South Africa’s electricity supply is under pressure because of inadequate capacity expansion in the early 2000s. One of the initiatives funded by Eskom to alleviate the pressure on the national electricity grid was an aggressive demand-side management (DSM) programme that commenced in 2004. A positive outcome of the DSM programme was that the industrial sector in South Africa benefited from the implementation of a relatively large number of DSM projects. These DSM projects reduced the electricity costs of industrial clients and reduced the demand on the national electricity grid. Unfortunately, the performance of industrial DSM projects deteriorates without proper maintenance. This results in wasted savings opportunities that are costly to industrial clients and Eskom. The purpose of this study was therefore to develop a maintenance strategy that could be applied, firstly, to reverse the deterioration of DSM project performance and, secondly, to sustain and to improve DSM project performance. The focus of the maintenance strategy was to obtain maximum project performance that translated to maximum electricity cost savings for the client. A new performance-centered maintenance (PCM) strategy was developed and proven through practical experience in maintaining industrial DSM projects over a period of more than 60 months. The first part of the PCM strategy consisted of developing a new strategy for the outsourcing of DSM project maintenance to energy services companies (ESCOs) on the company group level of the client. The strategy served as a guideline for both ESCOs and industrial clients to implement and manage a group-level DSM maintenance agreement successfully. The second part of the PCM strategy consisted of a simplified method that was developed to identify DSM projects where applying a PCM strategy would increase or sustain electricity cost savings. The third part of the PCM strategy consisted of practical maintenance guidelines that were developed to ensure maximum project performance. It was based on the plan-do-check-act cycle for continuous improvement with an emphasis on the monitoring of DSM project performance. The last part of the PCM strategy consisted of various alternative key performance indicators that should be monitored to ensure maximum sustainable DSM project performance. The PCM strategy was evaluated by implementing it on ten different DSM projects. The results showed that applying a PCM strategy resulted in an average increase of 64.4% in the electricity cost savings generated by these projects. The average implementation cost of the PCM strategy was 6% of the total benefit generated through it. This indicated that implementing the PCM strategy was a cost-effective manner to ensure that maximum performance of DSM projects was maintained sustainably. / PhD (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

The South African gold mining sector consumes 47% of the mining industry’s electricity. On a deep level gold mine, 20% of the energy is consumed by the refrigeration system. The refrigeration system cools 67 ˚C virgin rock temperatures underground. Underground cooling demand increases significantly with deeper mining activities. Various cooling systems are available for underground cooling. This study focuses on the electricity usage of an ice storage system versus a chilled water system for underground cooling. An energy-savings approach was developed to determine possible power savings on the surface refrigeration system of Mine M. The savings approach involved converting an ice storage system to a chilled water system and varying the water flow through the system. The water flow was varied by installing variable speed drives on the evaporator and condenser water pumps. The feasibility of the energy-efficiency approach was simulated with a verified simulation model. Simulation results indicated the feasibility of converting the thermal ice storage to a chilled water system and implementing the energy-efficiency approach on Mine M. Simulated results indicated a 9% electricity saving when using a chilled water system. Various problems encountered by the mine were also a motivation to convert the thermal ice storage system. Converting an ice storage facility to a chilled water system for energy efficiency on a deep level gold mine Energy management is achieved through the monitoring, controlling and reporting of the implemented savings approach. Converting the glycol plant and recommissioning the chilled water plant gave the mine an additional chiller as backup to sufficiently meet underground demand. An annual summer power saving of 1.5 MW was achieved through the conversion and control strategy. It is concluded that conversion of the thermal ice storage system on Mine M results in an energy- and cost saving. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

In South Africa the main electricity supplier “Eskom” is struggling to meet the increasing demand. To lower the problematic electricity demand, demand side management projects are implemented by large electricity consumers. Measuring equipment is installed as part of these projects to monitor and manage the electricity consumption. Measured data is stored and can be analysed to produce information used for energy management. This, however, is a difficult and time-consuming task, because there are large volumes of data to filter through. It is repetitive work which can be automated. Various data analysis methods are available. These include plotting charts and tables using software packages or data management products. Manually analysing the data using different methods and software packages can be a long and painstaking process especially with large volumes of historical data. Information needs to be customised for different users. For example, managers need to view the end power usage and the amount of electrical energy that can be saved or was saved. Technical personnel need more detail about the electricity consumption by individual components in their system. To interpret the data in different ways a powerful tool is needed. There are many existing tools and software packages available, but most of them focus on buildings or factories. The software packages also have fixed reporting methods that are usually not customisable. In this study a customisable data analysis interface was developed to provide a solution for all the different needs. This interface is user friendly without limiting its customisable functionality. Data is received via emails, processed and then stored in a database hosted by a web server. Users access a website and configure custom charts and tables using the available data. The charts and tables are then displayed on the client’s own home page when the client logs onto the website. This interface was implemented on a website. The results of the interface were tested by automating existing reports using the customisable data analysis interface. Also when compared with the previous data analysis methods it was easily customisable, where it was very hard to customise the previous data analysis methods. It was found that the development of the customisable data analysis interface reduced man-hours spent on reporting with 70% to 80% for large energy consumers by automating the reports. The man-hours are estimated to have a value of R 20 000 to R 60 000 per month, depending on the salaries of the personnel and the volume of reports. It will help the Demand-Side Management (DSM) projects to become a continuous system to lower electricity consumption by providing information that is useful for energy management. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

South Africa’s electricity supply is under pressure because of inadequate capacity expansion in the early 2000s. One of the initiatives funded by Eskom to alleviate the pressure on the national electricity grid was an aggressive demand-side management (DSM) programme that commenced in 2004. A positive outcome of the DSM programme was that the industrial sector in South Africa benefited from the implementation of a relatively large number of DSM projects. These DSM projects reduced the electricity costs of industrial clients and reduced the demand on the national electricity grid. Unfortunately, the performance of industrial DSM projects deteriorates without proper maintenance. This results in wasted savings opportunities that are costly to industrial clients and Eskom. The purpose of this study was therefore to develop a maintenance strategy that could be applied, firstly, to reverse the deterioration of DSM project performance and, secondly, to sustain and to improve DSM project performance. The focus of the maintenance strategy was to obtain maximum project performance that translated to maximum electricity cost savings for the client. A new performance-centered maintenance (PCM) strategy was developed and proven through practical experience in maintaining industrial DSM projects over a period of more than 60 months. The first part of the PCM strategy consisted of developing a new strategy for the outsourcing of DSM project maintenance to energy services companies (ESCOs) on the company group level of the client. The strategy served as a guideline for both ESCOs and industrial clients to implement and manage a group-level DSM maintenance agreement successfully. The second part of the PCM strategy consisted of a simplified method that was developed to identify DSM projects where applying a PCM strategy would increase or sustain electricity cost savings. The third part of the PCM strategy consisted of practical maintenance guidelines that were developed to ensure maximum project performance. It was based on the plan-do-check-act cycle for continuous improvement with an emphasis on the monitoring of DSM project performance. The last part of the PCM strategy consisted of various alternative key performance indicators that should be monitored to ensure maximum sustainable DSM project performance. The PCM strategy was evaluated by implementing it on ten different DSM projects. The results showed that applying a PCM strategy resulted in an average increase of 64.4% in the electricity cost savings generated by these projects. The average implementation cost of the PCM strategy was 6% of the total benefit generated through it. This indicated that implementing the PCM strategy was a cost-effective manner to ensure that maximum performance of DSM projects was maintained sustainably. / PhD (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

The South African gold mining sector consumes 47% of the mining industry’s electricity. On a deep level gold mine, 20% of the energy is consumed by the refrigeration system. The refrigeration system cools 67 ˚C virgin rock temperatures underground. Underground cooling demand increases significantly with deeper mining activities. Various cooling systems are available for underground cooling. This study focuses on the electricity usage of an ice storage system versus a chilled water system for underground cooling. An energy-savings approach was developed to determine possible power savings on the surface refrigeration system of Mine M. The savings approach involved converting an ice storage system to a chilled water system and varying the water flow through the system. The water flow was varied by installing variable speed drives on the evaporator and condenser water pumps. The feasibility of the energy-efficiency approach was simulated with a verified simulation model. Simulation results indicated the feasibility of converting the thermal ice storage to a chilled water system and implementing the energy-efficiency approach on Mine M. Simulated results indicated a 9% electricity saving when using a chilled water system. Various problems encountered by the mine were also a motivation to convert the thermal ice storage system. Converting an ice storage facility to a chilled water system for energy efficiency on a deep level gold mine Energy management is achieved through the monitoring, controlling and reporting of the implemented savings approach. Converting the glycol plant and recommissioning the chilled water plant gave the mine an additional chiller as backup to sufficiently meet underground demand. An annual summer power saving of 1.5 MW was achieved through the conversion and control strategy. It is concluded that conversion of the thermal ice storage system on Mine M results in an energy- and cost saving. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

By 2040, global CO2 emissions and energy consumption are expected to increase by 40%. In the US, buildings account for 40% of national CO2 emissions and energy consumption, of which 75% is met by fossil fuels. Reducing this impact on the environment requires both improved building energy efficiency and increased renewable utilization. To this end, this dissertation presents a demand-supplystorage- based decision framework to enable strategic energy management in smart buildings. This framework includes important but largely unaddressed aspects pertaining to building demand and supply such as occupant plugloads and the integration of weather forecast-based solar prediction, respectively. We devote the first part of our work to study occupant plugloads, which account for up to 50% of demand in high performance buildings. We investigate the impact of plugload control mechanisms based on the analysis of real-world data from experiments we conducted at NASA Ames sustainability base and Carnegie Mellon University (SV campus). Our main contribution is in extending existing demand response approaches to an occupant-in-the-loop paradigm. In the second part of this work, we describe methods to develop weather forecastbased solar prediction models using both local sensor measurements and global weather forecast data from the National Ocean and Atmospheric Administration (NOAA).We contribute to the state-of-the-art solar prediction models by proposing the incorporation of both local and global weather characteristics into their predictions. This weather forecast-based solar model plus the plugload-integrated demand model, along with an energy storage model constitutes the weather-driven plugloadintegrated decision-making framework for energy management. To demonstrate the utility of this framework, we apply it to solve an optimal decision problem with the objective of minimizing the energy-related operating costs associated with a smart building. The findings indicate that the optimal decisions can result in savings of up to 74% in the expected operational costs. This framework enables inclusive energy management in smart buildings by accounting for occupants-in-the-loop. Results are presented and discussed in the context of commercial office buildings.

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of elds among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of ne-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this thesis, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We showthat our implementation is e cient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the thesis provide energy saving for the smart home.

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of elds among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of ne-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this thesis, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We showthat our implementation is e cient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the thesis provide energy saving for the smart home.

The judicious use of energy by industries is a key lever for ensuring a sustainable industrial development. The cost effective application of energy management and energy efficiency measures offers industries with an effective means of gaining both economic and social dividend, also reducing the negative environmental effects of energy use. Unfortunately, industries in developing countries are lagging behind in the adoption of energy efficiency and management measures; as such missing the benefits of implementation. This study is aims at enhance the knowledge of industrial energy efficiency and management strategies in Ghana, by investigating the present level of energy (and efficiency) management practices in Ghana largest industrial park (i.e. Tema industrial area). The study also incorporates the investigation of also investigation of barriers to and driving forces for the implementation of energy efficiency measure; to shed light on the rationale for both the adoption and non-adoption of cost effective industrial energy efficient technologies in Ghana. This study was carried out using a semi-structure interview due to the explorative nature of the study. The interviews were conducted in sessions, in the first session respondents were asked describe the energy management strategies in used in the respective companies. In the second session, respondents were asked to fill a structured questionnaire covering the various aspects of the study. The results reveal that energy is poorly managed in the industrial area and there is an energy efficiency gap resulting from the low implementation energy efficiency measures. In addition the reveals that the important barriers impeding the implementation of cost effective energy efficiency technologies or measures in the surveyed firms principally stems from rational behavior economic barriers, which are deeply linked to the lack of government frameworks for industrial energy efficiency. The study also finds that economic gains related to ‘cost reductions resulting from lowered energy use’ and ‘threats of rising energy prices’ are the most important drivers for implementing energy efficiency measures or technologies.

The issue of energy shortage has arisen in recent years. All countries must discuss the manner to reduce energy consumption, and smart grid is a better one of the solutions. According to related researches, energy consumption can be effectively reduced using energy management information of smart grids. By using smart grids, electricity suppliers can learn about the current energy consumption of neighborhoods, and control the electrical energy generation and price of electrical energy. Users can learn the current price of electrical energy and obtain energy management information from smart meters for energy management and device control. However, electricity consumptions of users may divulge the privacy information of users. Therefore, privacy of users and communication security of smart grid become crucial security issues. In this thesis, we propose a provably secure power usage data aggregation scheme for smart grids. Electricity suppliers can learn about the current power usage of neighborhoods without knowing the individual electricity consumption of each user, and use the current power usage of neighborhoods to arrange energy distribution. Therefore, electricity suppliers cannot use the data to reveal lifestyles of each user. In our scheme, the transmission information is encrypted and signed to prevent theft or tampering of data. Finally, we also provide formal proofs for our scheme in this thesis.