<p>Future development of electric power systems must pursue anumber of different goals. The power system should beeconomically efficient, it should provide reliable energysupply and should not damage the environment. At the same time,operation and development of the system is influenced by avariety of uncertain and random factors. The planner attemptsto find the best strategy from a large number of possiblealternatives. Thus, the complexity of the problems related topower systems planning is mainly caused by presence of multipleobjectives, uncertain information and large number ofvariables. This dissertation is devoted to consideration of themethods for development planning of a certain subsystem, i.e.the distribution network.</p><p>The dissertation first tries to formulate the networkplanning problem in general form in terms of Bayesian DecisionTheory. However, the difficulties associated with formulationof the utility functions make it almost impossible to apply theBayesian approach directly. Moreover, when approaching theproblem applying different methods it is important to considerthe concave character of the utility function. Thisconsideration directly leads to the multi-criteria formulationof the problem, since the decision is motivated not only by theexpected value of revenues (or losses), but also by theassociated risks. The conclusion is made that the difficultiescaused by the tremendous complexity of the problem can beovercome either by introducing a number of simplifications,leading to the considerable loss in precision or applyingmethods based on modifications of Monte-Carlo or fuzzyarithmetic and Genetic Algorithms (GA), or Dynamic Programming(DP).</p><p>In presence of uncertainty the planner aims at findingrobust and flexible plans to reducethe risk of considerablelosses. Several measures of risk are discussed. It is shownthat measuring risk by regret may lead to risky solutions,therefore an alternative measure - Expected Maximum Value - issuggested. The general future model, called fuzzy-probabilistictree of futures, integrates all classes of uncertain parameters(probabilistic, fuzzy and truly uncertain).</p><p>The suggested network planning software incorporates threeefficient applications of GA. The first algorithm searchessimultaneously for the whole set of Pareto optimal solutions.The hybrid GA/DP approach benefits from the global optimizationproperties of GA and local search by DP resulting in originalalgorithm with improved convergence properties. Finally, theStochastic GA can cope with noisy objective functions.</p><p>Finally, two real distribution network planning projectsdealing with primary distribution network in the large city andsecondary network in the rural area are studied.</p>

Thesis (Ph. D.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains xii, 191 p. : ill. Includes abstract. Includes bibliographical references (p. 182-191).

Thesis (Ph.D.)--University of Texas at Arlington, 2009.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 106-111). Also available on the Internet.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, December 2003. / Thesis advisor(s): Javier Salmeron, Kevin Wood. Includes bibliographical references (p. 101-102). Also available online.

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Dr. A. P. Meliopoulos; Committee Member: Dr. David Taylor; Committee Member: Dr. Ronald Harley; Committee Member: Dr. Shijie Deng. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 112-126).

Thesis (M.S.)--Ohio University, November, 2009. / Title from PDF t.p. Includes bibliographical references.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: contingency; interior point method; optimal power flow. Includes bibliographical references (p. 82-83).

M. Tech. Electrical Engineering. / Discusses that most real-time applications of synchronised phasor measurement units in power system stability studies are done using RTDS simulator, hardware PMUs and PTP hardware modules with GPS providing the time reference. The major drawbacks of this configuration are both technical and economical. The technical limitations are related to the possible number of outputs that can be used to interface PMU devices, which can be very limited; and also the possible limits on small-time step computation due to the big number of output signals. The economic constraints are mainly due to cost: for a research laboratory, only a limited number of units can be acquired due to budgeting issues. To overcome these difficulties, the realisation of an entirely software-based synchrophasor measurement unit, presents an attractive approach. Such a unit will be capable of deliveringreal-time data by acquiring the voltage and current signals from the Matlab/Simulink simulator, low cost software environment PMUs computing real-time phasors of voltage and current and software only PTP synchronisation protocol. The unit delivers synchrophasors for the application of power system SE and small signal stability analysis, but also taking into consideration the accuracy of the synchronisation protocol on the application of power system SE and small signal stability analysis.