Antlion optimization algorithm for optimal non-smooth economic load dispatch

This paper presents applications of Antlion optimization algorithm (ALO) for handling optimal economic load dispatch (OELD) problems. Electricity generation cost minimization by controlling power output of all available generating units is a major goal of the problem. ALO is a metaheuristic algorithm based on the hunting process of Antlions. The effect of ALO is investigated by solving a 10-unit system. Each studied case has different objective function and complex level of restraints. Three test cases are employed and arranged according to the complex level in which the first one only considers multi fuel sources while the second case is more complicated by taking valve point loading effects into account. And, the third case is the highest challenge to ALO since the valve effects together with ramp rate limits, prohibited operating zones and spinning reserve constraints are taken into consideration. The comparisons of the result obtained by ALO and other ones indicate the ALO algorithm is more potential than most methods on the solution, the stabilization, and the convergence velocity. Therefore, the ALO method is an effective and promising tool for systems with multi fuel sources and considering complicated constraints

Non-convex constrained economic power dispatch with prohibited operating zones and piecewise quadratic cost functions

This paper is focused on the solution of the non-convex economic power dispatch problem with piecewise quadratic cost functions and practical operation constraints of generation units. The constraints of the economic dispatch problem are power balance constraint, generation limits constraint, prohibited operating zones and transmission power losses. To solve this problem, a meta-heuristic optimization algorithm named crow search algorithm is proposed. A constraint handling technique is also implemented to satisfy the constraints effectively. For the verification of the effectiveness and the superiority of the proposed algorithm, it is tested on 6-unit, 10-unit and 15-unit test systems. The simulation results and statistical analysis show the efficiency of the proposed algorithm. Also, the results confirm the superiority and the high-quality solutions of the proposed algorithm when compared to the other reported algorithms

Aplikasi sistem penuaian air hujan (SPAH) di kawasan perumahan

Pada masa kini, kekurangan sumber air bersih merupakan satu ancaman di kebanyakkan negara, dan tidak terkecuali Malaysia. Keadaan ini adalah disebabkan oleh kaedah penggunaan sumber air yang tidak berkesan serta kemusnahan kawasan tadahan air disebabkan oleh pembangunan pesat yang tidak mematuhi peraturan. Sebagai alternatif untuk mengatasi masalah ini, Sistem Penuaian Air Hujan (SPAH) telah diperkenalkan sebagai kaedah pengurusan terbaik dalam amalan pengurusan air yang berkesan di Malaysia. Sistem ini bertujuan untuk melambatkan aliran air larian permukaan dan untuk menggalakkan penggunaan air secara efisien. Kajian ini dijalankan adalah untuk menentukan pelaksanaan Sistem Penuaian Air Hujan (SPAH), serta untuk menilai keberkesanan pelaksanaan Sistem Penuaian Air Hujan (SPAH). Hasil dapatan kajian ini adalah berdasarkan data yang dikumpul melalui siri-siri temubual yang dilaksanakan dengan enam orang responden iaitu Pemaju harta tanah, Pihak Berkuasa Tempatan, dan Kontraktor. Dapatan kajian menunjukkan bahawa tangki Penuaian Air Hujan yang sesuai untuk unit kediaman adalah dianggarkan bersaiz 200 gelen (50-60m3), dan jumlah kos pemasangan adalah RM 3000.00 seunit. Merujuk kepada keberkesanan pelaksanaan Sistem Penuaian Air Hujan (SPAH), majoriti responden berpuashati bahawa sistem yang digunakan memadai untuk mengawal masalah pembaziran gunaan air serta mampu menjimatkan penawaran air bersih. Diharapkan supaya dapatan kajian ini akan membantu untuk menyeimbangkan kegunaan air dan keperluan pembangunan air untuk generasi akan datang

Solving practical economic load dispatch problem using crow search algorithm

The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other reported algorithms. The comparison of results confirm the high-quality solutions and the effectiveness of the proposed method for solving the non-convex practical economic load dispatch problem

Solving economic dispatch problem using particle swarm optimization

This project presents a new approach to solve Economic Dispatch (ED) using Particle Swarm Optimization (PSO) technique with consideration of several generators constraints to search the optimal solution and the minimum of total generation operating cost. Conventional optimization methods assume generator cost curves to be continuous and monotonically increasing, but modern generators have a variety of nonlinearities in their cost curves making this assumption inaccurate, and the resulting approximate dispatches cause a lot of revenue loss. In PSO technique, the movement of a particle is governed by three behaviors namely, inertial, cognitive, and social. The cognitive behavior helps the particle to remember its previously visited best position. This technique helps to explore the search space very effectively. The proposed method considers the nonlinear characteristics of a generator such as ramp rate limits, power balance constraints with maximum and minimum operating limits and prohibited operating zone for actual power system operation. The practicality of the proposed method was demonstrated for different cases on 6-unit generation system and 15-unit generation system based on IEEE standard operation. The PSO algorithms with the proposed objective function are being considered efficient in solving this kind of models. Also, PSO has been successfully applied in many complex optimization problems in power systems. The proposed function approach was first tested on some less complex systems and then the effectiveness of the PSO was compared with the research studies from several references of studied papers

Smart real-time scheduling of generation units in an electricity market considering environmental aspects and physical constraints of generators.

Doctor of Philosophy in Electrical Engineering. University of KwaZulu-Natal, Durban 2017.Abstract available in PDF file

Load dispatch optimization of open cycle industrial gas turbine plant incorporating operational, maintenance and environmental parameters

Power generation fuel cost, unit availability and environmental rules and regulations are important parameters in power generation load dispatch optimization. Previous optimization work has not considered the later two in their formulations. The objective of this work is to develop a multi-objective optimization model and optimization algorithm for load dispatching optimization of open cycle gas turbine plant that not only consider operational parameters, but also incorporates maintenance and environmental parameters. Gas turbine performance parameters with reference to ASME PTC 22-1985 were developed and validated against an installed performance monitoring system (PMS9000) and plant performance test report. A gas turbine input-output model and emission were defined mathematically into the optimization multi-objectives function. Maintenance parameters of Equivalent Operating Hours (EOH) constraints and environmental parameters of allowable emission (NOx, CO and SO2) limits constraints were also included. The Extended Priority List and Particle Swarm Optimization (EPL-PSO) method was successfully implemented to solve the model. Four simulation tests were conducted to study and test the develop optimization software. Simulation results successfully demonstrated that multi-objectives total production cost (TPC) objective functions, the proposed EOH constraint, emissions model and constraints algorithm could be incorporated into the EPL-PSO method which provided optimum results, without violating any of the constraints as defined. A cost saving of 0.685% and 0.1157% could be obtained based on simulations conducted on actual plant condition and against benchmark problem respectively. The results of this work can be used for actual plant application and future development work for new gas turbine model or to include additional operational constraint

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion