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A study of cost-optimized operation of a grid-parallel PEM fuel cell power plant

IEEE TRANSACTIONS ON POWER SYSTEMS 2006年第3期21卷 1104-1114页

作者： El-Sharkh, M. Y. Tanrioven, M. Rahman, A. Alam, M. S. Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

A cost-based approach is developed to study the economics of operation of the proton exchange membrane (PEM) fuel cell power plants (FCPP). This paper includes the operational cost, thermal recovery, power trade with,the local grid, and hydrogen production. The cost-based approach is used to determine the optimal operational strategy that yields a minimum operating cost. The optimal operational strategy is achieved through the estimation of the hourly generated power, the amount of thermal power recovered from the FCPP to satisfy the thermal load, the amount of power trade with the local grid, and the amount of hydrogen that can be generated from the FCPP. An evolutionary programming-based technique is used to determine the optimal operational strategy. The strategy is tested using electrical and thermal load profiles. Results are encouraging and indicate the effectiveness of the proposed approach.

关键词： evolutionary programming fuel cell fuel cell cost-based approach proton exchange membrane (PEM) fuel cell

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JOURNAL OF POWER SOURCES 2006年第2期161卷 1198-1207页

作者： El-Sharkh, M. Y. Tanrioven, M. Rahman, A. Alam, M. S. Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

Fuel cell power plants (FCPP) as a combined source of heat, power and hydrogen (CHP&H) can be considered as a potential option to supply both thermal and electrical loads. Hydrogen produced from the FCPP can be stored for future use of the FCPP or can be sold for profit. In such a system, tariff rates for purchasing or selling electricity, the fuel cost for the FCPP/thermal load, and hydrogen selling price are the main factors that affect the operational strategy. This paper presents a hybrid evolutionary programming and Hill-Climbing based approach to evaluate the impact of change of the above mentioned cost parameters on the optimal operational strategy of the FCPP. The optimal operational strategy of the FCPP for different tariffs is achieved through the estimation of the following: hourly generated power, the amount of thermal power recovered, power trade with the local grid, and the quantity of hydrogen that can be produced. Results show the importance of optimizing system cost parameters in order to minimize overall operating cost. (c) 2006 Elsevier B.V. All rights reserved.

关键词： fuel cell economics PEM fuel cell evolutionary programming sensitivity analysis

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Impact of hydrogen production on optimal economic operation of a grid-parallel PEM fuel cell power plant

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JOURNAL OF POWER SOURCES 2006年第1期153卷 136-144页

作者： El-Sharkh, MY Tanrioven, M Rahman, A Alam, MS Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

This paper presents an economic model of a PEM fuel cell power plant (FCPP). The model includes the operational cost, thermal recovery, power trade with the local grid, and hydrogen production. The model is used to determine the optimal operational strategy, which yields the minimum operating cost. The optimal operational strategy is achieved through estimation of the following: hourly generated power, thermal power recovered from the FCPP, power trade with the local grid, and hydrogen production. An evolutionary programming-based technique is used to solve for the optimal operational strategy. The model is tested using different seasonal load demands. The results illustrate the impact of producing hydrogen on the operational strategies of the FCPP when subjected to seasonal load variation. Results are encouraging and indicate viability of the proposed model. (c) 2005 Elsevier B.V. All rights reserved.

关键词： fuel cell hydrogen PEM fuel cell economical fuel cell model evolutionary programming

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Evaluation of liquefaction induced lateral displacements using genetic programming

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COMPUTERS AND GEOTECHNICS 2006年第4-5期33卷 222-233页

作者： Javadi, Akbar A. Rezania, Mohammad Nezhad, Mohaddeseh Mousavi Univ Exeter Dept Engn Exeter EX4 4QF Devon England Ferdowsi Univ Mashhad Dept Engn Mashhad Iran

Determination of liquefaction induced lateral displacements during earthquake is a complex geotechnical engineering problem due to the complex and heterogeneous nature of the soils and the participation of a large number of factors involved. In this paper, a new approach is presented, based on genetic programming (GP), for determination of liquefaction induced lateral spreading. The GP models are trained and validated using a database of SPT-based case histories. Separate models are presented to estimate lateral displacements for free face and for gently sloping ground conditions. It is shown that the GP models are able to learn, with a very high accuracy, the complex relationship between lateral spreading and its contributing factors in the form of a function. The attained function can then be used to generalize the learning to predict liquefaction induced lateral spreading for new cases not used in the construction of the model. The results of the developed GP models are compared with those of a commonly used multi linear regression (MLR) model and the advantages of the proposed GP model over the conventional method are highlighted. (C) 2006 Elsevier Ltd. All rights reserved.

关键词： geotechnical models soil liquefaction earthquake evolutionary computation evolutionary programming lateral displacement

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Serengeti wildebeest migratory patterns modeled from rainfall and new vegetation growth

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ECOLOGY 2006年第8期87卷 1987-1994页

作者： Boone, Randall B. Thirgood, Simon J. Hopcraft, J. Grant C. Colorado State Univ Nat Resource Ecol Lab Ft Collins CO 80523 USA Univ Groningen Community & Conservat Ecol Grp NL-9750 AA Haren Netherlands Macauley Inst Aberdeen Scotland Frankfurt Zool Soc Arusha Tanzania

We used evolutionary programming to model innate migratory pathways of wildebeest in the Serengeti Mara Ecosystem, Tanzania and Kenya. Wildebeest annually move from the southern short-grass plains of the Serengeti to the northern woodlands of the Mara. We used satellite images to create 12 average monthly and 180 10-day surfaces from 1998 to 2003 of percentage rainfall and new vegetation. The surfaces were combined in five additive and three multiplicative models, with the weightings on rainfall and new vegetation from 0% to 100%. Modeled wildebeest were first assigned random migration pathways. In simulated generations, animals best able to access rainfall and vegetation were retained, and they produced offspring with similar migratory pathways. Modeling proceeded until the best pathway was stable. In a learning phase, modeling continued with the ten-day images in the objective function. The additive model, influenced 25% by rainfall and 75% by vegetation growth, yielded the best agreement, with a multi-resolution comparison to observed densities yielding 76.8% of blocks in agreement (kappa 0.32). Agreement was best for dry season and early wet season (kappa 0.22-0.57), and poorest for the late wet season (0.04). The model suggests that new forage growth is a dominant correlate of wildebeest migration.

关键词： Connochaetes taurinus evolutionary programming migration NDVI rainfall estimates Serengeti Mara Ecosystem wildebeest

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Comparison of modern optimization techniques with applications to single-phase induction motor design

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2006年第5期34卷 497-507页

作者： Subramanian, S Bhuvaneswari, R Annamalai Univ Dept Elect Engn Fac Engn & Technol Annamalainagar 608002 Tamil Nadu India

The need for energy conservation necessitates increased levels of induction motor efficiency. It is therefore important to optimize the efficiency of the induction motor if significant energy savings are to be obtained. To optimize the efficiency, the design of the induction motor has to be chosen appropriately. Here we present a comparative study of the various soft computing techniques and their applications to the optimum design of single phase induction motors. The process of optimization has been carried out by using simulated annealing, radial basis function networks, and evolutionary programming. These methods are tested on two sample motors, and the results are compared with conventional design results.

关键词： design optimization of single phase induction motor simulated annealing radial basis function network evolutionary programming

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Improved fast evolutionary program for optimum design of power transformer

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COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2006年第4期25卷 995-1006页

作者： Subramanian, S. Bhuvaneswari, R. Annamalai Univ Fac Engn & Technol Dept Elect Engn Annamalainagar 608002 Tamil Nadu India

Purpose - The power transformer is one of the most important pieces of equipment in a power system. The necessity for the optimum design of a power transformer arises because the design chosen should satisfy all the limitations and restrictions placed on it. This paper presents an improved fast evolutionary programming (IFEP) technique for the optimal design of a three-phase power transformer. Design/methodology/approach - The optimization of the transformer design problem is formulated as an NLP problem, expressing the objective and constraint functions in terms of the selected independent variables. Here the cost of the transformer is considered as the objective function and is the sum of material cost of stampings and copper windings, cost of cooling tube arrangements, cost of cooling medium, insulation cost and labour cost. A computer program is written from which the optimal design parameters are obtained. For optimization, the classical evolutionary programming (CEP) technique and its variant the IFEP technique are used and the results are compared. Findings - The application of CEP and IFEP for transformer design has been demonstrated on two test cases. It has been observed that this IFEP outperforms the CEP in obtaining the optimum design of transformers of smaller as well as larger ratings in terms of execution time, convergence rate, quality and success rate. Originality/value - The proposed method results in the economical design of a three-phase power transformer which can significantly reduce the cost of manufacturing transformers.

关键词： transformers evolutionary programming optimization techniques

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Product configuration optimization for disassembly planning: A differential approach

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2006年第6期34卷 599-616页

作者： Viswanathan, S Allada, V Univ Missouri Sustainable Design Lab 205 Engn Management Dept Rolla MO 65409 USA Brandeis Univ Comp Sci Dept Waltham MA 02254 USA

Product configuration immensely influences the suitability of a product for end-of-life (ECL) disassembly. The product configuration is the relative spatial and logical arrangement of the different parts/sub-assemblies of the product with respect to each other. The complexity involved in studying the influence of configuration design on EOL disassembly has limited the scope of the current design for disassembly (DfD) approaches to guideline-based prescriptive methods and index-based evaluation techniques. The application of these approaches has primarily been limited to specific case studies of product redesign. Many of the current methods do not provide the necessary rigor that will lead to the creation of a theoretical base for addressing product configuration issues which is indispensable during product redesign. Though fraught with obstacles, studying the effects of product configuration on DfD will be useful to develop automated configuration optimization methods for EOL disassembly. To this end, a model to study the combinatorial configuration design optimization problem from a disassembly perspective is described in this study. The different structural principles of the design space derived in this study provide insights into the possibilities and the natural shortcomings of automated optimization of a product by relating the effects of design constraints and disassembly requirements on product redesign. A hierarchical evolutionary programming based algorithm is also developed to test the design solutions generated by the proposed model. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： disassembly product configuration optimization evolutionary programming

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Nonconvex economic dispatch with heuristic load patterns using improved fast evolutionary program

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2006年第1期34卷 37-45页

作者： Ravi, G Chakrabarti, R Choudhuri, S Pondicherry Engn Coll Dept EEE Pondicherry 605014 India Jadavpur Univ Dept Elect Engn Kolkata 700032 W Bengal India

This article presents an attempt to explore the feasibility of an improved fast evolutionary program (IFEP) search technique to solve extremely challenging nonconvex economic load dispatch (ELD) problem with transmission losses involving variations of consumer load patterns. The effectiveness of the proposed approach has been tested successfully on the standard 6-bus system, IEEE 14-bus system, and the IEEE-30 bus system with several heuristic load patterns. The numerical results reveal that the proposed approach can provide better optimal dispatch solutions than those of classical lambda-iteration method (CLIM). Aside from this, the computation time is reasonable even with nonconvex fuel cost functions where the gradient based search methods are inapplicable.

关键词： economic load dispatch load patterns transmission losses evolutionary programming valve point loading mutation

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Application and Comparison of Metaheuristic Techniques to Generation Expansion Planning Incorporating Both Bilateral and Multilateral Transactions

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INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS 2006年第1期6卷 1-12页

作者： Subramanian, Kannan Slochanal, S. Mary Raja Subramanian, Baskar Padhy, Narayana Prasad Arulmigu Kalasalingam Coll Engn Krishnankoil Tamil Nadu India Thiagarajar Coll Engn Madurai 625015 Tamil Nadu India Indian Inst Technol Roorkee Uttar Pradesh India

In restructured environment, various transactions such as firm bilateral and multilateral transactions are taking place. An analysis is made on effects of transactions on Generation Expansion Planning (GEP). Some of the metaheuristic techniques such as Genetic Algorithm (GA), Differential Evolution (DE), evolutionary programming (EP), evolutionary Strategy (ES), Particle Swarm Optimization (PSO), Tabu Search (TS), Simulated Annealing (SA), and Hybrid Approach (HA) are applied to solve the Transactions-GEP problem with the support of AC-Optimal Power Flow (OPF) for the modified IEEE-30 bus test system with 6-years planning horizon. The original GEP problem is modified using the proposed methods i) Virtual Mapping Procedure (VMP), and ii) Penalty Factor Approach (PFA), to improve the effectiveness of the Metaheuristic techniques. Further, Intelligent Initial Population Generation (IIPG) and 'Store and Retrieve approach' are introduced in the solution techniques to reduce the computational time. PFA is used to convert the constrained problem into an unconstrained one. The results of the metaheuristic techniques are compared and validated with that of Dynamic programming (DP). The performances of each metaheuristic technique were compared in terms of their Success Rate (SR), Average Number of Generations (ANG), the error percentage and the mean execution time. The effects of various transactions on GEP are also analyzed.

关键词： differential evolution dynamic programming evolutionary programming evolutionary strategy generation expansion planning genetic algorithm hybrid approach metaheuristics particle swarm optimization simulated annealing tabu search transmission constrained GEP transactions GEP

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