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[en] Highlights: • An autoencoder-based ensemble method is developed for anomaly detection. • Autoencoders can capture the intrinsic characteristics in building energy data. • The performance of various autoencoder types and training schemes is compared. • Methods are developed for performance evaluation without using anomaly labels. • This study provides data-driven solutions to unsupervised anomaly detection. - Abstract: Practical building operations usually deviate from the designed building operational performance due to the wide existence of operating faults and improper control strategies. Great energy saving potential can be realized if inefficient or faulty operations are detected and amended in time. The vast amounts of building operational data collected by the Building Automation System have made it feasible to develop data-driven approaches to anomaly detection. Compared with supervised analytics, unsupervised anomaly detection is more practical in analyzing real-world building operational data, as anomaly labels are typically not available. Autoencoder is a very powerful method for the unsupervised learning of high-level data representations. Recent development in deep learning has endowed autoencoders with even greater capability in analyzing complex, high-dimensional and large-scale data. This study investigates the potential of autoencoders in detecting anomalies in building energy data. An autoencoder-based ensemble method is proposed while providing a comprehensive comparison on different autoencoder types and training schemes. Considering the unique learning mechanism of autoencoders, specific methods have been designed to evaluate the autoencoder performance. The research results can be used as foundation for building professionals to develop advanced tools for anomaly detection and performance benchmarking.
[en] Highlights: • An AMSS based on SA optimization is integrated with the rule-based strategy. • The proposed AMSS focusing on selecting the most suitable operating mode. • The optimization of the reference SC SOC and battery power is realized with the SA algorithm. • The proposed strategy can achieve the global energy management optimization. - Abstract: This paper proposes an adaptive mode switch strategy (AMSS) based on simulated annealing (SA) optimization of a multi-mode hybrid energy storage system (HESS) for electric vehicles. The proposed SA-AMSS is derived from a rule-based strategy to achieve the adaptive mode selection and energy management optimization. To improve the overall system efficiency of the multi-mode HESS, the state of charge (SOC) level of the supercapacitor (SC), the power level and the component efficiencies are discussed. On this basis, the objective function for the AMSS is established, focusing on selecting the most suitable mode. Furthermore, to accomplish a global energy management optimization based on the driving cycles, the SA approach is introduced into the optimizations of the reference SC SOC and battery power, rather than the direct power distribution optimization between the battery and SC. The AMSS is implemented based on the SA optimization. Simulations and experiments are presented to verify the effectiveness of the SA-AMSS for the multi-mode HESS. Results show that the SA-AMSS can not only reduce the frequency of the mode switching, but also avoid the sudden excessive power output of the battery. The SC can respond to all peak power demands and absorb all the braking energy. So the SA-AMSS is very flexible and effective, and the battery safety can be guaranteed. Compared with the rule-based strategy, the overall system efficiency of the multi-mode HESS is significantly improved.
[en] The building sector is primarily responsible for a major part of total energy consumption. The European Energy Performance of Buildings Directives (EPBD) emphasized the need to reduce the energy consumption in buildings, and put forward the rationale for developing Near to Zero Energy Buildings (NZEB). Passive and active strategies help architects to minimize the use of active HVAC systems, taking advantage of the available natural resources such as solar radiation, thermal variability and daylight. The building envelope plays a decisive role in passive and active design strategies. The ideal transparent façade would be one with optical properties, such as Solar Heat Gain Coefficient (SHGC) and Visible Transmittance (VT), that could readily adapt in response to changing climatic conditions or occupant preferences. The aim of this article consists of describing the system to maintain a small glazed pavilion located in Sofia (Bulgaria) at the desired interior temperature over a whole year. The system comprises i) the use of Water Flow Glazing facades (WFG) and Radiant Interior Walls (RIW), ii) the use of free cooling devices along with traditional heat pump connected to photo-voltaic panels and iii) the use of a new Energy Management System that collects data and acts accordingly by controlling all components. The effect of these strategies and the use of active systems, like Water Flow Glazing, are analysed by means of simulating the prototype over one year. Summer and Winter energy management strategies are discussed in order to change the SHGC value of the Water Flow Glazing and thus, reduce the required energy to maintain comfort conditions. (paper)
[en] Highlights: • Smart home energy management in summer season is considered. • Thermal and electrical performance of smart home is studied under price uncertainty. • Market price uncertainty is modeled based on information gap decision theory. • Smart appliances, battery, water tank, backup boiler and fuel cell are the equipment. - Abstract: After restructuring in the electricity industry, some concepts such as smart home and renewable energy sources improved extensively. This paper proposes information gap decision theory (IGDT) technique for robust energy management of smart home in summer season in the presence of market price fluctuation. Therefore, the proposed model is practical in a realistic model. The IGDT method contains the robustness and opportunity functions. The harmful aspect of price uncertainty is modeled by robustness function and the beneficial aspect of price uncertainty is modeled by opportunity function. The proposed IGDT-based performance optimization problem of low-energy smart home is formulated as mixed-integer non-linear programming (MINLP) and solved by General Algebraic Modeling System (GAMS) optimization software. Two scenarios as normal and smart scenarios are used to investigate the proposed model.
[en] Highlight• Analysis of the UK energy and non-energy intensive sectors firms in a real business cycle (RBC) model. We investigate the role of energy shocks during the Great Recession. We study the behaviour of the UK energy and non-energy intensive sectors firms in a real business cycle (RBC) model using unfiltered data. The model is econometrically estimated and tested by indirect inference. Output contraction during the Great Recession was largely caused by energy price and sector-specific productivity shocks, all of which are non-stationary and hence tend to dominate the sample variance decomposition. We also found that the channel by which the energy price shock reduces output in the model is via the terms of trade: these fall permanently when world energy prices increase and as substitutes for energy inputs are strictly limited there are few reactions via production channels. Therefore, there is no other way to balance the deteriorating current account than through lower domestic absorption.
[en] The re-communalization of public services is a matter of debate in Germany even though many towns are in a difficult budgetary situation but however always more often envisage a strengthening of structures of public production, notably regarding energy supply. Based on a survey performed among 159 German towns of different sizes, this note reports an analysis of objectives, stakes, reluctance, shapes and foundations of this come back to communalization.
[en] The nuclear education problem is treated as societal optimization task of nuclear energy management, with the key parameter of optimization—stakeholder awareness level. As the key principles of optimisation are chosen: a self-organization concept, the principle of the requisite variety, where as a primary source of growth of internal variety is information and knowledge. We have shown: public education, social learning and the use of mass media are efficient self-organization mechanisms, thereby forming a knowledge-creating community. Such a created knowledge could facilitate solution of key issues: a) public acceptance of novel nuclear objects, b) promotion of adequate risk perception, and c) fostering of interest to nuclear energy. Comprehensive knowledge management and informational support firstly is needed in: a) for increasing general nuclear awareness and confidence level to nuclear activities, b) personnel education and training, c) reliable staff renascence, d) public education and involvement of all stakeholder categories in decision making, e) risk management. A common approach to nuclear education should include also comprehensive research activities, thereby joining knowledge acquisition with the generation of novel advanced knowledge. (author)
[en] The Nuclear Energy Management School is proposed as a good tool to structure the experiences of industries. The importance of a short-term international education programme for gathering knowledge regarding nuclear embarkation projects is discussed in this paper. The results of evaluating education efficiency from 2013 to 2016 will also be introduced in this presentation (or poster). (author)
[en] Close mutual cooperation among nuclear-related organizations, such as government, industry and academia is extremely useful to promote Nuclear Human Resources Development (HRD). National HRD network has already been established in Japan since Nov. 20101. The network has promoted the following five discussion on (1) Elementary to High School Education (2) Nuclear Education at Universities and Colleges, (3) HRD for Working Engineers, (4) HRD to Internationalize National Human Resources, and (5) Supportive HRD Activities to newly NPP Introducing Countries successfully. Through the establishment of the network, the communication has been strongly improved so that the Japan-IAEA joint Nuclear Energy Management School can be held successfully every year. Based on the good experience with the network, Japan would like to recommend the introduction of national Nuclear HRD (N-HRD)-Network to the NPP-embarking Countries. We are interested in cooperation with IAEA for establishment of National N-HRD Network for efficient and effective N-HRD. (author)