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This dissertation proposes an Intelligent Energy Management Agent (IEMA) for parallel hybrid vehicles. A key concept adopted in the development of an IEMA is based on the premise that driving environment would affect fuel consumption and pollutant emissions, as well as the operating modes of the vehicle and the driver behavior do. IEMA incorporates a driving situation identification component whose role is to assess the driving environment, the driving style of the driver, and the operating mode (and trend) of the vehicle using long and short term statistical features of the drive cycle. This information is subsequently used by the torque distribution and charge sustenance components of IEMA to determine the power split strategy, which is shown to lead to improved fuel economy and reduced emissions.

Global climate change and the electricity supply constraints could possibly be one of the utmost strategic issues facing businesses and consumers of all sizes currently in South Africa. Energy Efficiency is the ability to produce the same output but with less energy. The implementation of Energy Efficiency strategies is pivotal in order to sustain the climatic conditions as well as mitigate the supply constraints the South African utility Eskom is experienced. The aim of this study was to reiterate the importance of energy efficiency strategies and to identify the barriers and challenges companies face towards implementing energy efficiency and energy management strategies. This dissertation identified incentives and rebate schemes available to promote energy efficiency strategies and discussed the policies and strategies the South African Government implemented towards realising the energy efficiency target of 12%.The literature review conclude with discussing best practices indentified by implementing corporate energy efficiency strategies. The level of preparedness and progress in implementing an energy management system and strategies between the different companies were assessed. The target population includes the high intensity user group (HIU), listed and SME companies in the different industry sectors in South Africa. The study concludes that there are still multiple challenges facing companies in implementing sustainable energy efficiency strategies. Although government and multiple stakeholders are initiating incentive and rebate models to promote the implementation of energy efficiency measures, industry still lacks the commitment to change their behaviour toward implementing energy management strategies. / Thesis (MBA)--North-West University, Potchefstroom Campus, 2013.

Global climate change and the electricity supply constraints could possibly be one of the utmost strategic issues facing businesses and consumers of all sizes currently in South Africa. Energy Efficiency is the ability to produce the same output but with less energy. The implementation of Energy Efficiency strategies is pivotal in order to sustain the climatic conditions as well as mitigate the supply constraints the South African utility Eskom is experienced. The aim of this study was to reiterate the importance of energy efficiency strategies and to identify the barriers and challenges companies face towards implementing energy efficiency and energy management strategies. This dissertation identified incentives and rebate schemes available to promote energy efficiency strategies and discussed the policies and strategies the South African Government implemented towards realising the energy efficiency target of 12%.The literature review conclude with discussing best practices indentified by implementing corporate energy efficiency strategies. The level of preparedness and progress in implementing an energy management system and strategies between the different companies were assessed. The target population includes the high intensity user group (HIU), listed and SME companies in the different industry sectors in South Africa. The study concludes that there are still multiple challenges facing companies in implementing sustainable energy efficiency strategies. Although government and multiple stakeholders are initiating incentive and rebate models to promote the implementation of energy efficiency measures, industry still lacks the commitment to change their behaviour toward implementing energy management strategies. / Thesis (MBA)--North-West University, Potchefstroom Campus, 2013.

thesis submitted in partial fulfilment of the requirements for the degree: Master of Technology: Electrical Engineering in the Faculty of Electrical Engineering at the Cape Peninsula University of Technology / Rural communities are often unable to access electrical energy due to their distant location away from the national grid. Renewable energy sources (RESs) make it possible to provide electrical energy to these isolated areas. Sustainable generation is possible at a local level and is not dependant on connection to a national power grid. Microgrids are small scale, stand-alone electricity networks that harness energy at its geographical location, from natural resources. These small scale power grids are either connected to a national grid or operate separately by obtaining their power from an RES. Microgrids are becoming increasingly popular because they can provide electricity, independently of the national grid. The size of microgrid systems are dependent on the amount of energy that needs to be drawn and the amount of energy that has to be stored. Mechanical and electrical system component sizes become bigger due to increased operational energy requirements. Increases in component sizes are required on growing power networks when higher current levels are drawn. Energy management of microgrids must thus be introduced to prevent overloading the power grid network and to extend the operational life of the storage batteries. Energy management systems consist of different components which are seen as operational units. Operational units are responsible for measurement, communication, decision–making and power supply switching control, to manipulate the power output to meet the energy demands. Due to the increasing popularity of DC home appliances, it is important to explore the possibility of keeping these microgrids on a DC voltage basis. Electrical generation equipment such as photovoltaic panels can be used to generate DC at designed voltage levels. The energy management system connects the user loads and generation units together to form the microgrid. The aim of this study was to carry out the design of an agent–based energy management system for rural and under-developed communities. It investigates how the control of the output of the energy management system can be carried out to service the loads. The simulations were done using the following software packages: Simulink, Matlab, and SimPowerSystems. PV sources, energy management system (EMS) and user load parameters are varied in the simulation software to observe how the control algorithm executes load shedding. A stokvel-type charge share concept is dealt with where the state-of-charge (SOC) of batteries and user consumption will determine how grid loads are managed. Load shedding within the grid is executed by monitoring energy flow and calculating how much energy is allowed to be used by each consumer. The energy management system is programmed to always provide the largest amount of energy to the consumer with the lowest energy consumption for each day. The batteries store surplus electrical energy during the day. Load shedding starts at 18:00 each day. Users will be disconnected from the grid whenever their allotted energy capacity were depleted.

Indiana University-Purdue University Indianapolis (IUPUI) / Heat, cooling, and ventilation units are major energy consumers for commercial buildings, they can consume as much as 50% of the total annual power usage of a building. Coherent management of an air handling system’s energy is a key factor of reducing the energy costs and CO2 emissions that are associated with the demand for ventilating and conditioning the air in a building. The issue is that buildings are frequently over ventilated as a full assessment of the air handling unit (AHU) data is not evaluated by building operators. According to ASHRAE standards there are three key parameters that control indoor air quality (IAQ); these are the temperature, humidity, and CO2. Commonly occupancy setpoints implemented by building operators are focused on temperature and humidity control while neglecting the CO2 levels and their impact. While this may seem insignificant additional data proves to be important and can assist with energy management. Additionally, it can develop awareness of implementable procedures which conserve energy. Furthermore, data is not monitored in regard to the continuous assessment of the energy consumption with respect to analysis of opportunities to implement energy saving control strategies. By using these standards as a guide an AHUs energy can be managed more effectively by measuring the data and assessing the outputs compared to the standard. Previous research has shown that up to 75% savings for the ventilation fan energy is achievable when taking into account ASHRAE ventilation standards and controlling outside air ventilation, however, this research has omitted investigating the savings for other energy consumers associated with AHU’s operation. In order to assess the demand, it is required that the CO2 levels of the occupied zones be measured, and the outdoor air ventilation rate be adjusted based on real-time demand. The goal of the research is to assess the number of CO¬2 sensors needed to accurately measure demand-based needs for ventilation and determine an algorithm that will help building operators assess the energy savings by implementing demand-controlled ventilation (DCV) procedures. The scope of this research is to identify what sensors at minimum are required to collect the most pertinent data for implementation of a comprehensive energy saving algorithms and assess the impact on energy consumption of AHUs when demand-controlled ventilation procedures are implemented.

The efficiency, security and resiliency are very important factors for the operation of a distribution power system. Taking into account customer demand and energy resource constraints, electric utilities not only need to provide reliable services but also need to operate a power grid as efficiently as possible. The objective of this dissertation is to design, develop and deploy the Multi-Agent Systems (MAS) - together with control algorithms - that enable demand response (DR) implementation at the customer level, focusing on both residential and commercial customers. For residential applications, the main objective is to propose an approach for a smart distribution transformer management. The DR objective at a distribution transformer is to ensure that the instantaneous power demand at a distribution transformer is kept below a certain demand limit while impacts of demand restrike are minimized. The DR objectives at residential homes are to secure critical loads, mitigate occupant comfort violation, and minimize appliance run-time after a DR event. For commercial applications, the goal is to propose a MAS architecture and platform that help facilitate the implementation of a Critical Peak Pricing (CPP) program. Main objectives of the proposed DR algorithm are to minimize power demand and energy consumption during a period that a CPP event is called out, to minimize occupant comfort violation, to minimize impacts of demand restrike after a CPP event, as well as to control the device operation to avoid restrikes. Overall, this study provides an insight into the design and implementation of MAS, together with associated control algorithms for DR implementation in smart buildings. The proposed approaches can serve as alternative solutions to the current practices of electric utilities to engage end-use customers to participate in DR programs where occupancy level, tenant comfort condition and preference, as well as controllable devices and sensors are taken into account in both simulated and real-world environments. Research findings show that the proposed DR algorithms can perform effectively and efficiently during a DR event in residential homes and during the CPP event in commercial buildings. / Ph. D.

This research presents a two-part study on a fuel cell electric van (FCEV), focusing on vehicle modelling and developing different control strategies for the modelled vehicle. The modelling phase accounts for the aging effects on the fuel cell (FC) and battery, analyzing FCEV behavior over time. This includes estimating and integrating the degradation impacts on characteristic curves, such as the FC’s polarization and efficiency curves, the battery’s charging and discharging resistance curves, and the open-circuit voltage curve. A simplified fuel cell system (FCS) model is designed to consider power losses in multiple components, including the FC stack, air compressor, and others. The dynamic limits of the FC are also included to yield more realistic results. The model is based on the vehicle Opel Vivaro FC specifications, incorporating parameters like maximum FC power, battery capacity, vehicle weight, and tire dimensions. Subsequently, various control strategies are applied to analyze their effectiveness in FC and battery State-of-Health (SOH) degradation and hydrogen consumption. A rule-based energy management system (EMS) is implemented first, which operates with five different operational modes dependent on the vehicle’s state. This is followed by a look-up table (LUT) based strategy, which uses two two-dimensional tables generated by a Neural Network (NN). The network is trained with discretized optimal / Thesis / Master of Applied Science (MASc)