Vv

Dictionary of Agriculture Pub Date : 2018-12-07 DOI:10.4324/9781315062020-22

D. LêAnh

{"title":"Vv","authors":"D. LêAnh","doi":"10.4324/9781315062020-22","DOIUrl":null,"url":null,"abstract":"This paper proposes a simple particle swarm optimization with constriction factor (PSO-CF) method for solving optimal reactive power dispatch (ORPD) problem. The proposed PSO-CF is the conventional particle swarm optimization based on constriction factor which can deal with different objectives of the problem such as minimizing the real power losses, improving the voltage profile, and enhancing the voltage stability and properly handle various constraints for reactive power limits of generators and switchable capacitor banks, bus voltage limits, tap changer limits for transformers, and transmission line limits. The proposed method has been tested on the IEEE 30-bus and IEEE 118-bus systems and the obtained results are compared to those from other PSO variants and other methods in the literature. The result comparison has shown that the proposed method can obtain total power loss, voltage deviation or voltage stability index less than the others for the considered cases. Therefore, the proposed PSO-CF can be favorable solving the ORPD problem TÀI LIỆU THAM KHẢO [1]. Abou El Ela, A.A., Abido, M.A. & Spea, S.R., Differential evolution algorithm for optimal reactive power dispatch, Electric Power Systems Research, 81(2), 458-464 (2011). [2]. About El-Ela, A., Kinawy, A., ElSehiemy, R., Mouwafi, M., Optimal reactive power dispatch using ant colony optimization algorithm, Electrical Engineering (Archiv fur Elektrotechnik), 114 (2011). . [3]. Alsac, O.& Stott, B., Optimal load flow with steady-state security, IEEE Trans. Power Apparatus and Systems, 93, 745-751 (1974). [4]. Aoki, K., Fan, M. & Nishikori, A., Optimal VAR planning by approximation method Science & Technology Development, Vol 16, No.K22013 Trang 100 for recursive mixed integer linear programming, IEEE Trans. Power Systems, 3(4), 1741-1747 (1988).. [5]. Clerc, M. & Kennedy, J., The particle swarm Explosion, stability, and convergence in a multidimensional complex space, IEEE Trans. Evolutionary Computation, 6(1), 58-73 (2002). [6]. Dabbagchi, I. & Christie, R., Power systems test case archive, University of Washington (1993). [7]. Devaraj, D. & Preetha Roselyn, J., Genetic algorithm based reactive power dispatch for voltage stability improvement, Electrical Power and Energy Systems, 32(10), 11511156 (2010). [8]. Esmin, A. A. A., Lambert-Torres, G. & Zambroni de Souza, A. C., A hybrid particle swarm optimization applied to loss power minimization, IEEE Trans. Power Systems, 2(2), 859-866 (2005).. [9]. Granville, S., Optimal reactive power dispatch through interior point methods, IEEE Trans. Power Systems, 9(1), 136-146 (1994).. [10]. Grudinin, N., Reactive power optimization using successive quadratic programming method, IEEE Trans. Power Systems, 13(4), 1219-1225 (1998).. [11]. Kennedy, J. , Eberhart, R., Particle swarm optimization, Proc. IEEE Conf. Neural Networks (ICNN’95), Perth, Australia, IV, 1942-1948 (1995).. [12]. Kessel, P., Glavitsch, H., Estimating the voltage stability of power systems, IEEE Trans Power Systems, 1(3), 346–54 (1986). [13]. Khazali, A. H., Kalantar, M., Optimal reactive power dispatch based on harmony search algorithm, Electrical Power and Energy Systems. [14]. Kirschen, D. S., Van Meeteren, H. P., MW/voltage control in a linear programming based optimal power flow, IEEE Trans. Power Systems, 3(2), 481-489 (1988).. [15]. Lai, L. L. & Ma, J. T., Application of evolutionary programming to reactive power planning, Comparison with nonlinear programming approach. IEEE Trans. Power Systems, 12(1), 198-206 (1997). [16]. Lee, K.Y, Park, Y.M., Ortiz, J.L., A united approach to optimal real and reactive power dispatch, IEEE Trans. Power Apparatus and Systems, PAS-104(5), 1147-1153 (1985). [17]. Li, Y., Cao, Y., Liu, Z., Liu, Y. & Jiang, Q., Dynamic optimal reactive power dispatch based on parallel particle swarm optimization algorithm, Computers and Mathematics with Applications, 57(11-12) 1835-1842 (2009). [18]. Lim, S.Y, Montakhab, M. & Nouri, H., A constriction factor based particle swarm optimization for economic dispatch, The 2009 European Simulation and Modelling Conference (ESM’2009), Leicester, United Kingdom (2009). TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 16, SOÁ K22013 Trang 101 [19]. Lu, F.C., Hsu, Y. Y., Reactive power/voltage control in a distribution substation using dynamic programming, IEE Proc. Gen. Transm. Distrib., 142 (6), 639–645 (1995).. [20]. Mahadevan, K. & Kannan, P.S., Comprehensive learning particle swarm optimization for reactive power dispatch, Applied Soft Computing, 10(2), 641-652 (2010).. [21]. Nanda, J., Hari, L. & Kothari, M. L., Challenging algorithm for optimal reactive power dispatch through classical coordination equations, IEE Proceedings C, 139 (2), 93-101 (1992).. [22]. Ratnaweera, A., Halgamuge, S K., Watson, H. C., Self organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Trans. Evolutionary Computation, 8(3), 240-255 (2004). [23]. Shi, Y. & Eberhart, R., A modified particle swarm optimizer, Proc. The 1998 IEEE World Congress on Computational Intelligence, Piscataway, NJ, IEEE Press, 69-73 (1998) [24]. Urdaneta, A. J., Gomez, J. F., Sorrentino, E., Flores, L. & Diaz, R., A hybrid genetic algorithm for optimal reactive power planning based upon successive linear programming, IEEE Trans. Power Systems, 14 (4), 1292-1298 (1999).. [25]. Vlachogiannis, J. G., Lee, K. Y., A Comparative study on particle swarm optimization for optimal steady-state performance of power systems, IEEE Trans. Power Systems, 21(4), 1718-1728 (2006). [26]. Yan, W., Lu, S., Yu, D. C., A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique, IEEE Trans. Power Systems, 19(2), 913 (2004). [27]. Zhao, B., Guo, C. X., Cao, Y. J., A multiagent-based particle swarm optimization approach for optimal reactive power dispatch, IEEE Trans. Power Systems, 20(2), 1070-1078 (2005).. [28]. Zimmerman, R.D., Murillo-Sánchez, C.E., Thomas, R.J., Matpower's extensible optimal power flow architecture, Proc. 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引用次数: 0

Abstract

This paper proposes a simple particle swarm optimization with constriction factor (PSO-CF) method for solving optimal reactive power dispatch (ORPD) problem. The proposed PSO-CF is the conventional particle swarm optimization based on constriction factor which can deal with different objectives of the problem such as minimizing the real power losses, improving the voltage profile, and enhancing the voltage stability and properly handle various constraints for reactive power limits of generators and switchable capacitor banks, bus voltage limits, tap changer limits for transformers, and transmission line limits. The proposed method has been tested on the IEEE 30-bus and IEEE 118-bus systems and the obtained results are compared to those from other PSO variants and other methods in the literature. The result comparison has shown that the proposed method can obtain total power loss, voltage deviation or voltage stability index less than the others for the considered cases. Therefore, the proposed PSO-CF can be favorable solving the ORPD problem TÀI LIỆU THAM KHẢO [1]. Abou El Ela, A.A., Abido, M.A. & Spea, S.R., Differential evolution algorithm for optimal reactive power dispatch, Electric Power Systems Research, 81(2), 458-464 (2011). [2]. About El-Ela, A., Kinawy, A., ElSehiemy, R., Mouwafi, M., Optimal reactive power dispatch using ant colony optimization algorithm, Electrical Engineering (Archiv fur Elektrotechnik), 114 (2011). . [3]. Alsac, O.& Stott, B., Optimal load flow with steady-state security, IEEE Trans. Power Apparatus and Systems, 93, 745-751 (1974). [4]. Aoki, K., Fan, M. & Nishikori, A., Optimal VAR planning by approximation method Science & Technology Development, Vol 16, No.K22013 Trang 100 for recursive mixed integer linear programming, IEEE Trans. Power Systems, 3(4), 1741-1747 (1988).. [5]. Clerc, M. & Kennedy, J., The particle swarm Explosion, stability, and convergence in a multidimensional complex space, IEEE Trans. Evolutionary Computation, 6(1), 58-73 (2002). [6]. Dabbagchi, I. & Christie, R., Power systems test case archive, University of Washington (1993). [7]. Devaraj, D. & Preetha Roselyn, J., Genetic algorithm based reactive power dispatch for voltage stability improvement, Electrical Power and Energy Systems, 32(10), 11511156 (2010). [8]. Esmin, A. A. A., Lambert-Torres, G. & Zambroni de Souza, A. C., A hybrid particle swarm optimization applied to loss power minimization, IEEE Trans. Power Systems, 2(2), 859-866 (2005).. [9]. Granville, S., Optimal reactive power dispatch through interior point methods, IEEE Trans. Power Systems, 9(1), 136-146 (1994).. [10]. Grudinin, N., Reactive power optimization using successive quadratic programming method, IEEE Trans. Power Systems, 13(4), 1219-1225 (1998).. [11]. Kennedy, J. , Eberhart, R., Particle swarm optimization, Proc. IEEE Conf. Neural Networks (ICNN’95), Perth, Australia, IV, 1942-1948 (1995).. [12]. Kessel, P., Glavitsch, H., Estimating the voltage stability of power systems, IEEE Trans Power Systems, 1(3), 346–54 (1986). [13]. Khazali, A. H., Kalantar, M., Optimal reactive power dispatch based on harmony search algorithm, Electrical Power and Energy Systems. [14]. Kirschen, D. S., Van Meeteren, H. P., MW/voltage control in a linear programming based optimal power flow, IEEE Trans. Power Systems, 3(2), 481-489 (1988).. [15]. Lai, L. L. & Ma, J. T., Application of evolutionary programming to reactive power planning, Comparison with nonlinear programming approach. IEEE Trans. Power Systems, 12(1), 198-206 (1997). [16]. Lee, K.Y, Park, Y.M., Ortiz, J.L., A united approach to optimal real and reactive power dispatch, IEEE Trans. Power Apparatus and Systems, PAS-104(5), 1147-1153 (1985). [17]. Li, Y., Cao, Y., Liu, Z., Liu, Y. & Jiang, Q., Dynamic optimal reactive power dispatch based on parallel particle swarm optimization algorithm, Computers and Mathematics with Applications, 57(11-12) 1835-1842 (2009). [18]. Lim, S.Y, Montakhab, M. & Nouri, H., A constriction factor based particle swarm optimization for economic dispatch, The 2009 European Simulation and Modelling Conference (ESM’2009), Leicester, United Kingdom (2009). TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 16, SOÁ K22013 Trang 101 [19]. Lu, F.C., Hsu, Y. Y., Reactive power/voltage control in a distribution substation using dynamic programming, IEE Proc. Gen. Transm. Distrib., 142 (6), 639–645 (1995).. [20]. Mahadevan, K. & Kannan, P.S., Comprehensive learning particle swarm optimization for reactive power dispatch, Applied Soft Computing, 10(2), 641-652 (2010).. [21]. Nanda, J., Hari, L. & Kothari, M. L., Challenging algorithm for optimal reactive power dispatch through classical coordination equations, IEE Proceedings C, 139 (2), 93-101 (1992).. [22]. Ratnaweera, A., Halgamuge, S K., Watson, H. C., Self organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Trans. Evolutionary Computation, 8(3), 240-255 (2004). [23]. Shi, Y. & Eberhart, R., A modified particle swarm optimizer, Proc. The 1998 IEEE World Congress on Computational Intelligence, Piscataway, NJ, IEEE Press, 69-73 (1998) [24]. Urdaneta, A. J., Gomez, J. F., Sorrentino, E., Flores, L. & Diaz, R., A hybrid genetic algorithm for optimal reactive power planning based upon successive linear programming, IEEE Trans. Power Systems, 14 (4), 1292-1298 (1999).. [25]. Vlachogiannis, J. G., Lee, K. Y., A Comparative study on particle swarm optimization for optimal steady-state performance of power systems, IEEE Trans. Power Systems, 21(4), 1718-1728 (2006). [26]. Yan, W., Lu, S., Yu, D. C., A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique, IEEE Trans. Power Systems, 19(2), 913 (2004). [27]. Zhao, B., Guo, C. X., Cao, Y. J., A multiagent-based particle swarm optimization approach for optimal reactive power dispatch, IEEE Trans. Power Systems, 20(2), 1070-1078 (2005).. [28]. Zimmerman, R.D., Murillo-Sánchez, C.E., Thomas, R.J., Matpower's extensible optimal power flow architecture, Proc. Power and Energy Society General Meeting, IEEE, 1-7 (2009).

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提出了一种带收缩因子的简单粒子群优化算法求解最优无功调度问题。本文提出的PSO-CF是传统的基于收缩因子的粒子群优化算法，能够处理实际功率损耗最小、改善电压分布、增强电压稳定性等不同目标问题，并能很好地处理发电机和可切换电容器组无功限值、母线电压限值、变压器分接开关限值和输电线路限值等各种约束条件。该方法已在IEEE 30总线和IEEE 118总线系统上进行了测试，并与文献中其他PSO变体和其他方法的结果进行了比较。结果比较表明，在考虑的情况下，该方法获得的总功率损耗、电压偏差和电压稳定指标均小于其他方法。因此，所提出的PSO-CF可以较好地解决ORPD问题TÀI LIỆU THAM KHẢO[1]。李建军，李建军，李建军，基于差分进化算法的无功优化调度，电力系统研究，31(2)，458-464(2011)。[2]。关于El-Ela, A. Kinawy, A. ElSehiemy, R. Mouwafi, M.基于蚁群算法的无功功率优化调度，电气工程学报，114(2011)。［3］．李建军，李建军，李建军，一种基于稳态安全的电力系统优化设计方法。电力设备与系统，93,745-751(1974)。[4]。青木，K，范，m，和Nishikori, A，最优VAR规划的逼近方法科学与技术发展，第16卷，第16期。[2][2013]递归混合整数线性规划。电力系统，3(4)，1741-1747 (1988)..［5］． Clerc, M. & Kennedy, J.，粒子群爆炸、稳定性和收敛性在多维复杂空间中的应用，IEEE Trans。进化计算，6(1)，58-73(2002)。［6］． Dabbagchi, I. & Christie, R.，《电力系统测试案例档案》，华盛顿大学(1993)。[7]。李建军，李建军，李建军。基于遗传算法的无功功率调度方法研究，电力系统学报，32(10)，344 - 344(2010)。[8]。Esmin, A. A. A.， Lambert-Torres, G.和Zambroni de Souza, A. C.，一种基于混合粒子群优化的损耗功率最小化算法，电子工程学报。电力系统，2(2)，859-866 (2005)..[9]。李志强，李志强，基于内点法的无功功率优化调度，电气工程学报。电力系统，9(1)，136-146 (1994)..[10]。郭志强，吴志强，基于二次规划的无功优化方法，电气与电子工程学报。电力系统，13(4)，1219-1225 (1998)..[11]。陈志强，陈志强，陈志强，粒子群优化算法，神经网络学报，1995,vol . 4, 42- 44(1995)。[12]。陈建军，张建军，张建军，电力系统电压稳定性评估，电力系统工程学报，1(3)，346-54(1986)。[13]。卡萨里，A. H.， Kalantar, M.，基于和谐搜索算法的最优无功调度，电力与能源系统。[14]。柯琛，范米特伦，H. P.，基于最优潮流的线性规划的兆瓦/电压控制，电气与电子工程学报。电力系统，3(2)，481-489 (1988)..[15]。赖丽丽，马建涛，进化规划在无功规划中的应用，与非线性规划方法的比较。IEEE反式。电力系统，12(1)，198-206(1997)。[16]。李桂英，李永明，李俊良，一种实用的无功功率和有功功率优化调度方法，电气工程学报。电力设备和系统，PAS-104(5)， 1147-1153(1985)。[17]。李艳，曹艳，刘忠，刘勇，蒋强，基于并行粒子群优化算法的动态最优无功调度，计算机应用，57(11):1835-1842(2009)。[18]。Lim, S.Y, Montakhab, M.和Nouri, H.，基于收缩因子的粒子群优化经济调度，2009年欧洲仿真与建模会议(ESM ' 2009)，英国Leicester(2009)。TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 16, SOÁ K22013庄101[19]。吕凤春，徐玉玉，基于动态规划的配电变电站无功电压控制，电气工程学报，vol . 11, no . 1。Distrib。， 142 (6)， 639-645 (1995)..[20]。马海德万，陈建军，李建军，无功调度的综合学习粒子群优化，应用软件计算，10(2)，641-652(2010)。[21]。李建军，李建军，李建军。基于经典协调方程的无功优化调度算法，电子工程学报，39(2)，93-101(1992)。[22]。李建军，张建军，李建军，基于自组织分层粒子群算法的多粒子群优化算法，物理学报。进化计算，8(3)，240-255(2004)。[23]。施,Y。提出了一种带收缩因子的简单粒子群优化算法求解最优无功调度问题。本文提出的PSO-CF是传统的基于收缩因子的粒子群优化算法，能够处理实际功率损耗最小、改善电压分布、增强电压稳定性等不同目标问题，并能很好地处理发电机和可切换电容器组无功限值、母线电压限值、变压器分接开关限值和输电线路限值等各种约束条件。该方法已在IEEE 30总线和IEEE 118总线系统上进行了测试，并与文献中其他PSO变体和其他方法的结果进行了比较。结果比较表明，在考虑的情况下，该方法获得的总功率损耗、电压偏差和电压稳定指标均小于其他方法。因此，所提出的PSO-CF可以较好地解决ORPD问题TÀI LIỆU THAM KHẢO[1]。李建军，李建军，李建军，基于差分进化算法的无功优化调度，电力系统研究，31(2)，458-464(2011)。[2]。关于El-Ela, A. Kinawy, A. ElSehiemy, R. Mouwafi, M.基于蚁群算法的无功功率优化调度，电气工程学报，114(2011)。[3]。李建军，李建军，李建军，一种基于稳态安全的电力系统优化设计方法。电力设备与系统，93,745-751(1974)。[4]。青木，K，范，m，和Nishikori, A，最优VAR规划的逼近方法科学与技术发展，第16卷，第16期。[2][2013]递归混合整数线性规划。电力系统，3(4)，1741-1747 (1988)..[5]。Clerc, M. & Kennedy, J.，粒子群爆炸、稳定性和收敛性在多维复杂空间中的应用，IEEE Trans。进化计算，6(1)，58-73(2002)。[6]。Dabbagchi, I. & Christie, R.，《电力系统测试案例档案》，华盛顿大学(1993)。[7]。李建军，李建军，李建军。基于遗传算法的无功功率调度方法研究，电力系统学报，32(10)，344 - 344(2010)。[8]。Esmin, A. A. A.， Lambert-Torres, G.和Zambroni de Souza, A. C.，一种基于混合粒子群优化的损耗功率最小化算法，电子工程学报。电力系统，2(2)，859-866 (2005)..[9]。李志强，李志强，基于内点法的无功功率优化调度，电气工程学报。电力系统，9(1)，136-146 (1994)..[10]。郭志强，吴志强，基于二次规划的无功优化方法，电气与电子工程学报。电力系统，13(4)，1219-1225 (1998)..[11]。陈志强，陈志强，陈志强，粒子群优化算法，神经网络学报，1995,vol . 4, 42- 44(1995)。[12]。陈建军，张建军，张建军，电力系统电压稳定性评估，电力系统工程学报，1(3)，346-54(1986)。[13]。卡萨里，A. H.， Kalantar, M.，基于和谐搜索算法的最优无功调度，电力与能源系统。[14]。柯琛，范米特伦，H. P.，基于最优潮流的线性规划的兆瓦/电压控制，电气与电子工程学报。电力系统，3(2)，481-489 (1988)..[15]。赖丽丽，马建涛，进化规划在无功规划中的应用，与非线性规划方法的比较。IEEE反式。电力系统，12(1)，198-206(1997)。[16]。李桂英，李永明，李俊良，一种实用的无功功率和有功功率优化调度方法，电气工程学报。电力设备和系统，PAS-104(5)， 1147-1153(1985)。[17]。李艳，曹艳，刘忠，刘勇，蒋强，基于并行粒子群优化算法的动态最优无功调度，计算机应用，57(11):1835-1842(2009)。[18]。Lim, S.Y, Montakhab, M.和Nouri, H.，基于收缩因子的粒子群优化经济调度，2009年欧洲仿真与建模会议(ESM ' 2009)，英国Leicester(2009)。TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 16, SOÁ K22013庄101[19]。吕凤春，徐玉玉，基于动态规划的配电变电站无功电压控制，电气工程学报，vol . 11, no . 1。Distrib。， 142 (6)， 639-645 (1995)..[20]。马海德万，陈建军，李建军，无功调度的综合学习粒子群优化，应用软件计算，10(2)，641-652(2010)。[21]。李建军，李建军，李建军。基于经典协调方程的无功优化调度算法，电子工程学报，39(2)，93-101(1992)。[22]。李建军，张建军，李建军，基于自组织分层粒子群算法的多粒子群优化算法，物理学报。进化计算，8(3)，240-255(2004)。[23]。施,Y。李晓东，李晓东，李晓东，一种改进的粒子群优化算法，1998年IEEE世界计算智能大会论文集，中国计算机工程学报，69-73(1998)[24]。吴丹内塔，A. J.， Gomez, J. F.， Sorrentino, E.， Flores, L.和Diaz, R.，基于连续线性规划的混合遗传算法的最优无功规划，电气与电子工程学报。电力系统，14 (4)，1292-1298 (1999)..[25]。李建军，李金勇，李建军，基于粒子群算法的电力系统最优稳态性能比较研究，电气工程学报。电力系统，21(4)，1718-1728(2006)。[26]。闫伟，吕树林，于德成，基于改进混合进化规划的无功优化调度方法，电气工程学报。电力系统，19(2)，913(2004)。[27]。赵斌，郭春霞，曹玉军，一种基于多智能体的无功优化算法，电气工程学报。电力系统，20(2)，1070-1078 (2005)..[28]。齐默尔曼，Murillo-Sánchez，张建军，张建军，张建军，Matpower的可扩展最优潮流架构，电力与能源学会年会，第1-7(2009)。

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来源期刊

Dictionary of Agriculture

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