Strategies for Reducing Energy Consumption in a Student Cafeteria in a Hot-Humid Climate: A Case Study

Increasing attention is being given to energy consumption and potential for energy savings in public buildings in order to improve energy performance. Due to their size and functional requirements, public buildings especially cafeteria facilities tend to consume a significant amount of energy. Furthermore, due to their operational characteristics and construction pattern, unnecessary energy is likely to be used for maintaining acceptable indoor environmental quality. In this study, a student cafeteria at King Fahd University of Petroleum and Minerals, Saudi Arabia, was selected for the assessment of its energy performance and potential energy conservation opportunities. Energy simulation software Visual DOE 4.1 was used to develop an energy performance model for assessing various energy conservation measures pertinent to the building envelope and HVAC system design. Data required for setting up the model were gathered through simple energy audits. The architectural and mechanical drawings and the history of electrical consumption were collected. Various energy conservation strategies were then implemented including standards, single and combined energy conservation measures. These measures resulted in a combined design saving of 27.4%, the HVAC system saving 10.6%, implementation of standards saving about 16.7%, lighting 6.6%, equipment 2.6%, insulation 2.5% and glazing 1.4%. Based on these results, it is apparent that there is a significant potential for improving energy performance and justification to employ the suggested measures for achieving substantial energy savings and minimize energy consumption

Modeling and Managing Engineering Changes in a Complex Product Development Process

Today\u27s hyper-competitive worldwide market, turbulent environment, demanding customers, and diverse technological advancements force any corporations who develop new products to look into all the possible areas of improvement in the entire product lifecycle management process. One of the areas that both scholars and practitioners have overlooked in the past is Engineering Change Management (ECM). The vision behind this dissertation is to ultimately bridge this gap by identifying main characteristics of a New Product Development (NPD) process that are potentially associated with the occurrence and magnitude of iterations and Engineering Changes (ECs), developing means to quantify these characteristics as well as the interrelationships between them in a computer simulation model, testing the effects of different parameter settings and various coordination policies on project performance, and finally gaining operational insights considering all relevant EC impacts. The causes for four major ECM problems (occurrence of ECs, long EC lead time, high EC cost, and occurrence frequency of iterations and ECs), are first discussed diagrammatically and qualitatively. Factors that contribute to particular system behavior patterns and the causal links between them are identified through the exploratory construction of causal/causal-loop diagrams. To further understand the nature of NPD/ECM problems and verify the key assumptions made in the conceptual causal framework, three field survey studies were conducted in the summer of 2010 and 2011. Information and data were collected to assess the current practice in automobile and information technology industries where EC problems are commonly encountered. ased upon the intuitive understanding gained from these two preparation work, a Discrete Event Simulation (DES) model is proposed. In addition to combining essential project features, such as concurrent engineering, cross functional integration, resource constraints, etc., it is distinct from existing research by introducing the capability of differentiating and characterizing various levels of uncertainties (activity uncertainty, solution uncertainty, and environmental uncertainty) that are dynamically associated with an NPD project and consequently result in stochastic occurrence of NPD iterations and ECs of two different types (emergent ECs and initiated ECs) as the project unfolds. Moreover, feedback-loop relationships among model variables are included in the DES model to enable more accurate prediction of dynamic work flow. Using a numerical example, different project-related model features (e.g., learning curve effects, rework likelihood, and level of dependency of product configuration) and coordination policies (e.g., overlapping strategy, rework review strategy, IEC batching policy, and resource allocation policy) are tested and analyzed in detail concerning three major performance indicators: lead time, cost, and quality, based on which decision-making suggestions regarding EC impacts are drawn from a systems perspective. Simulation results confirm that the nonlinear dynamics of interactions between NPD and ECM plays a vital role in determining the final performance of development efforts

Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems

This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book

Accurate Battery Modelling for Control Design and Economic Analysis of Lithium-ion Battery Energy Storage Systems in Smart Grid

Adoption of lithium-ion battery energy storage systems (Li-ion BESSs) as a flexible energy source (FES) has been rapid, particularly for active network management (ANM) schemes to facilitate better utilisation of inverter based renewable energy sources (RES) in power systems. However, Li-ion BESSs display highly nonlinear performance characteristics, which are based on parameters such as state of charge (SOC), temperature, depth of discharge (DOD), charge/discharge rate (C-rate), and battery-aging conditions. Therefore, it is important to include the dynamic nature of battery characteristics in the process of the design and development of battery system controllers for grid applications and for techno-economic studies analyzing the BESS economic profitability. This thesis focuses on improving the design and development of Li-ion BESS controllers for ANM applications by utilizing accurate battery performance models based on the second-order equivalent-circuit dynamic battery modelling technique, which considers the SOC, C-rate, temperature, and aging as its performance affecting parameters. The proposed ANM scheme has been designed to control and manage the power system parameters within the limits defined by grid codes by managing the transients introduced due to the intermittence of RESs and increasing the RES penetration at the same time. The validation of the ANM scheme and the effectiveness of controllers that manage the flexibilities in the power system, which are a part of the energy management system (EMS) of ANM, has been validated with the help of simulation studies based on an existing real-life smart grid pilot in Finland, Sundom Smart Grid (SSG). The studies were performed with offline (short-term transient-stability analysis) and real-time (long-term transient analysis) simulations. In long-term simulation studies, the effect of battery aging has also been considered as part of the Li-ion BESS controller design; thus, its impact on the overall power system operation can be analyzed. For this purpose, aging models that can determine the evolving peak power characteristics associated with aging have been established. Such aging models are included in the control loop of the Li-ion BESS controller design, which can help analyse battery aging impacts on the power system control and stability. These analyses have been validated using various use cases. Finally, the impact of battery aging on economic profitability has been studied by including battery-aging models in techno-economic studies.Aurinkosähköjärjestelmien ja tuulivoiman laajamittainen integrointi sähkövoimajärjestelmän eri jännitetasoille on lisääntynyt nopeasti. Uusiutuva energia on kuitenkin luonteeltaan vaihtelevaa, joka voi aiheuttaa nopeita muutoksia taajuudessa ja jännitteessä. Näiden vaihteluiden hallintaan tarvitaan erilaisia joustavia energiaresursseja, kuten energiavarastoja, sekä niiden tehokkaan hyödyntämisen mahdollistaviea älykkäitä ja aktiivisia hallinta- ja ohjausjärjestelmiä. Litiumioniakkuihin pohjautuvien invertteriliitäntäisten energian varastointijärjestelmien käyttö joustoresursseina aktiiviseen verkonhallintaan niiden pätö- ja loistehon ohjauksen avulla on lisääntynyt nopeasti johtuen niiden kustannusten laskusta, modulaarisuudesta ja teknisistä ominaisuuksista. Litiumioniakuilla on erittäin epälineaariset ominaisuudet joita kuvaavat parametrit ovat esimerkiksi lataustila, lämpötila, purkaussyvyys, lataus/ purkausnopeus ja akun ikääntyminen. Akkujen ominaisuuksien dynaaminen luonne onkin tärkeää huomioida myös akkujen sähköverkkoratkaisuihin liittyvien säätöjärjestelmien kehittämisessä sekä teknis-taloudellisissa kannattavuusanalyyseissa. Tämä väitöstutkimus keskittyy ensisijaisesti aktiiviseen verkonhallintaan käytettävien litiumioniakkujen säätöratkaisuiden parantamiseen hyödyntämällä tarkkoja, dynaamisia akun suorituskykymalleja, jotka perustuvat toisen asteen ekvivalenttipiirien akkumallinnustekniikkaan, jossa otetaan huomioon lataustila, lataus/purkausnopeus ja lämpötila. Työssä kehitetyn aktiivisen verkonhallintajärjestelmän avulla tehtävät akun pätö- ja loistehon ohjausperiaatteet on validoitu laajamittaisten simulointien avulla, esimerkiksi paikallista älyverkkopilottia Sundom Smart Gridiä simuloimalla. Simuloinnit tehtiin sekä lyhyen aikavälin offline-simulaatio-ohjelmistoilla että pitkän aikavälin simulaatioilla hyödyntäen reaaliaikasimulointilaitteistoa. Pitkän aikavälin simulaatioissa akun ikääntymisen vaikutus otettiin huomioon litiumioniakun ohjauksen suunnittelussa jotta sen vaikutusta sähköjärjestelmän kokonaistoimintaan voitiin analysoida. Tätä tarkoitusta varten luotiin akun ikääntymismalleja, joilla on mahdollista määrittää akun huipputehon muutos sen ikääntyessä. Akun huipputehon muutos taas vaikuttaa sen hyödynnettävyyteen erilaisten pätötehon ohjaukseen perustuvien joustopalveluiden tarjoamiseen liittyen. Lisäksi väitöstutkimuksessa tarkasteltiin akkujen ikääntymisen vaikutusta niiden taloudelliseen kannattavuuteen sisällyttämällä akkujen ikääntymismalleja teknis-taloudellisiin tarkasteluihin.fi=vertaisarvioitu|en=peerReviewed