The focus of this thesis is formulation and development of a mathematical framework for the solution of the contingency constrained optimal power flow (OPF) based on sequential quadratic programming. The contingency constrained optimal power flow minimizes the total cost of a base case operating state as well as the expected cost of recovery from contingencies such as line or generation outages. The sequential quadratic programming (SCP) OPF formulation has been expanded in order to recognize contingency conditions and the problem is solved as a single entity by an efficient interior point method. The new formulation takes into account the system corrective capabilities in response to contingencies introduced through ramp-rate constraints. Contingency constrained OPF is a very challenging problem, because each contingency considered introduces a new problem as large as the base case problem. By proper system reduction and benefits of constraint relaxation (active set) methods, in which transmission constraints are not introduced until they are violated, the size of the system can be reduced significantly Therefore, restricting our attention to the active set constraint set makes this large problem significantly smaller and computationally feasible.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Vita. / Includes bibliographical references. / by Pierre Dersin. / Ph.D.

Two studies are presented quantifying the impact of plug-in hybrid vehicles (PHEVs) on power systems. The first study quantifies this impact in terms of (a) primary fuel utilization shifts, (b) pollution shifts, and (c) total cost for consumers. The second study quantifies this impact on distribution transformers. In the first study vehicle and power system simulations are used to compute the expected power system fuels utilized to meet a projected level of power demand. The projected electric power demand includes business as usual electric load and random PHEV charging electric load. In the second study the impact on distribution transformers is quantified through a loss of life calculation. The loss of life calculation is based on distribution transformer hot-spot temperature. The hot-spot temperature is estimated using an electro-thermal distribution transformer model and is a function of the transformer currents. The transformer currents are computed using a center-tapped single phase transformer model. Random business as usual and PHEV charging electric loading is assumed.

Thesis (MTech(Electrical Engineering))--Cape Peninsula University of Technology, 2011 / In a situation, where there is a shortage of power generation or the power stations are operating with a very low reserve margin, as is typically the current position in South Africa, there is a need to operate distribution network at the highest possible efficiency by utilising network power loss reduction techniques. Such techniques are especially important when contingencies occur as they tend to increase loss, reduce efficiencies and cause power supplies to such networks to increase. This increase can cause the network or multiples of such networks to be load shed as the power stations do not have the reserve margins to meet this increased demand. The ideal situation would thus be to minimise network loss and in so doing decrease the amount of power needed and possibly avoid load shedding. Thus, there is a need to study efficiency, network loss reduction under contingency conditions and this is the focus of the research. Most large urban distribution networks are operated as ring main networks. Ring networks are considered to have less power loss. However, a major component in a ring network can cause the loss to substantially increase; resulting in power shortage in the network. There is an urgency to eliminate high network loss. An efficiency plan was developed for a large ring network that reduces the loss so that its input power can be decreased. In this way, the available power existing due to the contingency can be more evenly spread, and the number of ring main networks to be load shed could be reduced.

D.Ing. / This thesis initially reviews current empirical and probabilistic electrical load models available to distribution design engineers today to calculate voltage regulation levels in low voltage residential, commercial and light industrial consumer networks. Although both empirical and probabilistic techniques have extensively been used for residential consumers in recent years, it has been concluded that commercial and light industrial consumer loads have not been a focus area of probabilistic load study for purposes of low voltage feeder design. However, traditional empirical techniques, which include adjustments for diversity to accommodate non-coincidental electrical loading conditions, have generally been found to be applied using in-house design directives with only a few international publications attempting to address the problem. This work defines the light industrial group of consumers in accordance with its international Standard Industrial Classification (SIC) and presents case studies on a small group of three different types of light industrial sub-classes, It is proposed and proved that the electrical load models can satisfactorily be described as beta-distributed load current models at the instant of group or individual maximum power demand on typical characteristic 24-hour load cycles. Characteristic mean load profiles were obtained by recording repetitive daily loading of different sub-classes, ensuring adequate sample size at all times. Probabilistic modelling of light industrial loads using beta-distributed load current at maximum demand is a new innovation in the modelling of light industrial loads. This work is further -complemented by the development of a new probabilistic summation algorithm in spreadsheet format. This algorithm adds any selected number of characteristic load current profiles, adjusted for scale, power factor, and load current imbalance, and identifies the combined instant of group or system maximum demand. This spreadsheet also calculates the characteristic beta pdf parameters per phase describing the spread and profile of the combined system loading at maximum demand. These parameters are then conveniently used as input values to existing probabilistic voltage regulation algorithms to calculate voltage regulation in single-, bi- and three-phase low voltage distribution networks.

The effects of interphase coupling in a multiphase power system become important in the presence of network imbalances and unbalanced phase loadings. In grounded-wye systems, currents that flow in the earth can have significant effects on the system's behavior. Both these effects must be considered in an accurate multiphase power system model. A new treatment of multiphase power system modeling is presented. The treatment relies upon linear graph theory and produces a system multiport model. Mutual coupling effects, the effects of neutral and static conductors, the finite conductivity of earth, and various component models are considered. A reduction in the order of the multiport model also is presented. Multiphase load flow analysis is introduced. Special considerations that arise in multiphase analyses are discussed. Example solutions are presented. A convenient method of representing multiple slack ports is described which results from an application of the principle of superposition. Circulating power flow in multiphase loops is discussed. A procedure is proposed for conveniently representing common shunt and series faults that occur in power systems. The procedure is constructed for efficient computer modeling of multiple cases of various fault combinations in a particular system. / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

The objective of the proposed research is to analyze automated residential energy management technology using primary energy source utilization. A residential energy management system (REMS) is an amalgamation of hardware and software that performs residential energy usage monitoring, planning, and control. Primary energy source utilization quantifies power system levels impacts on power generation cost, fuel utilization, and environmental air pollution; based on power system generating constraints and electric load. Automated residential energy management technology performance is quantified through a physically-based REMS simulation. This simulation includes individual appliance operation and accounts for consumer behavior by stochastically varying appliance usage and repeating multiple simulation iterations for each simulated scenario. The effect of the automated REMS under varying levels of control will be considered. Aggregate REMS power system impacts are quantified using primary energy source utilization. This analysis uses a probabilistic economic dispatch algorithm. The economic dispatch algorithm quantifies: fuel usage and subsequent environmental air pollution (EAP) generated; based on power system generating constraints and electric load (no transmission constraints are considered). The analysis will comprehensively explore multiple residential energy management options to achieve demand response. The physically-based REMS simulation will consider the following control options: programmable thermostat, direct load control, smart appliance scheduling, and smart appliance scheduling with a stationary battery. The ability to compare multiple automated residential energy management technology options on an equal basis will guide utility technology investment strategies.