Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441646
Chih-Ming Hong, Whei-Min Lin, F. Cheng
An induction generator (IG) speed drive with the application of a sliding mode controller and a proposed fuzzy neural network (FNN) controller is introduced in this paper. Grid connected wind energy conversion system (WECS) present interesting control demands, due to the intrinsic nonlinear characteristic of wind mills and electric generators. The FNN torque compensation is feedforward to increase the robustness of the wind driven induction generator system. A multivariable controller is designed to drive the turbine speed to extract maximum power from the wind and adjust to the power regulation. Moreover, a sliding mode speed controller is designed based on an integral-proportional (IP) sliding surface. When sliding mode occurs on the sliding surface, the control system acts as a robust state feedback system.
{"title":"Application of Fuzzy Neural Network Sliding Mode Controller for Wind Driven Induction Generator System","authors":"Chih-Ming Hong, Whei-Min Lin, F. Cheng","doi":"10.1109/ISAP.2007.4441646","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441646","url":null,"abstract":"An induction generator (IG) speed drive with the application of a sliding mode controller and a proposed fuzzy neural network (FNN) controller is introduced in this paper. Grid connected wind energy conversion system (WECS) present interesting control demands, due to the intrinsic nonlinear characteristic of wind mills and electric generators. The FNN torque compensation is feedforward to increase the robustness of the wind driven induction generator system. A multivariable controller is designed to drive the turbine speed to extract maximum power from the wind and adjust to the power regulation. Moreover, a sliding mode speed controller is designed based on an integral-proportional (IP) sliding surface. When sliding mode occurs on the sliding surface, the control system acts as a robust state feedback system.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133725105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441678
Konrad Wojdan, K. Swirski, Tomasz Chomiak
The article presents an optimization method of combustion process in a power boiler. Immune inspired optimizer SILO is used to minimize CO and NOx emission. This solution is implemented in each of three units of Ostroleka Power Plant (Poland) and in the Newton Power Plant (USA). The result from the second SILO implementation in Newton Power Plant is presented. The results confirm that this solution is effective and usable in practice and it can be a good alternative to MPC controllers.
{"title":"Immune Inspired System for Chemical Process Optimization using the example of a Combustion Process in a Power Boiler","authors":"Konrad Wojdan, K. Swirski, Tomasz Chomiak","doi":"10.1109/ISAP.2007.4441678","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441678","url":null,"abstract":"The article presents an optimization method of combustion process in a power boiler. Immune inspired optimizer SILO is used to minimize CO and NOx emission. This solution is implemented in each of three units of Ostroleka Power Plant (Poland) and in the Newton Power Plant (USA). The result from the second SILO implementation in Newton Power Plant is presented. The results confirm that this solution is effective and usable in practice and it can be a good alternative to MPC controllers.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121920088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441650
S. Kyanzadeh, M. M. Farsangi, H. Nezamabadi-pour, Kwang Y. Lee
This paper investigates the ability of immune algorithm (IA) in designing power system stabilizer (PSS) to damp the power system inter-area oscillation. For this the parameters of the PSS are determined by IA using a phase-based objective function. The numerical results are presented on a 2- area 4-machine system to illustrate the feasibility of the proposed method. To show the effectiveness of the designed PSSs, a three phase fault is applied. The simulation study shows that the designed PSSs improve the stability of the system. Also, to validate the results obtained by IA, a simple genetic algorithm (GA) is applied for comparison.
{"title":"Design of Power System Stabilizer Using Immune Algorithm","authors":"S. Kyanzadeh, M. M. Farsangi, H. Nezamabadi-pour, Kwang Y. Lee","doi":"10.1109/ISAP.2007.4441650","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441650","url":null,"abstract":"This paper investigates the ability of immune algorithm (IA) in designing power system stabilizer (PSS) to damp the power system inter-area oscillation. For this the parameters of the PSS are determined by IA using a phase-based objective function. The numerical results are presented on a 2- area 4-machine system to illustrate the feasibility of the proposed method. To show the effectiveness of the designed PSSs, a three phase fault is applied. The simulation study shows that the designed PSSs improve the stability of the system. Also, to validate the results obtained by IA, a simple genetic algorithm (GA) is applied for comparison.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126047480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441626
Y. Chang, C. Yang
After deregulation, power transactions are significantly increased and thus it becomes more urgent to improve system transmission loadability (TL). Utilization of flexible AC transmission systems (FACTS) can be a better choice to accommodate the requirement instead of building new transmission lines. FACTS devices can enhance system dynamic behavior and system reliability. If they are installed at suitable positions and provide system with sufficient capacities, TL may be largely improved. This issue is playing an increasingly vital role in operation and control for the deregulated markets. The objectives of the optimization problem in the paper involve to maximize the benefit from the future fuel expense with proper investment in the allocation of FACTS devices and to improve TL the most. The solution method proposed is based on the particle swarm optimization (PSO) algorithm involving in the computational procedure of the continuation power flow (PFC). Only static VAR compensator (SVC) is used; however, the installation of SVC and the effectiveness of the solution method can be validated.
{"title":"Benefit-Based Optimal Allocation of FACTS: SVC Device for Improvement of Transmission Network Loadability","authors":"Y. Chang, C. Yang","doi":"10.1109/ISAP.2007.4441626","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441626","url":null,"abstract":"After deregulation, power transactions are significantly increased and thus it becomes more urgent to improve system transmission loadability (TL). Utilization of flexible AC transmission systems (FACTS) can be a better choice to accommodate the requirement instead of building new transmission lines. FACTS devices can enhance system dynamic behavior and system reliability. If they are installed at suitable positions and provide system with sufficient capacities, TL may be largely improved. This issue is playing an increasingly vital role in operation and control for the deregulated markets. The objectives of the optimization problem in the paper involve to maximize the benefit from the future fuel expense with proper investment in the allocation of FACTS devices and to improve TL the most. The solution method proposed is based on the particle swarm optimization (PSO) algorithm involving in the computational procedure of the continuation power flow (PFC). Only static VAR compensator (SVC) is used; however, the installation of SVC and the effectiveness of the solution method can be validated.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115243422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441661
N. Sinha, L. Lai, P. Ghosh, Ying-Nan Ma
This paper proposes a hybrid model developed through wiser integration of wavelet transforms, floating point GA and artificial neural networks for prediction of short-term load. The use of wavelet transforms has added the capability of capturing of both global trend and hidden templates in loads, which is otherwise very difficult to incorporate into the prediction model of ANN. Auto-configuring RBF networks are used for predicting the wavelet coefficients of the future loads. Floating point GA (FPGA) is used for optimizing the RBF networks. The use of GA optimized RBF network has added to the model the online prediction capability of short-term loads accurately. The performance of the proposed model is validated using Queensland electricity demand data from the Australian National Electricity Market. Results demonstrate that the proposed model is more accurate as compared to RBF only model.
{"title":"Wavelet-GA-ANN Based Hybrid Model for Accurate Prediction of Short-Term Load Forecast","authors":"N. Sinha, L. Lai, P. Ghosh, Ying-Nan Ma","doi":"10.1109/ISAP.2007.4441661","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441661","url":null,"abstract":"This paper proposes a hybrid model developed through wiser integration of wavelet transforms, floating point GA and artificial neural networks for prediction of short-term load. The use of wavelet transforms has added the capability of capturing of both global trend and hidden templates in loads, which is otherwise very difficult to incorporate into the prediction model of ANN. Auto-configuring RBF networks are used for predicting the wavelet coefficients of the future loads. Floating point GA (FPGA) is used for optimizing the RBF networks. The use of GA optimized RBF network has added to the model the online prediction capability of short-term loads accurately. The performance of the proposed model is validated using Queensland electricity demand data from the Australian National Electricity Market. Results demonstrate that the proposed model is more accurate as compared to RBF only model.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116280232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441691
Tsair-Fwu Lee, H. Wu, Ying-Chang Hsiao, P. Chao, F. Fang, M. Cho
We study the problem of dynamically scheduling a set of period stage control tasks controlling a set of large air conditioner loads (ACLs). To be able to solve the scheduling problem for realistic on-line cases, we utilize the technique of relaxed dynamic programming (RDP) algorithm to generate an optimal or near optimal daily control scheduling for ACLs with relaxing bounds. Field tests of controlling the ACLs located in the campus are tested on-site to demonstrate the effectiveness of the proposed load control strategy.
{"title":"Relaxed Dynamic Programming for Constrained Economic Direct Loads Control Scheduling","authors":"Tsair-Fwu Lee, H. Wu, Ying-Chang Hsiao, P. Chao, F. Fang, M. Cho","doi":"10.1109/ISAP.2007.4441691","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441691","url":null,"abstract":"We study the problem of dynamically scheduling a set of period stage control tasks controlling a set of large air conditioner loads (ACLs). To be able to solve the scheduling problem for realistic on-line cases, we utilize the technique of relaxed dynamic programming (RDP) algorithm to generate an optimal or near optimal daily control scheduling for ACLs with relaxing bounds. Field tests of controlling the ACLs located in the campus are tested on-site to demonstrate the effectiveness of the proposed load control strategy.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125864009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.3182/20080706-5-KR-1001.02028
U. Moon, Seung-chul Lee, K.Y. Lee
This paper proposes an adaptive dynamic matrix control (DMC) using fuzzy inference and its application to boiler-turbine system. In a conventional DMC, object system is described as a step response model (SRM). However, a nonlinear system is not effectively described as a single SRM. In this paper, nine SRMs at various operating points are represented as fuzzy inference rules. On-line fuzzy inference is performed at every sampling step to find the suitable SRM. Therefore, the proposed adaptive DMC can consider the nonlinearity of boiler-turbine system. The simulation results show satisfactory result with wide range operation of boiler-turbine system.
{"title":"An Adaptive Dynamic Matrix Control of a Boiler-Turbine System Using Fuzzy Inference","authors":"U. Moon, Seung-chul Lee, K.Y. Lee","doi":"10.3182/20080706-5-KR-1001.02028","DOIUrl":"https://doi.org/10.3182/20080706-5-KR-1001.02028","url":null,"abstract":"This paper proposes an adaptive dynamic matrix control (DMC) using fuzzy inference and its application to boiler-turbine system. In a conventional DMC, object system is described as a step response model (SRM). However, a nonlinear system is not effectively described as a single SRM. In this paper, nine SRMs at various operating points are represented as fuzzy inference rules. On-line fuzzy inference is performed at every sampling step to find the suitable SRM. Therefore, the proposed adaptive DMC can consider the nonlinearity of boiler-turbine system. The simulation results show satisfactory result with wide range operation of boiler-turbine system.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114409290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441624
R. Garduno-Ramirez, K.Y. Lee
Mostly during wide-range operation, load-following capability and efficacy for frequency regulation of fossil-fuel power plants may be affected by interaction among the control loops, caused by the non-linear coupled plant dynamics. This paper introduces a fuzzy gain-scheduling decoupling control scheme to improve plant response under large power excursions throughout the power plant operating space. The control scheme consists of single-loop PID controllers in series with an inverse interaction compensator. Both, the controllers and compensator are gain-scheduled with fuzzy systems to embrace the entire operating space. The proposed control scheme is evaluated through simulation experiments. Results show improved wide-range operation.
{"title":"Fuzzy Gain-Scheduling PID+Decoupling Control for Power Plant Wide-Range Operation","authors":"R. Garduno-Ramirez, K.Y. Lee","doi":"10.1109/ISAP.2007.4441624","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441624","url":null,"abstract":"Mostly during wide-range operation, load-following capability and efficacy for frequency regulation of fossil-fuel power plants may be affected by interaction among the control loops, caused by the non-linear coupled plant dynamics. This paper introduces a fuzzy gain-scheduling decoupling control scheme to improve plant response under large power excursions throughout the power plant operating space. The control scheme consists of single-loop PID controllers in series with an inverse interaction compensator. Both, the controllers and compensator are gain-scheduled with fuzzy systems to embrace the entire operating space. The proposed control scheme is evaluated through simulation experiments. Results show improved wide-range operation.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124620450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441630
S. Small, B. Jeyasurya
Increased load forecasts can severely deteriorate the performance of a power system. Reactive compensation devices are a common method to allow a power system to return to an acceptable performance level for an expected load. Reactive power planning (RPP) is used to determine the optimal placement of reactive devices for a set of objectives. RPP is a large scale multiple objectives highly constrained and partially discrete optimization problem that is very difficult to solve. Evolutionary algorithms have been used to solve RPP problems. However, new multi-objective evolutionary computational techniques have shown the ability to consider an optimization problem's objectives independently for the determination of Pareto Optimal solutions. This paper aims at applying the Non-Dominated Sorting Genetic Algorithm II (NSGAII) to a multi-objective RPP. The results from the case study presented show that there is great potential in the use of evolutionary computation for solving the multi-objective RPP.
{"title":"Multi-Objective Reactive Power Planning: A Pareto Optimization Approach","authors":"S. Small, B. Jeyasurya","doi":"10.1109/ISAP.2007.4441630","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441630","url":null,"abstract":"Increased load forecasts can severely deteriorate the performance of a power system. Reactive compensation devices are a common method to allow a power system to return to an acceptable performance level for an expected load. Reactive power planning (RPP) is used to determine the optimal placement of reactive devices for a set of objectives. RPP is a large scale multiple objectives highly constrained and partially discrete optimization problem that is very difficult to solve. Evolutionary algorithms have been used to solve RPP problems. However, new multi-objective evolutionary computational techniques have shown the ability to consider an optimization problem's objectives independently for the determination of Pareto Optimal solutions. This paper aims at applying the Non-Dominated Sorting Genetic Algorithm II (NSGAII) to a multi-objective RPP. The results from the case study presented show that there is great potential in the use of evolutionary computation for solving the multi-objective RPP.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133646513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-01DOI: 10.1109/ISAP.2007.4441637
H. Haroonabadi, M. Haghifam
Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In this paper, generation reliability is considered, and a method for its assessment using fuzzy logic is proposed. Monte Carlo simulation is used for reliability evaluation. Since generation reliability, merely focuses on interaction between generation complex and load, therefore in this paper, transmission and distribution systems are considered reliable. In this research, based on market type and its concentration, a fuzzy logic is proposed for modeling the market which is valid for all kinds of power pool markets. The proposed method is assessed on IEEE-reliability test system with satisfactory results. In all case studies, generation reliability indices are evaluated with different reserve margins and various load levels.
{"title":"Generation Reliability Assessment in Power Market Using Fuzzy Logic and Monte Carlo Simulation","authors":"H. Haroonabadi, M. Haghifam","doi":"10.1109/ISAP.2007.4441637","DOIUrl":"https://doi.org/10.1109/ISAP.2007.4441637","url":null,"abstract":"Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In this paper, generation reliability is considered, and a method for its assessment using fuzzy logic is proposed. Monte Carlo simulation is used for reliability evaluation. Since generation reliability, merely focuses on interaction between generation complex and load, therefore in this paper, transmission and distribution systems are considered reliable. In this research, based on market type and its concentration, a fuzzy logic is proposed for modeling the market which is valid for all kinds of power pool markets. The proposed method is assessed on IEEE-reliability test system with satisfactory results. In all case studies, generation reliability indices are evaluated with different reserve margins and various load levels.","PeriodicalId":320068,"journal":{"name":"2007 International Conference on Intelligent Systems Applications to Power Systems","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132125866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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