The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The combined operation of active thermal energy storage and passive building thermal mass has shown substantial improvement in demand-side control performance when compared to current state-of-the-art demand-side control measures. Specifically, "model-based" optimal control for this operation has the potential to significantly increase performance and bring economic advantages. However, due to the uncertainty in certain operating conditions in the field its control effectiveness could be diminished and/or seriously damaged, which results in poor performance. This dissertation pursues improvements of current demand-side controls under uncertainty by proposing a robust supervisory demand-side control strategy that is designed to be immune from uncertainty and perform consistently under uncertain conditions. Uniqueness and superiority of the proposed robust demand-side controls are found as below: a. It is developed based on fundamental studies about uncertainty and a systematic approach to uncertainty analysis. b. It reduces variability of performance under varied conditions, and thus avoids the worst case scenario. c. It is reactive in cases of critical "discrepancies" observed caused by the unpredictable uncertainty that typically scenario uncertainty imposes, and thus it increases control efficiency. This is obtainable by means of i) multi-source composition of weather forecasts including both historical archive and online sources and ii) adaptive Multiple model-based controls (MMC) to mitigate detrimental impacts of varying scenario uncertainties. The proposed robust demand-side control strategy verifies its outstanding demand-side control performance in varied and non-indigenous conditions compared to the existing control strategies including deterministic optimal controls. This result reemphasizes importance of the demand-side control for a building in the global carbon economy. It also demonstrates a capability of risk management of the proposed robust demand-side controls in highly uncertain situations, which eventually attains the maximum benefit in both theoretical and practical perspectives.

Environmental concerns have led to a rapid increase in renewable energy development and production as the global demand for electricity continues to increase. The intermittent and uncertain nature of electricity generation from renewable sources, such as wind and solar, however, create significant challenges in maintaining power system reliability at reasonable costs. Energy storage and smart-grid technologies are perceived to provide potential solutions to these challenges in modern power systems of different sizes. This work investigates the opportunity to incorporate energy storage in microgrids with renewable energy production, as well as applying smart microgrid management techniques to reduce the lifetime costs while maintaining an acceptable level of reliability. A microgrid consisting of a 5 home community with generation supplied by two propane generators to meet the “N-1” reliability criterion is used as the base case scenario. Actual load data of typical homes is obtained from the industry partner. An equivalent loss of load expectation criterion is used to benchmark the acceptable reliability level. A model is developed to calculate the lifetime operational cost of the base case scenario which is used to assess the benefit of the addition of renewable energy sources, energy storage, and smart microgrid management techniques. A MATLAB program is developed to assess the 20 year operational costs of various combinations of renewable energy sources and battery energy storage, which will be considered the lifetime of the system. The combination of generation and storage which yields the lowest lifetime operational cost is defined as the optimized microgrid, and is used as a basis to determine if additional savings are realized by the implementation of a microgrid operated by a Smart Microgrid Management System (SMMS). The conceptual layout of the proposed SMMS is presented along with identified methods of utilizing in-home thermal storage. The SMMS mechanism is discussed along with proposed functionality, potential methods of employment, and associated development and implementation costs. The microgrid operated by the SMMS is assessed, and its lifetime operational cost is presented and contrasted against the base case microgrid and the optimized microgrid. A power system reliability evaluation of the proposed microgrids are conducted using a probabilistic method to ensure that reliability is not sacrificed by the implementation of a cost-minimized microgrid. A sequential Monte Carlo simulation model is developed to assess the power system reliability of the various microgrid configuration cases. The functionality of this model is verified using an existing reliability assessment program. The results from the presented studies show that the implementation of renewable energy sources, energy storage, and smart microgrid management techniques are an effective way of reducing the operational cost of a remote microgrid while increasing its power system reliability.

Peak electricity demand in South Africa will exceed the available operational generation capacity in 2007. The state utility Eskom is addressing this challenge, inter aha, with the implementation of the Demand-side Management (DSM) initiative. The aim of DSM is to defer the building of additional power stations by modifying the end-user pattern to reduce electrical load during the morning and evening peaks. At the end of 2005 the DSM programme has only achieved 30°/o of its target. Some of the biggest problems are the lack of knowledge on how to perform ESCO audits and availability of tools and procedures to enable Energy Service Companies (ESCOs) to evaluate DSM potential. Studies in South Africa have shown that 20°/o of the total municipal energy is utilised in commercial buildings. Additional investigations have shown that in the commercial sector approximately 50% of energy is used for air conditioning. Energy savings of around 30% can be realised through improved management procedures and retrofit projects of HVAC systems of existing buildings. Telecommunication companies own and operate a large portfolio of diverse buildings. It was shown that these buildings are very inefficient in terms of energy usage. Performing ESCO analyses on these building portfolios present huge savings opportunities for the building owners as well as load reduction opportunities to help meet DSM targets. ESCOs however face major problems in evaluating DSM projects on telecommunication facilities. Some of these problems are: time to perform the ESCO audits on such a large portfolio of buildings; skill levels of available personnel; lack of experience and structured audit process; availability of information; data capturing of information; determining the impact of the retrofits and calculating the savings and financial benefits of retrofits. Obtaining approval for DSM projects is also a lengthy process. Smaller ESCOs cannot afford to commit resources to ESCO investigations only to recover their investment after project approval. Having an ESCO procedure that will speed up the audit process will help the ESCO to minimise resources that need to be committed to these investigations. Having a tested and reliable ESCO procedure will also help Eskom since they will receive more and better quality DSM proposals. A new ESCO procedure for telecommunications facilities was developed. The primary requirements for the new ESCO procedure are that it should be simple, stable, fast and accurate. This procedure is evaluated against the known energy management opportunities in telecommunication facilities. Some of the benefits of the new ESCO procedure are: time taken to perform ESCO analysis on all types of buildings is drastically reduced; lower qualified personnel can be used to perform the ESCO analysis; any type of HVAC system configuration can be accommodated; new data capturing procedures ensure that only essential data is captured; integrated simulation software is used that can easy and accurately simulate the building operations and retrofits on a building; retrofit options suitable for telecommunication facilities are identified; contribution to the DSM programme is evaluated; financial evaluation of the retrofits and feasibility for DSM funding and results are integrated into a standardised reporting format. The new ESCO procedure was implemented on several case studies within the telecommunication infrastructure. Five different types of buildings were selected to implement the ESCO procedure. Each step of the procedure was evaluated and tested against the requirements of the new ESCO procedure. It was proven through implementation that the new ESCO procedure is successful in solving the unique problems in performing ESCO analyses for telecommunications facilities. Valuable insight into the problems that can occur during the ESCO process was highlighted, and recommendation for future work was presented. / Thesis (Ph.D. (Electrical Engineering))--North-West University, Potchefstroom Campus, 2006.

Eskom is under increasing pressure to provide reliable and sustainable electricity. Demand Side Management (DSM), offers a short– to medium–term solution to this problem. During 2009, the mining sector consumed approximately 16% of the domestic electricity supplied by Eskom. This made the mining sector one of the major targets for Eskom–initiated DSM programmes. The mining industry uses compressed air for a wide variety of applications and production purposes. This creates many opportunities to reduce electricity consumption and operating costs. Reducing the airsystem demand may however not result in significant electrical energy savings, unless the compressed–air supply is accurately managed to meet the reduced demand. Until recently, compressor control in the mining sector generally consisted of operating the compressors continuously, regardless of the actual demand for compressed air. Excessive compressed air is blown off into the atmosphere resulting in energy loss. This usually occurs when the compressors are operated manually. A computer–controlled compressor management solution, which optimises the efficiency potential of the compressed–air supply, is required to obtain significant electrical energy savings. The need for such a solution was addressed by the development of an energy management solution for mine compressor systems. This solution is referred to as Energy Management System (EMS) and is capable of starting, stopping, loading and unloading compressors. In addition to this, compressor output can be controlled to maintain a desired pressure set–point. In this study, the development and implementation of EMS on ten different mine compressor systems is presented. Automatic compressor capacity control was implemented, while an operator manually initiated compressor starting; stopping; loading and unloading, according to EMS control schedules. Centralised compressor control is one of the main advantages offered by EMS, especially for compressed–air systems with multiple compressor systems at different geographic locations. EMS facilitated effective and sustainable electrical energy reductions for all these compressed–air systems. / Thesis (M. Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2011.

Eskom is under increasing pressure to provide reliable and sustainable electricity. Demand Side Management (DSM), offers a short– to medium–term solution to this problem. During 2009, the mining sector consumed approximately 16% of the domestic electricity supplied by Eskom. This made the mining sector one of the major targets for Eskom–initiated DSM programmes. The mining industry uses compressed air for a wide variety of applications and production purposes. This creates many opportunities to reduce electricity consumption and operating costs. Reducing the airsystem demand may however not result in significant electrical energy savings, unless the compressed–air supply is accurately managed to meet the reduced demand. Until recently, compressor control in the mining sector generally consisted of operating the compressors continuously, regardless of the actual demand for compressed air. Excessive compressed air is blown off into the atmosphere resulting in energy loss. This usually occurs when the compressors are operated manually. A computer–controlled compressor management solution, which optimises the efficiency potential of the compressed–air supply, is required to obtain significant electrical energy savings. The need for such a solution was addressed by the development of an energy management solution for mine compressor systems. This solution is referred to as Energy Management System (EMS) and is capable of starting, stopping, loading and unloading compressors. In addition to this, compressor output can be controlled to maintain a desired pressure set–point. In this study, the development and implementation of EMS on ten different mine compressor systems is presented. Automatic compressor capacity control was implemented, while an operator manually initiated compressor starting; stopping; loading and unloading, according to EMS control schedules. Centralised compressor control is one of the main advantages offered by EMS, especially for compressed–air systems with multiple compressor systems at different geographic locations. EMS facilitated effective and sustainable electrical energy reductions for all these compressed–air systems. / Thesis (M. Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2011.

L'architecture physique des réseaux électriques et les structures organisationnelles des industries électriques survenues à la suite des réformes ont principalement été conçues en fonction des caractéristiques relatives aux infrastructures de transport et aux parcs de production. Or, les nouveaux enjeux de transition énergétique, associés aux progrès réalisés dans les équipements de communication et d'automatisation, plaident pour une plus grande participation des activités décentralisées de production et des consommateurs finals. Nous constatons que les systèmes électriques sont à l'aube d'évolutions majeures qui partagent une double caractéristique. La première et que ces évolutions nécessiteront des apports en capitaux considérables pour adapter et moderniser les réseaux de distribution. La seconde est que l'activation de l'aval de la chaîne électrique libère des gains d'efficacité économique actuellement inexploités, mais est également porteuse de contraintes nouvelles.Partant de ce constat, l'objectif de cette thèse est double. Il s'agit dans un premier temps de proposer une analyse théorique des instruments de régulation qui encadrent et orientent les dépenses des opérateurs réseau. Nous cherchons en nous appuyant sur la littérature à caractériser les outils de régulation les mieux adaptés à l'investissement en smart technologies. Puisqu'il est nécessaire de confronter l'analyse théorique aux faits, nous entreprenons de recenser les gains clés d'efficacité économique escomptés de la généralisation des smart grids. Nous illustrons chacun de ces gains par une étude empirique qui nous permet de comparer les résultats issus de notre analyse théorique aux schémas de régulation existants et de formuler un certain nombre de recommandations.Le second objectif de la thèse se concentre sur les impacts de la diffusion de programmes de la gestion de la demande. Le raisonnement adopté s'articule autour de deux constats. D'importants bénéfices sont attendus des réductions substantielles des pointes de demande, réductions qui se traduisent par de moindres opportunités de profit pour les producteurs. Il s'agira de réaliser une estimation des gains et pertes que l'on peut attendre de la gestion de la demande. Pour cela, nous développons et utilisons un modèle d'optimisation dans lequel nous intégrons plusieurs pays interconnectés dotés de parcs de production différenciés.La thèse montre que les cadres de régulation dominants actuellement sont limités dans leur portée incitative pour favoriser un investissement efficace dans la technologie, ce qui est susceptible de retarder son introduction. La quantification des impacts de la gestion de la demande montre quant à elle que des efficacités significatives peuvent être activées via la généralisation de ces mesures. Toutefois, elles posent des problèmes nouveaux dans la rémunération de l'existant, l'adéquation future des capacités, et souligne l'antagonisme potentiel entre perte de revenus pour les unités de pointe les plus réactives et développement des énergies bas carbone.De toute évidence, les interrogations soulevées par le développement des smart grids nécessitent que soit mené un débat politique éclairé puisque l'industrie électrique est indispensable à nos sociétés. Parmi le nombre considérable d'éléments à aborder, arriveront en bonne place les questions relatives au financement des projets d'investissement et à l'inclusion des nouvelles sources de flexibilité induites par l'adoption de la technologie dans les marchés électriques libéralisés. / The physical architecture of electricity grids and the organizational structure of power systems implemented after the reforms have traditionally be achieved according to the characteristics of the transmission infrastructures and power mixes. However, the new challenges related to energy transition favor a greater participation of decentralized generation and final consumers to system exploitation and competitive markets. This latter participation is made possible thanks to recent innovations in the fields of communication and remote control technologies.Significant evolutions are expected in power industries that share common characteristics. First, these evolutions suppose massive capital investments to modernize and adapt current power distribution grids. Second, it is expected the activation of distribution grids and final consumers will unleash substantial unexploited economic efficiency gains as well as impose new constraints.Taking these simple facts as a starting point, the objective of the thesis is twofold. In the first place, we provide a theoretical analysis of the regulatory instruments that monitor the system operators' expenses. Relying on the literature, we aim at characterizing what regulatory tools and incitation are suitable for investing in smart grids technologies. Since it is necessary to compare theoretical formulation to facts, we use an empirical approach that allows us to designate key benefits pursued by the development of smart grids and to compare our theoretical results with practical regulatory applications. Our findings eventually allow us to formulate recommendations.In the second place, the thesis focuses on the impacts of demand-side management during peak periods. We structure our approach around two general observations. Large benefits should be generated in lowering substantially peak demand. However, such situation also creates losses of profit for generators. We provide an estimation of efficiency gains and revenue losses induced by peak shedding. To this end, we develop and use a linear optimization model and expand our analysis to interconnected countries endowed with differentiated generation means.The thesis shows dominant regulatory frameworks are unsuited to provide the necessary sets of incentive to efficiently develop smart technologies. This can cause delays in their integration to power grids. The quantitative evaluation of the impacts generated by demand-side management shows significant efficiency gains are achievable through final consumers' flexibility. However, such measures create new discrepancies regarding installed capacities profitability, future capacity adequacy, and highlight potential antagonism between missing money for flexible peak capacities and the development of low carbon energies.It is clear the issues raised by the development of smart grids call for informed public debate as power industries are essential to our societies. Among the considerable amount of elements to discuss, issues relative to financing the investment projects and the inclusion of the new sources of flexibility induced by the technology in competitive markets will be of priority.

This research investigates ways to reduce the carbon dioxide emissions from the cement industry. Cement is one of the largest sources of man-made greenhouse gases, contributing ~5% of the global total. 40% of emissions from cement come from the fuel used in the process, while the electricity used contributes a further 5%. The focus of the research is to find operational changes that can reduce emissions without the need for large capital investment. Three cement plants in the UK were investigated using four different mathematical models based on real data from the plants. A new metric for assessing the environmental impact of the fuel mix of a plant was proposed, and evidence indicates that it may be a better predictor of environmental performance than the metrics currently used in industry. The research found that consistently improving this fuel metric to best-observed levels, as well as reducing the excess air ratio to industry-standard levels had the potential to reduce fuel consumption by up to 7%, and fuel derived CO2 emissions by up to 12%. Increasing use of biomass to best-observed levels had the potential to reduce the net fuel derived CO2 emissions by up to 20%. Comparing the proposed improvements to the historic range of plant performance showed that this level of performance is within the normal operating range of the plants. A reduction of 2-4% in electricity costs and electricity derived emissions was also possible from operational changes. These savings would reduce operating costs as well as emissions, and require little to no capital investment, meaning they could be implemented directly. If successfully implemented in the near future the total savings by 2050 would be on a similar scale to those expected from much more expensive technology changes, such as upgrading to new cement plants, or installing carbon capture and storage technology.

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2012. / Electric motors consume over 60% of the world's generated electricity. In South Africa approximately 65% of the energy generated is consumed by electric motors (Niekerk, 2009). About 95% of motors in use in South Africa are Standard-Efficient Motors (SE-motors) that operate at an average efficiency of 84% to 90%, depending on the size of the motor and the load driven by them. High-Efficient motors (HE-motor) run at an efficiency of 2% to 8% higher than that of SE-motors. In recent years, a drive to replace SE-motors with HE-motors has been promoted for the purpose of Demand Side Management (DSM). The rationale of using HE-motors as a tool of DSM is to harness a small difference in operating efficiency per motor, which can result in a huge reduction in electricity consumption, depending on the number of HE-motors that will replace SE-motors. Reducing the demand for electricity is the key driving factor for DSM in South Africa, so as to relieve the already stressed power generation capacity. Other consequential factors of DSM are to reduce the amount of pollutant gases emitted into the atmosphere. To the electricity users DSM will be a great incentive, as reduced consumption of electricity will decrease the amount of money spent on electricity. Much has been written on the ability of HE-motors to reduce electricity consumption, cost of electricity and global pollution. ESKOM has even demonstrated the faith they have in these motors by giving rebates to motor users who are willing to exchange their existing SE-motors with new HE-motors. The rebates are paid by ESKOM through a newly established DSM program. However, it must be mentioned that savings through HE-motors is not a perfect guarantee. HE-motors have inherent design limitations that may inhibit the saving of energy. To achieve higher efficiency, HE-motors are designed to operate on a smaller slip that consequently increases their speed compared to that of SE-motors (Cheek et al., 1995). Higher rotor speed impacts energy saving abilities of HE-motors when they are used to drive fans, pumps and compressors, normally referred to as centrifugal loads. An increase in speed results in a proportional increase in flow. Power consumed by a motor goes up as a cube of the speed, and the flow rate increases linearly with speed. Motor loads in the petrochemical industry are generally centrifugal, and that is why this thesis focuses on refineries.

This research aims to develop solutions to relieve system stress conditions in electric grids. The approach adopted in this research is based on a new concept in the Smart Grid, namely, demand response optimization. A number of demand response programs with energy storage systems are designed to enable a community to achieve optimal demand side energy management. The proposed models aim to improve the utilization of the demand side energy through load management programs including peak shaving, load shifting, and valley lling. First, a model is proposed to nd the optimal capacity of the battery energy storage system (BESS) to be installed in a power system. This model also aims to design optimal switchable loads programs for a community. The penetration of the switchable loads versus the size of the BESS is investigated. Another model is developed to design an optimal load operation scheduling of a residential heating ventilation and air-conditioning system (HVACs). This model investigates the ability of HVACs to provide optimal demand response. The model also proposes a comfort/cost trade-os formulation for end users. A third model is proposed to incorporate the uncertainty of the photovoltaic power in a residential model. The model would nd the optimal utilization of the PV-output to supply the residential loads. In the first part of this research, mixed integer programming (MIP) formulations are proposed to obtain the optimal capacity of the (BESS) in a power system. Two optimization problems are investigated: (i) When the BESS is owned by a utility, the operation cost of generators and cost of battery will be minimized. Generator on/o states, dispatch level and battery power dispatch level will be determined for a 24-hour period. (ii) When the BESS is owned by a community for peak shaving, the objective function will have a penalty component for the deviation of the importing power from the scheduled power. MIP problems are formulated and solved by CPLEX.The simulation results present the effect of switchable load penetration level on battery sizing parameters. In the second part, a mixed integer programming (MIP) based operation is proposed in this part for residential HVACs. The objective is to minimize the total cost of the HVAC energy consumption under varying electricity prices. A simplied model of a space cooling system considering thermal dynamics is adopted. The optimization problems consider 24-hour operation of HVAC. Comfort/cost trade-o is modeled by introducing a binary variable. The big-M technique is adopted to obtain linear constraints while considering this binary variable. The MIP problems are solved by CPLEX. Simulation results demonstrate the effectiveness of HVAC's ability to respond to varying electricity price. Then, in the final part of this research, two Benders Decomposition strategies are applied to solve a stochastic mixed integer programming (MIP) formulation to obtain the optimal sizing of a photovoltaic system (PV) and battery energy storage system (BESS) to power a residential HVACs. The uncertainty of PV output is modeled using stochastic scenarios with the probability of their occurrence. Total cost including HVAC energy consumption cost and PV/battery installation cost is to be minimized with the system at grid-connected mode over eight hours subject to a varying electricity price. The optimization problem will nd the optimal battery energy capacity, power limit, a number of PV to be installed, and expected HVAC on/o states and BESS charging/discharging states for the next eight hours. This optimization problem is a large-scale MIP problem with expensive computing cost.

In South Africa, where 75% of the worlds platinum is produced, electricity tariffs have increased significantly over recent years. This introduces challenges to the energy intensive mineral processing industry. Within the mineral processing chain, run-of-mine ore milling circuits are the most energy-intensive unit processes. Opportunities to reduce the operating costs associated with power consumption through process control are explored in this work. In order to reduce operating costs, demand side management was implemented on a milling circuit using load shifting. Time-of-use tariffs were exploited by shifting power consumption of the milling circuit from more expensive to cheaper tariff periods in order to reduce overall costs associated with electricity consumption. Reduced throughput during high tariff periods was recovered during low tariff periods in order to maintain milling circuit throughput over a week long horizon. In order to implement and evaluate demand side management through process control, a load shifting controller was developed for the non-linear Hulbert model. Implementation of the load shifting controller was achieved through a multi-layered control approach. A regulatory linear MPC controller was developed to address technical control requirements such as milling circuit stability. A supervisory real-time optimizer was developed to meet economic control requirements such as reducing electricity costs while maintaining throughput. Scenarios, designed to evaluate the sensitivities of the load shifting controller, showed interesting results. Mill power set-point optimization was found to be proportionally related to the mineral price. Set-points were not sensitive to absolute electricity costs but rather to the relationships between peak, standard, and off-peak electricity costs. The load shifting controller was most effective at controlling the milling circuit where weekly throughput was between approximately 90% and 100% of the maximum throughput capacity. From an economic point of view, it is shown that for milling circuits that are not throughput constrained, load shifting can reduce operating costs associated with electricity consumption. Simulations performed indicate that realizable cost savings are between R16.51 and R20.78 per gram of unrefined platinum processed by the milling circuit. This amounts to a potential annual cost saving of up to R1.89 m for a milling circuit that processes 90 t/h at a head grade of 3 g/t. / Dissertation (MEng)--University of Pretoria, 2015. / Electrical, Electronic and Computer Engineering / Unrestricted