Power System State Estimation and Contingency Constrained Optimal Power Flow - A Numerically Robust Implementation

The research conducted in this dissertation is divided into two main parts. The first part provides further improvements in power system state estimation and the second part implements Contingency Constrained Optimal Power Flow (CCOPF) in a stochastic multiple contingency framework. As a real-time application in modern power systems, the existing Newton-QR state estimation algorithms are too slow and too fragile numerically. This dissertation presents a new and more robust method that is based on trust region techniques. A faster method was found among the class of Krylov subspace iterative methods, a robust implementation of the conjugate gradient method, called the LSQR method. Both algorithms have been tested against the widely used Newton-QR state estimator on the standard IEEE test networks. The trust region method-based state estimator was found to be very reliable under severe conditions (bad data, topological and parameter errors). This enhanced reliability justifies the additional time and computational effort required for its execution. The numerical simulations indicate that the iterative Newton-LSQR method is competitive in robustness with classical direct Newton-QR. The gain in computational efficiency has not come at the cost of solution reliability. The second part of the dissertation combines Sequential Quadratic Programming (SQP)-based CCOPF with Monte Carlo importance sampling to estimate the operating cost of multiple contingencies. We also developed an LP-based formulation for the CCOPF that can efficiently calculate Locational Marginal Prices (LMPs) under multiple contingencies. Based on Monte Carlo importance sampling idea, the proposed algorithm can stochastically assess the impact of multiple contingencies on LMP-congestion prices

Sequential Quadratic Programming-Based Contingency Constrained Optimal Power Flow

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

Istraživanje novog tehničko-tehnološkog rešenja u zasnivanju voćnjaka kombinovanim oruđem rigoler –razrivač u obradi zemljišta

Modern agriculture requires the use of modern technology, with new technical and technological solutions. Basic agro-technical operation in phase of establishing orchards and vineyards that requires large amounts of energy is plowing, for its specificity called rigoling. Trenching phase consumes greatest portion of energy int he processing and preparation of land in general and especially for the establishment of cultural agricultural fruit-grape production. There are more operational technologies, and this paper analyses classical technology, and combined technology using rigoler and plowing tools for soil cultivation. When classic technologies are applied, soil is cut and sectioned, moved and crushed, thus creating loose soil layer. The depth of processed soil is different for different fruitgrape crops, depending on the needs of the root system, as penetration depth and the breadth of development, ranging between 60 and 100 cm. Such technology moves active soil layer to the inactive bottom of the furrow, while inactive soil layer is removed to the surface. This technology has to be defined for different soil types. Combined technical-technological solution using a rigoler with built-in plow enables the achievement of working depth required by the root system, but the inactive soil layer is not moved to the surface of the plowed soil. The lower topsoil layer is only shaken and broken. Work technology combining rigoler and plow in one pass, can significantly increase technological production, while saving significant amounts of energy. This technology should be applied to avoid unnecessary expenditure of energy.U radu su prikazani rezultati ostvarenih vučnih otpora pri rigolovanju zemljišta sa plugom rigolerom na dubini od 60 cm, 70 cm, 80 cm i 90 cm, kao i vučni otpori rigolera sa dodatnim radnim organom u obliku dleta. Dodatkom dleta, dubina rigolovanja po varijantama rada, povećana je za 10 cm, 15 cm i 20 cm. Dobijeni rezultati pokazuju da na povećanim dubinama rigolovanja, specifičan otpor zemljišta ima nepromenjenu vrednost kao i pri samom rigolovanju. Ovo se postiže time što je odnos povećane dubine rigolovanja veći od povećanog vučnog otpora sa dodatkom dleta. Ekonomičnost upotrebe dleta je do 70 cm rigolovanja i 20 cm dubine rada dleta. Iznad 70 cm rigolovanja primena dleta se ekonomski smanjuje, jer se na toj dubini ispunjava agrotehnički zahtev