Congestion in the transmission network in a power system may occur due to lack of coordination between generation and transmission utilities or as a result of unexpected contingencies such as line outages, sudden increase of load demand, or failure of equipments. The power dispatch is a nonlinear programming problem. It is classified into two parts namely real and reactive power dispatch problems. The reactive power dispatch helps to minimize the real power loss in a transmission network. The real power dispatch is the most widely used control for network overload alleviation because of ease of control and require no additional reserves.
Optimal power flow (OPF) is an important tool for power system management. The aim of OPF problem is to optimize one or more objectives by adjusting the power system control variables while satisfying a set of physical and operating constraints such as generation and load balance, bus voltage limits, power flow equations and active and reactive power limits. A variety of optimization techniques have been applied to solve the OPF problem such as gradient method [1], linear programming method [2] and interior point method. In conventional optimization methods, identification of global minimum is not possible. To overcome the difficulty, evolutionary algorithms like genetic Algorithm [3], particle swarm optimization [4], differential evolution [5], gravitational search algorithm [6], harmony search method [7] and artificial bee colony optimization [8] have been proposed.
In [9], the authors’ proposed a fuzzy logic based approach to alleviate the network overloads by generation rescheduling. The generation shift sensitivity factor (GSSF) was used to decide the changes in generati...
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...olution (DE). The algorithm improves the loadability margin with less number of iterations by consuming more time per iteration when compared to other algorithms.
In this paper, a fuzzy ranking based non-dominated sorting genetic algorithm-II for overload management in power system network is presented with illustrated example.
The organization of the paper is as follows: Section 2 presents the optimization problem formulation for transmission line management. Sections 3, 4, 5 and 6 explain the overview of PSO, DE, NSGA-II and Fuzzy ranking method. In section 7 the algorithm of proposed NSGA-II in solving the network overload alleviation is presented. The simulation results for different contingency cases in IEEE 30 and IEEE 118 bus systems are presented in section 8. Finally, conclusions are given in Section 9.
On August 14th, 2003, a major blackout swept across portions of the northeastern United States and Canada. It was reported that a series of equipment outages in the Midwest led to uncontrolled cascading outages of power transmission lines and generators serving parts of the Northeast, Midwest and Canada. Automatic protective systems operated to open circuits and shut down power plants to prevent further spread of the outages. This is very similar to what happened in The Great Northeast Blackout of 1965. In both situations, the “grid system” shut down one generator in line at a time to protect a surge from the station before it.
In some low power densities areas, utilities are connected to an existing transmission line using a tapped line because of economic advantages. Such a configuration of transmission lines presents great difficulty in the task of fault location when the fault resistance is not negligible due to the infeed currents from different sources.
Disclaimer; this is intended to be an introductory technical article; certain details have been excluded in the interests of space and clarity. Network design examples are presented to illustrate specific technical points and are not intended to fully complete.
...ment and Control System for Increasing Transmission Capacity in Deregulated Energy Markets. Proc. 2002 Power Systems Computation Conference in Sevilla, (2002).
Besides the calculation of electrical characteristics of the power system, power flow analysis can also help to optimize the system operating conditions and minimize the power losses [19].
Cianfrani, A., Eramo, V., Listanti, M., Polverini, M., & Vasilakos, A.V. (2012). An OSPF-integrated routing strategy for Qos-aware energy saving in IP backbone networks. IEEE Transactions on Network & Service Management, 9(3), 254. doi: 10.1109/TNSM.2012.031512.110165
The superscript (new) distinguishes the elements of the new (n-1)×(n-1) Y_bus from the original ×n Y_bus. Every step of the Gaussian elimination yields an equivalent circuit of the network at the base case. If the network is reduced to r nodes, a new bus admittance matrix of dimension r×r, and a new current injection vector of dimension r×1 are obtained. This reduced network carries full information of the original power system at the base case.
For the prevantion of the electricity blackout we need to build smart power grid. A modernized electrical grid that uses analog or digital information and communications technology to gather and act on information, such as information about the behaviours of suppliers and consumers is known as a smart grid. This is used to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity in an automated fashion[12]. The important aspects of smart grid is to electronic power conditioning and control of the production and distribution of
Different objective functions generate different solutions even form the same evolutionary algorithm. Presuming also that the fitness could either be a minimization or a maximization function. Moreover, the algorithm could be formulated with one or with multi objective functions. To sum up, "choosing optimizati...
[10] L.Xiaotong, L.Yimei, Z. Xiaoli, and Z.Ming “Generation and Transmission Expansion Planning Based on Game Theory in Power Engineering” Systems Engineering Procedia 4 (2012) 79 – 86.
Abstract—Computational problems have significance from the early civilizations. These problems and solutions are used for the study of universe. Numbers and symbols have been used for different fields e.g. mathematics, statistics. After the emergence of computers the number and objects needs to be arranged in a particular order i.e. ascending and descending orders. The ordering of these numbers is generally referred to as sorting. Sorting gained a lot of importance in computer sciences and its applications are in file systems etc. A number of sorting algorithms have been proposed with different time and space complexities. In this paper author will propose a new sorting algorithm i.e. Relative Split and Concatenate Sort, implement the algorithm and then compared results with some of the existing sorting algorithms. Algorithm’s time and space complexity will also be the part of this paper.
Multiple constraint satisfaction problems (MCSP) is a problem in which a set of values must meet a number of constraints. it has been widely used in AI to solve a wide range of problems. In this thesis we use MCSP to solve the load balancing proble. Therefore, we first review the different algorithms in MCSP and the Dynamic MCSP then we review the load balancing problem.
...imal solution. Then, a simulation method is developed to compare the centralized and decentralized SCs. In addition, to reach the near optimal solution in the centralized model, evolution strategy (ES) algorithm and imperialist competitive algorithm (ICA) as meta-heuristic approaches are applied.
My undergraduate studies got me interested in the application of mathematics in engineering and I topped the subject in my second year of engineering and was also a University Rank Holder (9th). Mathematics simplifies concepts into numbers, constants, variables and equations and that helps to predict some complex outcomes. A power system per se is a simple set of interconnected electrical and mechanical components, but their unified behavior is a very complex phenomenon. Efficient generation, transmission, distribution and usage of electric power require thorough understanding of this network behavior. Increasing power demands and meshing of multiple & complex networks into super grids demand superior system designs and ultimate built in operational control. Without mathematics, this engineering complexity cannot be analyzed, ...
Generates a population of points for each iteration, leading to multiple options for solution out of which the best is to be selected.