M. Phil. / Presently, ESKOM is rated as the fifth largest utility in the world that generates and distributes electricity power to their consumers at the lowest price per kilowatt-hour (kW.h). As a utility, ESKOM is the largest supplier of electrical energy in South Africa and is currently generating and distributing on demand to approximately 3000 consumers. This represents 92% of the South African market. ESKOM was selected as the utility supplying electrical energy for the purpose of this study. ESKOM's objective is to provide the means and systems by which the consumer can be satisfied with electricity at the most cost-effective manner. In order to integrate the consumers into these objectives, ESKOM took a decision in 1994 to change the supply tariff from active power (kW) to apparent power (kVA) for a number of reasons: To establish a structure whereby the utility and the consumer can control the utilisation of electrical power supply to the consumer. To utilise demand and control through power factor correction and implementation of load management systems. To identify some cost implications of electrical power factor correction and load management. Consumers with kW maximum demand tariff options had little or no financial incentives to improve their low power factor (PF) by reducing their reactive current supply. Switching to (kVA) maximum demand will involve steps to be taken to ensure that the reactive component is kept to a minimum with maximum power factor. ESKOM has structured various tariff rates and charges with unique features that would accommodate the consumers in their demand side management and load cost requirements, which, when applied, will result in an efficient and cost effective load profile. These tariffs are designed to guide consumers automatically into an efficient way of using electrical power, as it is designed to recover both the capital investment and the operating cost within two to three years after installation of power factor correction equipment. ESKOM's concept of Time-of-use (TOU) periods for peak, standard and off-peak times during week, Saturday and Sunday periods is discussed as load management. Interruptible loads can be scheduled or shed to suit lower tariff rates and to avoid maximum demand charge. The concept of load management will change the operation pattern of the consumer's electricity demand whereby the consumer will have immediate technical and financial benefits. In the last chapter of this dissertation, a hypothetical case study addresses and concludes on some of the technical and cost implications of electrical power factor correction and load management as a successful and profitable solution to optimize electrical power supply to the consumer. By implementing the above, ESKOM ensures that the consumer utilizes the electrical power supply to its optimum level at the lowest cost per kilowatthour (kW.h) generated.

M.Ing. (Electrical and Electronic Engineering) / Long transmission lines in power system require high line loading in order to lower voltage limits due to line losses. For relatively long lines, line charging is high and thus higher voltage limits reached at low loading. It follows then that it is a challenge to maintaining the voltages between the acceptable limits for relatively long lines. This dissertation highlights the problems experienced when load varying from very low to very high is supplied by very long parallel lines of different impedance characteristic. When the load is extremely high, there are low voltages experienced which are solved by use of shunt capacitors and/or adding more lines. When the load is extremely low, there are high voltages experienced which are solved by use of shunt reactors and/or switching some of the lines off. The type of solutions to this two loading extremes as indicated above, can be problematic, in that; new lines requires servitudes which can take too long, shunt capacitors and reactors in this type of the network is not desirable since the introduction of too many of these devices have maintenance implications and they would require continuous switching to maintain acceptable voltages, resulting in complicated operation of the network. This research proposes the use of a phase shifting transformer located on one of two parallel corridors supplying power to a load located remotely from the rest of the system. The transformer is able to rearrange the active power flows to vary loadings of the corridors and the improvements in voltage regulation can be realised during both low and high load conditions.

D.Phil / The prediction of the expected transmission network loads as required for transmission network power flow studies, has become very important and much more complex than ten to twenty years ago. Therefore a single forecast is no longer the answer to the problem. The modelling of different long-term electrical forecasts makes it possible to compare a number of different forecasts. The modelling provides the further option that each expected load can be entered as a range and then the developed balancing algorithm checks for consensus (feasibility). If feasibility exists, then the different forecasts are reconciled (a feasible solution is determined). Factors such as international and national market trends, economical cycles, different weather patterns, climate cycles and demographic changes are studied. The factors that have significant impact on the transmission electrical loads are integrated in ten different forecasts. It thus gives more insight into the electrical industry and makes the forecast results more informative and therefore reduces the uncertainty in the future expected loads.

Distributed energy resources like residential electric water heaters and residential battery inverter systems offer a small amount of change to the grid individually. When aggregated however, these assets can cause major effects to the electric grid. Aggregating these resources allows them to take on generator-like functions with the ability to increment power and decrement power. The Western Energy Imbalance Market is an energy market offering 15 minute and 5 minute markets for energy transactions between balancing areas. Generation assets make increment and decrement bids. Traditionally the only entrants to this market have been large scale generators and large scale assets legally designated as generators. Aggregated distributed resources could offer the same increments and decrements from managing residential assets like electric water heaters and batteries. DERAS, a Distributed Energy Resource Aggregation System developed by the Portland State Power Lab group, is an aggregator of residential resources that could offer increment and decrement bids to an energy market, like an Energy Imbalance Market. This research models and simulates aggregations of distributed energy resources. This work analyzes the effects of 10,000 electric water heaters and 10,000 battery inverter systems. A simulation program was built to simulate regular use of these assets, and then add the additional effects of a decrement bid into the Western Energy Imbalance Market. The effects of the bids on energy levels inside the water heaters and batteries are examined. The power imported from the grid is also analyzed as an effect of the aggregator attempting to cover a generation decrement bid.

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The design, simulation and evaluation of an intelligent and integrated load management system is presented in this dissertation. The objective of this research was to apply modern computer and communication technology to influence customer use of electricity in ways that would produce desired changes in the utility's load shape. Peak clipping (reduction of peak load) using direct load control is the primary application of this research. The prototype computerized communication and control package developed during this work has demonstrated the feasibility of this concept. The load management system consists of a network of computers, data and graphics terminals, controllers, modems and other communication hardware, and the necessary software. The network of interactive computers divides the responsibility of monitoring of meteorological data, electric load, and performing other functions. These functions include: data collection, processing and archiving, load forecasting, load modeling, information display and alarm processing. Each of these functions requires a certain amount of intelligence depending on the sophistication and complication of that function. Also, a high level of reliability has been provided to each function to guarantee an uninterrupted operation of the system. A full scale simulation of this concept was carried out in the laboratory using five microcomputers and the necessary communication hardware. An important and integral part of the research effort is the development of the short-term load forecast, load models and the decision support system using rule-based algorithms and expert systems. Each of these functions has shown the ability to produce more accurate results compared to classical techniques while at the same time requiring much less computing time and historical data. Development of these functions has made the use of microcomputers for constructing an integrated load management system possible and practical. Also, these functions can be applied for other applications in the electric utility industry and maintain their importance and contribution. In addition to that, the use of rule-based algorithms and expert systems promises to yield significant benefits in using microcomputers in the load management area. / Ph. D.

Most of the techniques that have been applied to the short-term load forecasting problem fall within the time series approaches. The exception to this has been a new approach based on the application of expert systems. Recently several techniques have been reported which apply the rule-based (or expert systems) approach to the short-term load forecasting problem. However, the maximum lead time used for these forecasts has not gone beyond 48 hours, even though there is a significant difference between these algorithms in terms of their data base requirements (few weeks to 10 years). The work reported in this dissertation deals with two aspects. The first one is the application of rule-based techniques to weekly load forecast. A rule-based technique is presented that is capable of issuing a 168-hour lead-time load forecast. The second aspect is the development of a comprehensive load forecasting system that utilizes both the statistical and rule-based approaches. This integration overcomes the deficiencies that exist in both of these modeling techniques. The load forecasting technique is developed using two parallel approaches. In the first approach expert information is used to identify weather variables, day types and diurnal effects that influence the electrical utility load. These parameters and hourly historical loads are then selectively used for various statistical techniques (e.g., univariate, transfer function and linear regression). A weighted average load forecast is then produced which judiciously combines the forecasts from these three techniques. The second approach, however, is free of any significant statistical computation, and is based totally on rules derived from electric utility experts. The data base requirement for any of these approaches do not extend more than four weeks ol hourly load, dry bulb and dew point temperatures. When the algorithms are applied to generate seven-day ahead load forecasts for summer (August) and winter (February) the average forecast errors for the month come under 3%. / Ph. D.

Direct Load Control (DLC) -- the direct control of customer loads by an electric utility for the economic and reliable operation of the power system, is an important and active element of Load Management (LM). Currently attention has focussed on the integration of DLC into system operations. However, as yet, DLC is regarded as a discretionary resource to be used by the system operator based on informed judgment. The integration process has therefore, concentrated on improving the informational inputs to the operator. This dissertation extends the integration from that of a discretionary resource to a dispatchable system resource. The concept of the dynamic dispatch of DLC is formulated and defined to be an online evaluation and utilization of DLC for optimum benefit to the utility, as system conditions change. The concept envisages the use of DLC in an automated mode and coordinated with other system resources for optimum benefit. An important and integral part of the research effort is the development of a cost characterization of DLC. A closed form solution, using a dynamic programming framework, has been developed to estimate the costs of DLC dispatch. The derivation takes into account all operational constraints on the utilization of DLC -- payback characteristics, maximum on-times and minimum recovery times. The cost, defined as the difference in the fuel costs with and without DLC dispatch, were found to be dependent on the cost characteristics of the online generators and the load shape impacts of DLC dispatch. The dynamic dispatch concept is concretized by a power system operations model which incorporates DLC dispatch for fuel cost minimization and peak load shaving. The two modes are toggled by the dispatch algorithm as system conditions change. Results from the model are presented for several combinations of system conditions and DLC system parameters. / Ph. D.

This work explores the need for multiprocessing in the power industry. A suitable computer architecture for power system problems is presented. An efficient decomposition technique is developed to solve the problem parallely. Simulation of distributed processing using IBM 370 computer is considered. A microprocessor version of load flow program is developed and distributed load flow for on-line and off-line applications are studied. A novel algorithm for economic dispatch with and without transmission losses is presented. The algorithm utilizes a closed form expression for the calculation of the Lagrange multiplier thereby avoiding any iterative process in the calculation. Different nonlinear programming techniques are compared to the improved method. The algorithm presented is fast and appears to have good convergence properties. The improved algorithm is extended to distributed processing. Characteristics of a distributed microcomputer system and a multiple processor system are discussed. Intel 8080, 8085 and 8086 versions of distributed and multiprocessing methods are presented to solve power system problems. / Ph. D.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering in the School of Electrical and Information Engineering, July 2017 / This dissertation presents the design and testing of controllers intended to provide au- tonomous demand response, through the use of water heater loads and grid frequency measurements. The controllers use measured frequency as an indication of the strain on a utility grid, which allows demand side management to be isolated from any form of central control. Water heaters can operate as exible loads because their power consump- tion can be dispatched or deferred without directly impacting users. These properties make it possible to control individual water heaters based on the functioning of the grid, rather than end user input. The purpose of this research is to ultimately provide a low- cost alternative to a traditional Smart Grid, that will improve the resilience of a grid without negatively impacting users. The controllers presented here focus on ensuring that users receive hot water, while attempting to reduce any imbalance between power generated and power consumed on the grid. Simulations of these controllers in various situations highlight that while the controllers developed respond suitably to variations in the grid frequency and adequately ensure end users receive hot water, the practical bene t of the controllers depends largely on the intrinsic characteristics of the grid. / CK2018