The Oil and Gas (O&G) Industry has been one of the most environmentally questioned sectors in the lastdecades, where the management of the resources and impact over natural life has been severelycriticized. There are many adverse effects of the activities around the O&G business, from which theconsumption of energy and the emissions of Greenhouse Gases (GHG) stand out to be one of the mostimportant aspects to mitigate. This project studies the actual EnMS in E&P and develops measures of improvement using establishedmanagement tools in the division, applying the principles of the ISO 50001 Standard, to include energysavings and GHG emissions mitigation in the lifecycle of Repsol’s E&P operated assets. The main focuslands over three core elements: the Integrated Project Management platform for new projects, the EnergyPlanning follow-up applications, and the implementation of relevant energy audit outlines.

Smart Grid has emerged a very important concept in modern power systems. The integration of different loads such as residential, commercial and industrial into the smart grid and their optimal operation has a significant effect on the system's reliability, stability, peak power demand and energy price. This work presents the mathematical modeling of a Centralized Temperature Control System (CTCS) of a Multi-Unit Residential Building (MURB) and its optimal operation considering electricity prices and weather variations. The model considers comfort levels, preference settings and activity of residents in different units of the building to determine the optimal operation schedules of the CTCS, minimizing its total energy consumption cost. Multi-objective operation of the MURB is also investigated when residents in different units have conflicting interests, and the impact of such conflicting preferences on the operation of CTCS is analyzed. A case-study on optimal energy management of a single unit house considering net-metering is also presented. The proposed CTCS model is a Mixed Integer Non Linear Programing (MINLP) model, where some of the constraints are linearized to reduce the computational complexity arising from the non-linearity, for real-time applications. The model is studied for various customers' preferences using a realistic MURB model. Simulation results show that significant cost savings can be achieved using the proposed mathematical model.

1ST Otokon, a Pretoria based company delivering energy management systems to the industrial and utility market segments, has shown steady growth since its inception 15 years ago. However, after ailing financial results, all aspects of the business were interrogated. It was doubted whether its energy management system (EMS) offering, ecWIN, was fulfilling the needs of the industry. Therefore this study was needed to identify new technology which could improve the effectiveness of ecWIN. After doing a thorough literature study on ecWIN, its competitors and the technologies currently utilised, the product was mapped to various technology management models. Deficiencies in the current software development environment were identified, including a lack of manpower and old software development tools. The empirical study entailed determining the effectiveness of the product through a user survey in the form of a questionnaire. Certain problem areas (e.g. insufficient software testing and a lack of documentation on advanced features) were identified by this survey. The numerous complaints about the slowness of certain reports and lack in user-friendliness were also highlighted. Also forming part of the literature and empirical study respectively, were the identification and evaluation of new technologies not yet utilised in the ecWIN sphere. Taking a holistic view of all this information, recommendations were made on how to improve the effectiveness of ecWIN. This was presented in terms of three dimensions: • Upgrade the current infrastructure over the next 12 months, mainly with new software development tools such as Centura Team Developer 2005, Crystal Reports, etc. • Improve the cost-effectiveness of ecWIN during 2006 and 2007, typically by utilising GPRS, MMS, WiFi and BlueTooth to retrieve information from meters. • Utilise a new business model (mainly centred on the cost-effectiveness dimension together with Linux and MySQL) which could allow the company to directly compete with other firms, even in the commercial and residential markets. A fourth dimension, consisting of technologies that should not be considered for integration with ecWIN at this stage, was also identified (e.g. IPv6, XHTML and Visual Studio .NET). In a world with rapidly changing technology, this study should not be a once-off process, but should be undertaken regularly to ascertain that the effectiveness of 1ST Otokon's EMS offering is constantly improved through the identification of new technology. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2005.

1ST Otokon, a Pretoria based company delivering energy management systems to the industrial and utility market segments, has shown steady growth since its inception 15 years ago. However, after ailing financial results, all aspects of the business were interrogated. It was doubted whether its energy management system (EMS) offering, ecWIN, was fulfilling the needs of the industry. Therefore this study was needed to identify new technology which could improve the effectiveness of ecWIN. After doing a thorough literature study on ecWIN, its competitors and the technologies currently utilised, the product was mapped to various technology management models. Deficiencies in the current software development environment were identified, including a lack of manpower and old software development tools. The empirical study entailed determining the effectiveness of the product through a user survey in the form of a questionnaire. Certain problem areas (e.g. insufficient software testing and a lack of documentation on advanced features) were identified by this survey. The numerous complaints about the slowness of certain reports and lack in user-friendliness were also highlighted. Also forming part of the literature and empirical study respectively, were the identification and evaluation of new technologies not yet utilised in the ecWIN sphere. Taking a holistic view of all this information, recommendations were made on how to improve the effectiveness of ecWIN. This was presented in terms of three dimensions: • Upgrade the current infrastructure over the next 12 months, mainly with new software development tools such as Centura Team Developer 2005, Crystal Reports, etc. • Improve the cost-effectiveness of ecWIN during 2006 and 2007, typically by utilising GPRS, MMS, WiFi and BlueTooth to retrieve information from meters. • Utilise a new business model (mainly centred on the cost-effectiveness dimension together with Linux and MySQL) which could allow the company to directly compete with other firms, even in the commercial and residential markets. A fourth dimension, consisting of technologies that should not be considered for integration with ecWIN at this stage, was also identified (e.g. IPv6, XHTML and Visual Studio .NET). In a world with rapidly changing technology, this study should not be a once-off process, but should be undertaken regularly to ascertain that the effectiveness of 1ST Otokon's EMS offering is constantly improved through the identification of new technology. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2005.

Buildings are responsible for a significant portion of energy consumption worldwide. Intelligent buildings have been devised as a potential solution, where energy consumption and building use are harmonised. At the heart of the intelligent building is the building energy management system (BEMS), the central platform which manages and coordinates all the building monitoring and control subsystems, such as heating and lighting loads. There is often a disconnect between the BEMS and the building it is installed in, leading to inefficient operation, due to incongruous commissioning of sensors and control systems. In these cases, the BEMS has a lack of knowledge of the building form and function, requiring further complex optimisation, to facilitate efficient all year round operation. Flawed BEMS configurations can then lead to ‘sick buildings’. Recently, building energy performance simulation (BEPS) has been viewed as a conceptual solution to assist in efficient building control. Building energy simulation models offer a virtual environment to test many scenarios of BEMS operation strategies and the ability to quickly evaluate their effects on energy consumption and occupant comfort. Challenges include having an accurate building model, but recent advances in building information modelling (BIM) offer the chance to leverage existing building data, which can be translated into a form understood by the building simulator. This study will address these challenges, by developing and integrating a BEMS, with a BIM for BEPS assisted predictive control, and assessing the outcome and potential of the integration.

Practicing engineers need an integrated building, HVAC and control simulation tool for optimum HVAC design and retrofit. Various tools are available to the researchers, but these are not appropriate for the consulting engineer. To provide the engineer with a tool which can be used for typical HVAC projects, new models for building, HVAC and control simulation are introduced and integrated in a user-friendly, quick-to-use tool. The new thermal model for buildings is based on a transfer matrix description of the heat transfer through the building shell. It makes provision for the various heat flow paths that make up the overall heat flow through the building structure. The model has been extensively verified with one hundred and three case studies. These case studies were conducted on a variety of buildings, ranging from a 4m2 bathroom, to a 7755 m2 factory building. Eight of the case studies were conducted independently in the Negev Desert in Israel. The thermal model is also used in a program that was custom-made for the AGREMENT Board (certification board for the thermal performance of new low-cost housing projects). Extensions to the standard tool were introduced to predict the potential for condensation on the various surfaces. Standard user patterns were incorporated in the program so that all the buildings are evaluated on the same basis. In the second part of this study the implementation of integrated simulation is discussed. A solution algorithm, based on the Tarjan depth first-search algorithm, was implemented. This ensures that the minimum number of variables are identified. A quasi-Newton solution algorithm is used to solve the resultant simultaneous equations. Various extensions to the HVAC and control models and simulation originally suggested by Rousseau [1] were implemented. Firstly, the steady-state models were extended by using a simplified time-constant approach to emulate the dynamic response of the equipment. Secondly, a C02 model for the building zone was implemented. Thirdly, the partload performance of particular equipment was implemented. Further extensions to the simulation tool were implemented so that energy management strategies could be simulated. A detailed discussion of the implications of the energy management systems was given and the benefits of using these strategies were clearly illustrated, in this study. Finally, the simulation tool was verified by three case studies. The buildings used for the verification ranged from a five-storeyed office and laboratory building, to a domestic dwelling. The energy consumption and the dynamics of the HVAC systems could be predicted sufficiently accurately to warrant the use of the tool for future building retrofit studies / Thesis (PhD)--University of Pretoria, 1997. / gm2014 / Mechanical and Aeronautical Engineering / unrestricted

The accurate and reliable estimation of the State-of-Charge (SOC) and State-of-Health (SOH) of Li-ion batteries is paramount to the safe and reliable operation of any electrified vehicle. Not only is accuracy and reliability necessary, but these estimation techniques must also be practical and intelligent since their use in real world applications can include noisy input signals, varying ambient conditions and incomplete or partial sequences of measured battery data. To that end, a novel framework, utilizing deep learning techniques, is considered whereby battery modelling and state estimation are performed in a single unified step. For SOC estimation, two different deep learning techniques are used with experimental data. These include a Recurrent Neural Network with Long Short-Term Memory (LSTM-RNN) and a Deep Feedforward Neural Network (DNN); each one possessing its own set of advantages. The LSTM-RNN achieves a Mean Absolute Error (MAE) of 0.57% over a fixed ambient temperature and a MAE of 1.61% over a dataset with ambient temperatures increasing from 10°C to 25°C. The DNN algorithm, on the other hand, achieves a MAE of 1.10% over a 25°C dataset while, at -20°C, a MAE of 2.17% is obtained. A Convolutional Neural Network (CNN), which has the advantage of shared weights, is used with randomized battery usage data to map raw battery measurements directly to an estimated SOH value. Using this strategy, average errors of below 1% are obtained when using fixed reference charge profiles. To further increase the practicality of this algorithm, the CNN is trained and validated over partial reference charge curves. SOH is estimated with a partial reference profile with the SOC ranging from 60% to 95% and achieves a MAE of 0.81%. A smaller SOC range is then used where the partial charge profile spans a SOC of 85% to 95% and a MAE of 1.60% is obtained. Finally, a fused convolutional recurrent neural network (CNN-RNN) is used to perform combined SOC and SOH estimation over constant charge profiles. This is performed by feeding the estimated SOH from the CNN into a LSTM-RNN, which, in turn, estimates SOC with a MAE of less than 0.5% over the lifetime of the battery. / Thesis / Doctor of Philosophy (PhD)

The contributions of the research are (a) an infrastructure of data acquisition systems that provides the necessary information for an automated EMS system enabling autonomous distributed state estimation, model validation, simplified protection, and seamless integration of other EMS applications, (b) an object-oriented, interoperable, and unified component model that can be seamlessly integrated with a variety of applications of the EMS, (c) a distributed dynamic state estimator (DDSE) based on the proposed data acquisition system and the object-oriented, interoperable, and unified component model, (d) a physically-based synchronous machine model, which is expressed in terms of the actual self and mutual inductances of the synchronous machine windings as a function of rotor position, for the purpose of synchronous machine parameters identification, and (e) a robust and highly efficient algorithm for the optimal power flow (OPF) problem, one of the most important applications of the EMS, based on the validated states and models of the power system provided by the proposed DDSE.

This thesis presents the design and implementation of control strategies for building energy management systems (BEMS). The controllers considered include the multi PI-loop controllers, state-space designs, constrained input and output MIMO adaptive controllers, fuzzy logic solutions and genetic algorithm techniques. The control performances of the designs developed using the various methods based on aspects such as regulation errors squared, energy consumptions and the settling periods are investigated for different designs. The aim of the control strategy is to regulate the room temperature and the humidity to required comfort levels. In this study the building system under study is a 3 input/ 2 output system subject to external disturbances/effects. The three inputs are heating, cooling and humidification, and the 2 outputs are room air temperature and relative humidity. The external disturbances consist of climatic effects and other stochastic influences. The study is carried out within a simulation environment using the mathematical model of the test room at Loughborough University and the designed control solutions are verified through experimental trials using the full-scale BMS facility at the University of Bradford.

As open access market principles are applied to power systems, significant changes are happening in their planning, operation and control. In the emerging marketplace, systems are operating under higher loading conditions as markets focus greater attention to operating costs than stability and security margins. Since operating stability is a basic requirement for any power system, there is need for newer tools to ensure stability and security margins being strictly enforced in the competitive marketplace. This dissertation investigates issues associated with incorporating voltage security into the unbundled operating environment of electricity markets. It includes addressing voltage security in the monitoring, operational and planning horizons of restructured power system. This dissertation presents a new decomposition procedure to estimate voltage security usage by transactions. The procedure follows physical law and uses an index that can be monitored knowing the state of the system. The expression derived is based on composite market coordination models that have both PoolCo and OpCo transactions, in a shared stressed transmission grid. Our procedure is able to equitably distinguish the impacts of individual transactions on voltage stability, at load buses, in a simple and fast manner. This dissertation formulates a new voltage stability constrained optimal power flow (VSCOPF) using a simple voltage security index. In modern planning, composite power system reliability analysis that encompasses both adequacy and security issues is being developed. We have illustrated the applicability of our VSCOPF into composite reliability analysis. This dissertation also delves into the various applications of voltage security index. Increasingly, FACT devices are being used in restructured markets to mitigate a variety of operational problems. Their control effects on voltage security would be demonstrated using our VSCOPF procedure. Further, this dissertation investigates the application of steady state voltage stability index to detect potential dynamic voltage collapse. Finally, this dissertation examines developments in representation, standardization, communication and exchange of power system data. Power system data is the key input to all analytical engines for system operation, monitoring and control. Data exchange and dissemination could impact voltage security evaluation and therefore needs to be critically examined.