomposition was enhanced in the proposed scheme. • Computation load was significantly distributed from BEMS to local computation unit. • Global convergence of the distributed optimal control was investigated. • Distributed and centralized optimal control led to similar energy performance. Real-time optimal control (RtOpt) is an efficient tool to improve the energy efficiency of heating, ventilating and air-conditioning (HVAC) systems. RtOpt is always centralized and solved entirely in building energy management systems (BEMSs). However, centralized optimization is not be an efficient solution because real-time operation data in local loops need to be sent to the central computation unit in BEMS for optimization. This paper, therefore, proposes a distributed RtOpt scheme for typical centralized HVAC systems, which uses a dual decomposition mechanism to break the centralized problem into one mater problem and several sub-problems that can be solved in parallel and independently. The mater problem is converted to a simple mean value calculation using a projected sub-gradient method, thus distributing the computation load from the central computation unit into local computation units. Unlike available decomposition schemes in literature, the proposed method considered the functionality and spatial distribution of the major components of HVAC systems, which could enhance the physical meaning and facilitate the application of the decomposition scheme. The proposed distributed RtOpt scheme was tested in case studies, with numerical analysis being used to demonstrate its potential benefits. [ABSTRACT FROM AUTHOR]

Abstract: In an increasingly constrained context with severe requirements of quality, safety and environment respect, a building-integrated photovoltaic (BIPV) involves advanced local energy management rather than photovoltaic (PV) power permanent grid injection. This paper focus on building-integrated microgrid (BIMG) design and implementation applied to BIPV system with energy storage and smart grid communication. The goal is to propose power balancing strategy with smart grid interaction, aiming at reducing grid peak consumption, avoiding undesirable grid power injection, making full use of local PV production. The energy management is carried out considering grid time-of-use tariffs, grid access limits, storage capacity, load and PV power shedding if necessary. Based on experimental platform, the results show that the system maintains stability and confirm the relevance of the proposed local energy management giving perspectives on better integration of small PV plant in power grid. [Copyright &y& Elsevier]

Abstract: Numerous studies have focused on improving energy efficiency in commercial buildings. Engineers and researchers have developed complex methods to improve energy efficiency, but buildings are often managed by non-specialised technicians who need understandable and cost-effective actions to implement in their buildings. This paper presents basic actions on which to base improvements in energy efficiency in commercial buildings in operation. Furthermore, obtained results and details of the implementation of these techniques in various buildings in the Universitat Politècnica de València are presented. [Copyright &y& Elsevier]

Abstract: This paper presents a robust strategy for online fault detection and optimal control of condenser cooling water systems. The optimal control strategy is formulated using a model-based approach, in which simplified models and a hybrid quick search (HQS) method are used to optimize the performance of the overall system by changing the settings of the local process controllers. A system level online fault detection scheme is embedded into the control system and used to monitor whether the system operates in a healthy condition. The faults considered are mainly the component performance degradations. When a fault is detected, the control system will be reconstructed to regain the control through using robust schemes. The performance of the proposed strategy is tested and evaluated against on a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the fault detection scheme is effective in identifying system performance degradations and the fault-tolerant control strategy with online fault detection and optimal control can enhance the overall system performance significantly when the operation of condenser cooling water systems suffers from performance degradations, as compared to that using optimal control only. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to present the design and installation of a fuzzy logic controller of indoor thermal and visual comfort as well as indoor air quality, using the EIB (European Installation Bus) system through interconnection with Matlab. An experimental chamber is implemented for testing and optimization of the system. The chamber which controls the indoor environment, consists of interconnected nodes (sensors and actuators) in an EIB fieldbus network infrastructure connected with a PC, through RS-232 port. Control is achieved by a fuzzy controller, which is programmed in Matlab. The interconnection between EIB and Matlab is realized via the EIB OPC server and an OPC Client for Matlab. In this way artificial intelligence control, EIB-based platforms and Matlab are interconnected in order to explore the possibilities of using advanced control techniques in energy efficient practices in real buildings. [Copyright &y& Elsevier]

The aim of this paper is to present the architecture, the algorithms and the performance results of an integrated indoor environment energy management system (IEEMS) for buildings. The buildings’ users comfort requirements are fulfilled and regulated using a fuzzy controller. The fuzzy controller’s structure is adjusted to the users’ requirements that are monitored via a smart card system. The IEEMS is installed in two buildings in Athens and in Crete, both in Greece. The energy conservation achieved by the IEEMS operation is more than 30% compared to the existing control system. [Copyright &y& Elsevier]

In the UK, heating systems in the built environment consume a substantial proportion of its total energy and are responsible for about 25% of the total carbon emission. A similar pattern is also exhibited in many other European countries. Despite the enormous effort made over the last decades to improve the energy efficiency of these heating systems, a huge potential for further energy saving still persists. This paper investigates the potential for energy saving in heating systems that can be achieved through improving boiler controls. This investigation was carried out through surveys, simulation and experimental study. Through the surveys, typical boiler control schemes widely used in current practice were identified. The performance of some systems surveyed was monitored through the survey. The data obtained is used to demonstrate the problems associated with the control of boilers in heating systems. These typical control schemes identified through surveys were studied using a simulator that had been rigorously validated. An experiment was carried out to demonstrate how the overall performance of a heating system could be improved by using a better boiler controller. The result shows that improving boiler controls can lead to up to 20% of energy saving and a significant improvement in thermal comfort. [Copyright &y& Elsevier]