" Because of the high volume and unpredictable arrival rates, stream processing systems may not always be able to keep up with the input data streams, resulting in buffer overflow and uncontrolled loss of data. To continuously supply online results, two alternate solutions to tackle this problem of unpredictable failures of such overloaded systems can be identified. One technique, called load shedding, drops some fractions of data from the input stream to reduce the memory and CPU requirements of the workload. However, dropping some portions of the input data means that the accuracy of the output is reduced since some data is lost. To produce eventually complete results, the second technique, called data spilling, pushes some fractions of data to persistent storage temporarily when the processing speed cannot keep up with the arrival rate. The processing of the disk resident data is then postponed until a later time when system resources become available. This dissertation explores these load reduction technologies in the context of XML stream systems. Load shedding in the specific context of XML streams poses several unique opportunities and challenges. Since XML data is hierarchical, subelements, extracted from different positions of the XML tree structure, may vary in their importance. Further, dropping different subelements may vary in their savings of storage and computation. Hence, unlike prior work in the literature that drops data completely or not at all, in this dissertation we introduce the notion of structure-oriented load shedding, meaning selectively some XML subelements are shed from the possibly complex XML objects in the XML stream. First we develop a preference model that enables users to specify the relative importance of preserving different subelements within the XML result structure. This transforms shedding into the problem of rewriting the user query into shed queries that return approximate answers with their utility as measured by the user preference model. Our optimizer finds the appropriate shed queries to maximize the output utility driven by our structure-based preference model under the limitation of available computation resources. The experimental results demonstrate that our proposed XML-specific shedding solution consistently achieves higher utility results compared to the existing relational shedding techniques. Second, we introduces structure-based spilling, a spilling technique customized for XML streams by considering the spilling of partial substructures of possibly complex XML elements. Several new challenges caused by structure-based spilling are addressed. When a path is spilled, multiple other paths may be affected. We categorize varying types of spilling side effects on the query caused by spilling. How to execute the reduced query to produce the correct runtime output is also studied. Three optimization strategies are developed to select the reduced query that maximizes the output quality. We also examine the clean-up stage to guarantee that an entire result set is eventually generated by producing supplementary results to complement the partial results output earlier. The experimental study demonstrates that our proposed solutions consistently achieve higher quality results compared to the state-of-the-art techniques. Third, we design an integrated framework that combines both shedding and spilling policies into one comprehensive methodology. Decisions on the choice of whether to shed or spill data may be affected by the application needs and data arrival patterns. For some input data, it may be worth to flush it to disk if a delayed output of its result will be important, while other data would best directly dropped from the system given that a delayed delivery of these results would no longer be meaningful to the application. Therefore we need sophisticated technologies capable of deploying both shedding and spilling techniques within one integrated strategy with the ability to deliver the most appropriate decision customers need for each specific circumstance. We propose a novel flexible framework for structure-based shed and spill approaches, applicable in any XML stream system. We propose a solution space that represents all the shed and spill candidates. An age-based quality model is proposed for evaluating the output quality for different reduced query and supplementary query pairs. We also propose a family of four optimization strategies, OptF, OptSmart, HiX and Fex. OptF and OptSmart are both guaranteed to identify an optimal solution of reduced and supplementary query pair, with OptSmart exhibiting significantly less overhead than OptF. HiX and Fex use heuristic-based approaches that are much more efficient than OptF and OptSmart. "

Should Eskom and municipalities be held liable for loss resulting from load shedding? In essence, this is the question this dissertation answers or at least sheds some light on. This dissertation looks at the possibility of holding Eskom and municipalities delictually or contractually liable for loss resulting from load shedding. It does this by first discussing the delictual elements and thereafter determining whether these elements are present in the current circumstances in which Eskom and municipalities find themselves. It also looks at the relevant forms of breach of contract which may be present under the circumstances. It discusses their applicability to Eskom’s Standard Conditions of Supply for Small Supplies with Conventional Metering. It also discusses the applicability of these forms of breach to the relevant electricity supply by-laws which, in essence, provide the terms and conditions relating to the agreement for the supply of electricity between municipalities and consumers. The nature of electricity supply contracts are discussed throughout the dissertation in brief. It is found that electricity in itself is a very unique thing where the supply and sale thereof cannot be separated. The dissertation also deals with some interesting legislation which has the effect of municipalities and Eskom having to prove that they were not negligent in causing loss to consumers. Furthermore, the dissertation looks at related topics, briefly discussing class actions, pure economic loss, the “once and for all” rule, mitigation of loss, prescription, concurrent actions and possible infringement of constitutional rights. It considers the types of loss which might be claimed for as well as alternatives to instituting claims for damages. In the end, the conclusion is reached that all claims must be assessed with due regard to the circumstances surrounding each claim. It also comes to the conclusion that, in general, Eskom can be held delictually and contractually liable for load shedding. The assessed contract contains provisions which are contrary to national legislation and thus inoperative. It is, however, doubtful if such liability would succeed since courts would in all probability deny such claims for fear of opening the flood gates. It might be harder and even impossible to hold municipalities delictually liable. However, municipalities might be contractually liable as it is clear that by-laws, which regulate the supply of electricity to the consumer by the municipality, are often inoperative since these are in conflict with national legislation. This dissertation does not proclaim to provide all the answers relating to claims resulting from load shedding. It is, however, hoped that it will provide some insight into the considerations that need to be taken into account whilst raising some thought provoking questions. / Dissertation (LLM)--University of Pretoria, 2011. / Private Law / unrestricted

Masters in Public Administration - MPA / Nigeria has been experiencing challenges in the distribution of power to the whole country in the past decades. As a result, more than half of Nigeria's population is affected by the ineffectiveness of the distribution of electricity which lowers their standard of living. As the country's power sector experienced a steady growth after its independence in 1960, it was anticipated at the time that, at that rate of growth and development, most of Nigeria should have been electrified by now. However, challenges in the distribution of electricity have persisted and this has negatively affected the economy and living standard of the country. From the management perspective, this research looks at the situation of the distribution of electricity in Nigeria from the year 2005 to 2015. Specifically, it will analyses management challenges affecting the distribution of electricity in the country. It is well documented how Nigeria is currently facing an electricity crisis despite all the government efforts to provide adequate power to the citizens. In the distribution of electricity in Nigeria, the research will look at how the planning of the organization is been done so as to ensure effective power delivery to the country. The research will further look at how the management manages the organization and how it is being controlled for effective power distribution. In this research, I shall use qualitative and quantitative research techniques. Secondary qualitative and quantitative data will be used in carrying out this research. Published books, journals, newspaper articles, and government policies shall be critically examined in order to produce a well-informed report. Before the research is conducted, the appropriate consent from the University of the Western Cape will be sought to ensure that all protocols are strictly adhered to.

The trend of making more profits for the owners, deregulation of the utility market and need for obtaining permission from regulatory agencies have forced electric power utilities to operate their systems close to the security limits of their generation, transmission and distribution systems. The result is that power systems are now exposed to substantial risks of experiencing voltage collapse. This phenomenon is complex and is localized in nature but has widespread adverse consequences. The worst scenario of voltage collapse is partial or total outage of the power system resulting in loss of industrial productivity of the country and major financial loss to the utility. On-line monitoring of voltage stability is, therefore becoming a vital practice that is being increasingly adopted by electric power utilities. The phenomenon of voltage collapse has been studied for quite some time, and techniques for identifying voltage collapse situations have been suggested. Most suggested techniques examine steady-state and dynamic behaviors of the power system in off-line modes. Very few on-line protection and control schemes have been proposed and implemented. In this thesis, a new technique for preventing voltage collapse is presented. The developed technique uses subset of measurements from local bus as well as neighbouring buses and considers not only the present state of the system but also future load and topology changes in the system. The technique improves the robustness of the local-based methods and can be implemented in on-line as well as off-line modes. The technique monitors voltages and currents and calculates from those measurements time to voltage collapse. As the system approaches voltage collapse, control actions are implemented to relieve the system to prevent major disturbances. The developed technique was tested by simulating a variety of operating states and generating voltage collapse situations on the IEEE 30-Bus test system. Some results from the simulation studies are reported in this thesis. The results obtained from the simulations indicates that the proposed technique is able to estimate the time to voltage collapse and can implement control actions as well as alert operators.

Monitoring and mining real-time network data streams are crucial operations for managing and operating data networks. The information that network operators desire to extract from the network traffic is of different size, granularity and accuracy depending on the measurement task (e.g., relevant data for capacity planning and intrusion detection are very different). To satisfy these different demands, a new class of monitoring systems is emerging to handle multiple and arbitrary monitoring applications. Such systems must inevitably cope with the effects of continuous overload situations due to the large volumes, high data rates and bursty nature of the network traffic. These overload situations can severely compromise the accuracy and effectiveness of monitoring systems, when their results are most valuable to network operators. In this thesis, we propose a technique called load shedding as an effective and low-cost alternative to over-provisioning in network monitoring systems. It allows these systems to handle efficiently overload situations in the presence of multiple, arbitrary and competing monitoring applications. We present the design and evaluation of a predictive load shedding scheme that can shed excess load in front of extreme traffic conditions and maintain the accuracy of the monitoring applications within bounds defined by end users, while assuring a fair allocation of computing resources to non-cooperative applications. The main novelty of our scheme is that it considers monitoring applications as black boxes, with arbitrary (and highly variable) input traffic and processing cost. Without any explicit knowledge of the application internals, the proposed scheme extracts a set of features from the traffic streams to build an on-line prediction model of the resource requirements of each monitoring application, which is used to anticipate overload situations and control the overall resource usage by sampling the input packet streams. This way, the monitoring system preserves a high degree of flexibility, increasing the range of applications and network scenarios where it can be used. Since not all monitoring applications are robust against sampling, we then extend our load shedding scheme to support custom load shedding methods defined by end users, in order to provide a generic solution for arbitrary monitoring applications. Our scheme allows the monitoring system to safely delegate the task of shedding excess load to the applications and still guarantee fairness of service with non-cooperative users. We implemented our load shedding scheme in an existing network monitoring system and deployed it in a research ISP network. We present experimental evidence of the performance and robustness of our system with several concurrent monitoring applications during long-lived executions and using real-world traffic traces.

This thesis derives the proper load shedding scheme for a distribution system with wind power generating units to maintain the power supply reliability for the islanding operation of micro grid systems after fault disturbance. The comparison of operation performance and control scheme between the fixed speed and the variable speed wind power generators are made. The seasonal wind power energy by the wind turbine is calculated by applying the exponential rate (Power Law) and Weibull possibility distribution model with the actual minutely wind speed data in Hengchun and Penghu area in 2005. The mean values of seasonal wind power output and standard deviation are determined for the design of load shedding scheme for the islanding operation of the distribution feeder. Moreover, a practical distribution feeder BX31 in Fengshan District in Taiwan Power Company (TPC) is selected for the computer simulation of micro grid systems. The systems voltage and power variation of the distribution feeder are investigated when the wind turbine is connected to the feeder by considering the weekday and weekend load models. The voltage sag on the distribution feeder and transient stability of wind turbine are simulated for the fault contingency with three-phase short-circuit fault occurred on the feeder outlet. Consequently, synchronous condensers are connected and the blade angle of wind turbines is then adjusted to improve the transient response of output characteristic of wind turbine. It is found that the power supply reliability of micro grid with wind power generations will be deteriorated following the tripping of wind turbines due to the oscillation of terminal voltage introduced by long fault clearing time. To solve the problem, the proper design of the tripping for the micro grid systems with wind turbines is derived according to the transient stability analysis. To restore the systems stability of the islanding systems, the proper amount of load shedding is determined and the switching of control modes of the wind turbine is executed, according to the power mismatch between wind turbine generation and load demand of the distribution feeder.

This objective of thesis is to derive the adaptive load shedding by artificial neural network (ANN) so that the amount of load shedding can be minimized. An actual industrial customer and Taipower system are selected for computer simulation to fit the ANN model. The mathematical models of generation, exciters, governors and loads are used in the simulator program. The back propagation neural method is considered for the neural network training of load shedding.To create the training data set for ANN models, the transient stability analysis is performed to fit the load shedding under different operation and fault condition. The back propagation method and L-M learning process are then used to fit the minimum load shedding without causing system stability problem. To verify the effectiveness of the proposed methodology for adaptive load shedding, three fault contingencies for both the industrial cogeneration system and Taipower system have been simulated. By compare to the conventional load shedding, it is found that the amount of load shedding can be minimized and adjusted according to the real time operation conditions of power systems.

Cette recherche se concentre sur l'optimisation d'un micro-réseau en interaction avec le réseau électrique intelligent. Il s'agit de la recherche de solutions optimales pour la conception d'un micro-réseau afin de minimiser les coûts, d'une part, et la possibilité augmenter 1'utilisation des sources renouvelables, d'autre part. La supervision, doit traiter la prise en compte des incertitudes dans la gestion prédictive optimisée des flux de puissance. / This thesis study focuses on a DC microgrid building-integrated satisfying the power balance at the local level and supplying DC loads during both, grid-connected and isolated operation modes. Considering that energy management can be defined as a group of different control strategies and operational practices that together with the new physical equipment and software solutions aims to accomplish the objectives of energy management, the main objective of this thesis is to define the energy management strategies for the building-integrated DC microgrid, aiming to keep the bus voltage stable as well as to reduce the energy cost to the end users and the negative impact to the main grid. Therefore, this research work focuses to optimize and develop the implementation of the designed controller of building-integrated DC microgrid. The proposed DC microgrid consists of PV building-integrated sources, a storage system, a main grid connection for the grid-connected mode and a micro turbine for the off-grid or isolated mode, and a DC load (electric appliances of a tertiary building). The bidirectional connections with the main grid and the storage aim to supply the building’s DC appliances, and sell or store the energy surplus. The results validate the operation of the whole system, ensuring the capability of the proposed supervisory control to manage the energy power flow while ensuring voltage stability. Other goals concern the analyze of the proposed separation between optimization and real time power balance and the usage of the proposed load shedding/restoration algorithm in the microgrid environment are also validate. Regarding the technical contributions, the work of this thesis allowed the creation and the practical development of a test bench for microgrid based on PV sources emulator, which allows the repeatability conditions (closeness of the agreement between the results of successive measurements of the same solar irradiance and air temperature carried out under the same conditions of measurement) and reproducibility (closeness of the agreement between the results of measurements of the same solar irradiation and air temperature carried out under changed conditions of measurement). Numerous experimental tests were carried out and allowed the validation of the proposed concepts.

Indiana University-Purdue University Indianapolis (IUPUI) / Electric demand charge is a large portion (usually 40%) of electric bill in residential, commercial, and manufacturing sectors. This charge is based on the greatest of all demands that have occurred during a month recorded by utility provider for an end-user. During the past several years, electric demand forecasting have been broadly studied by utilities on account of the fact that it has a crucial impact on planning resources to provide consumers reliable power at all time; on the other hand, not many studies have been conducted on consumer side. In this thesis, a novel Maximum Daily Demand (MDD) forecasting method, called Adaptive-Rate-of-Change (ARC), is proposed by analysing real-time demand trend data and incorporating moving average calculations as well as rate of change formularization to develop a forecasting tool which can be applied on either utility or consumer sides. ARC algorithm is implemented on two different real case studies to develop very short-term load forecasting (VSTLF), short-term load forecasting (STLF), and medium-term load forecasting (MTLF). The Chi-square test is used to validate the forecasting results. The results of the test reveal that the ARC algorithm is 84% successful in forecasting maximum daily demands in a period of 72 days with the P-value equals to 0.0301. Demand charge is also estimated to be saved by $8,056 (345.6 kW) for the first year for case study I (a die casting company) by using ARC algorithm. Following that, a new Maximum Demand Management (MDM) method is proposed to provide electric consumers a complete package. The proposed MDM method broadens the electric consumer understanding of how MDD is sensitive to the temperature, production, occupancy, and different sub-systems. The MDM method are applied on two different real case studies to calculate sensitivities by using linear regression models. In all linear regression models, R-squareds calculated as 0.9037, 0.8987, and 0.8197 which indicate very good fits between fitted values and observed values. The results of proposed demand forecasting and management methods can be very helpful and beneficial in decision making for demand management and demand response program.

Severe disturbances in a large electrical interconnection cause a large mismatch in generation and load in the network, leading to frequency instability. If the mismatch is not rectified quickly, the system may disintegrate into multiple islands. Though the Automatic Generation Controls (AGC) perform well in correcting frequency deviation over a period of minutes, they are ineffective during a rolling blackout. While traditional Under Frequency Load Shedding Schemes (UFLS) perform quick control actions to arrest frequency decline in an islanded network, they are not designed to prevent unplanned islanding. The proposed Intelligent Load Shedding algorithm combines the effectiveness of AGC Scheme by observing tie line flows and the speed of operation of the UFLS Scheme by shedding loads intelligently, to preserve system integrity in the event of an evolving cascading failure. The proposed scheme detects and estimates the size of an event by monitoring the tie lines of a control area using Wide Area Measurement Systems (WAMS) and initiates load shedding by removing loads whose locations are optimally determined by a sensitivity analysis. The amount and location of the load shedding depends on the location and size of the initiating event, making the proposed algorithm adaptive and selective. Case Studies have been presented to show that control actions of the proposed scheme can directly mitigate a cascading blackout. / Ph. D.