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Multi-objective unit commitment problem using Cuckoo search Lagrangian method
K Chandrasekaran, SP Simon
International Journal of Engineering, Science and Technology , 2012,
Abstract: Restructuring of power system changed the mechanism of reliability management in solving the unit commitment problem (UCP). In general, operating reserve capacity is predetermined either by dispatch rules or predefined by reliability index. This paper considers that the operating reserve capacity in a power system is bendable, which is based on the cost-reliability issues. In UCP, these two competing objectives such as fuel cost and reliability level of the system were optimized simultaneously, as a multi-objective unit commitment problem (MOUCP), using the proposed fuzzy integrated binary real coded cuckoo search Lagrangian (BCSL) algorithm. The ON/OFF status of the thermal power units is obtained by binary coded cuckoo search algorithm (CSA), where as the economic dispatch is obtained by Lagrangian multiplier method. The fuzzy set theory is used to pick up the best compromise solution. The proposed methodology is tested and validated for both the single and multi-objective UCP. The effectiveness of the proposed technique is demonstrated on IEEE RTS 24 bus system by comparing its performance with other methods reported in the literature.
Particle swarm optimization technique to solve unit commitment problem  [PDF]
P.V. Rama Krishna, G. Poornachandra Rao, Dr Sukhdeo Sao
International Journal of Advanced Computer Research , 2012,
Abstract: Unit commitment problem is one of the major problems in power system operation and control. The determination of time intervals at which a particular unit to be on and off, satisfying various constraints is a multi constrained complex optimization problem. In this paper we have used Particle swarm optimization technique which is population based global searching optimization technique is applied to solve unit commitment problem, for optimum unit commitment schedule. With the application of PSO algorithm it is easy to update the lagrangian multipliers, useful to sub divide the main problem in to a number of sub problem. Single unit dynamic programming is used to solve for each unit so that the total cost can be minimized over a scheduling period of time.
Lagrangian Relaxation-Based Unit Commitment Considering Fast Response Reserve Constraints  [PDF]
C. S. Chuang, G. W. Chang
Energy and Power Engineering (EPE) , 2013, DOI: 10.4236/epe.2013.54B186
Abstract:

Unit commitment (UC) is to determine the optimal unit status and generation level during each time interval of the scheduled period. The purpose of UC is to minimize the total generation cost while satisfying system demand, reserve requirements, and unit constraints. Among the UC constraints, an adequate provision of reserve is important to ensure the security of power system and the fast-response reserve is essential to bring system frequency back to acceptable level following the loss of an online unit within a few seconds. In this paper, the authors present and solve a UC problem including the frequency-based reserve constraints to determine the optimal FRR requirements and unit MW schedules. The UC problem is solved by using Lagrangian Relaxation-based approach and compared with the actual system schedules. It is observed that favorable reserve and unit MW schedules are obtained by the proposed method while the system security is maintained.

Solving the unit commitment problem of hydropower plants via Lagrangian Relaxation and Sequential Quadratic Programming
Finardi, Erlon C.;Silva, Edson L. da;Sagastizábal, Claudia;
Computational & Applied Mathematics , 2005, DOI: 10.1590/S0101-82052005000300001
Abstract: we consider the optimal scheduling of hydropower plants in a hydrothermal interconnected system. this problem, of outmost importance for large-scale power systems with a high proportion of hydraulic generation, requires a detailed description of the so-called hydro unit production function. in our model, we relate the amount of generated hydropower to nonlinear tailrace levels; we also take into account hydraulic losses, turbine-generator efficiencies, as well as multiple 0-1 states associated with forbidden operation zones. forbidden zones are crucial to avoid nasty phenomena such as mechanical vibrations in the turbine, cavitation, and low efficiency levels. the minimization of operating costs subject to such detailed constraints results in a large-scale mixed-integer nonlinear programming problem. by means of lagrangian relaxation, the original problem is split into a sequence of smaller and easy-to-solve subproblems, coordinated by a dual master program. in order to deal better with the combinatorial aspect introduced by the forbidden zones, we derive three different decomposition strategies, applicable to various configurations of hydro plants (with few or many units, which can be identical or different). we use a sequential quadratic programming algorithm to solve nonlinear subproblems. we assess our approach on a real-life hydroelectric configuration extracted from the south sub region of the brazilian hydrothermal power system.
Solving the unit commitment problem of hydropower plants via Lagrangian Relaxation and Sequential Quadratic Programming  [cached]
Erlon C. Finardi,Edson L. da Silva,Claudia Sagastizábal
Computational and Applied Mathematics , 2005,
Abstract: We consider the optimal scheduling of hydropower plants in a hydrothermal interconnected system. This problem, of outmost importance for large-scale power systems with a high proportion of hydraulic generation, requires a detailed description of the so-called hydro unit production function. In our model, we relate the amount of generated hydropower to nonlinear tailrace levels; we also take into account hydraulic losses, turbine-generator efficiencies, as well as multiple 0-1 states associated with forbidden operation zones. Forbidden zones are crucial to avoid nasty phenomena such as mechanical vibrations in the turbine, cavitation, and low efficiency levels. The minimization of operating costs subject to such detailed constraints results in a large-scale mixed-integer nonlinear programming problem. By means of Lagrangian Relaxation, the original problem is split into a sequence of smaller and easy-to-solve subproblems, coordinated by a dual master program. In order to deal better with the combinatorial aspect introduced by the forbidden zones, we derive three different decomposition strategies, applicable to various configurations of hydro plants (with few or many units, which can be identical or different). We use a Sequential Quadratic Programming algorithm to solve nonlinear subproblems. We assess our approach on a real-life hydroelectric configuration extracted from the south sub region of the Brazilian hydrothermal power system.
The Judging Standard and the Identification of Corporate DNA  [cached]
Xianbai Li
International Journal of Business and Management , 2009,
Abstract: Based on the characteristics of germ plasm, the author presents the judging standard on corporate DNA. That is the corporate DNA should have the characteristics of stability, control, variability and replication. Judging by this standard, the corporate DNA is composed of four chains, namely the corporate system, the corporate culture, the adapting mechanism to environment, and the adapting system to relevant theories and laws. The corporate DNA is composed of a double chain. And the four DNA chains are overlapped and intercross.
Quick HyperVolume  [PDF]
Luís M. S. Russo,Alexandre P. Francisco
Computer Science , 2012,
Abstract: We present a new algorithm to calculate exact hypervolumes. Given a set of $d$-dimensional points, it computes the hypervolume of the dominated space. Determining this value is an important subroutine of Multiobjective Evolutionary Algorithms (MOEAs). We analyze the "Quick Hypervolume" (QHV) algorithm theoretically and experimentally. The theoretical results are a significant contribution to the current state of the art. Moreover the experimental performance is also very competitive, compared with existing exact hypervolume algorithms. A full description of the algorithm is currently submitted to IEEE Transactions on Evolutionary Computation.
Quick Summary  [PDF]
Robert Wahlstedt
Computer Science , 2012,
Abstract: Quick Summary is an innovate implementation of an automatic document summarizer that inputs a document in the English language and evaluates each sentence. The scanner or evaluator determines criteria based on its grammatical structure and place in the paragraph. The program then asks the user to specify the number of sentences the person wishes to highlight. For example should the user ask to have three of the most important sentences, it would highlight the first and most important sentence in green. Commonly this is the sentence containing the conclusion. Then Quick Summary finds the second most important sentence usually called a satellite and highlights it in yellow. This is usually the topic sentence. Then the program finds the third most important sentence and highlights it in red. The implementations of this technology are useful in a society of information overload when a person typically receives 42 emails a day (Microsoft). The paper also is a candid look at difficulty that machine learning has in textural translating. However, it speaks on how to overcome the obstacles that historically prevented progress. This paper proposes mathematical meta-data criteria that justify the place of importance of a sentence. Just as tools for the study of relational symmetry in bio-informatics, this tool seeks to classify words with greater clarity. "Survey Finds Workers Average Only Three Productive Days per Week." Microsoft News Center. Microsoft. Web. 31 Mar. 2012.
Security-Constrained Unit Commitment Based on a Realizable Energy Delivery Formulation
Hongyu Wu,Qiaozhu Zhai,Xiaohong Guan,Feng Gao,Hongxing Ye
Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/178193
Abstract: Security-constrained unit commitment (SCUC) is an important tool for independent system operators in the day-ahead electric power market. A serious issue arises that the energy realizability of the staircase generation schedules obtained in traditional SCUC cannot be guaranteed. This paper focuses on addressing this issue, and the basic idea is to formulate the power output of thermal units as piecewise-linear function. All individual unit constraints and systemwide constraints are then reformulated. The new SCUC formulation is solved within the Lagrangian relaxation (LR) framework, in which a double dynamic programming method is developed to solve individual unit subproblems. Numerical testing is performed for a 6-bus system and an IEEE 118-bus system on Microsoft Visual C# .NET platform. It is shown that the energy realizability of generation schedules obtained from the new formulation is guaranteed. Comparative case study is conducted between LR and mixed integer linear programming (MILP) in solving the new formulation. Numerical results show that the near-optimal solution can be obtained efficiently by the proposed LR-based method.
Security Constraint Unit Commitment Considering Line and Unit Contingencies- Particle Swarm Optimization  [cached]
Mohammad Sadegh Javadi
International Journal of Applied Power Engineering , 2012, DOI: 10.11591/ijape.v1i1.433
Abstract: This paper presents a new approach for considering all possible contingencies in short-term power system operation. Based on this new approach, both generator and transmission line outages would be modeled in network-based power system analysis. Multi generator and also parallel transmission lines is modeled in this methodology. We also investigate this claim that feasibility and applicability of this approach is much more than the previous analytical methodologies. Security Constrained Unit commitment (SCUC) program which is carried out by Independent System Operator (ISO), is one of the complex problems which would be handled by this approach. In this paper, a DC-Optimal Power Flow (DCOPF) methodology has been implemented by particle swarm optimization technique. The Lagrangian Relaxation technique is based on the derivatives and the PSO is a non- derivative technique. These approaches are effective tools which can be implemented for short-term and long-term power system analysis, especially for economic analysis of restructured power systems. The DCOPF methodology has been considered for LMP calculation in LR, which is not available in PSO techniques. In the other hand, PSO technique may be able to provide the optimal solution, where LR usually getting stuck at a local optimum in a large scale power system. The simulation results show that the presented methods are both satisfactory and consistent with expectation.
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