Hybrid Approach for Power System Operational Planning With Smart Grid and Small-Signal Stability Enhancement Considerations

Operational planning of power systems, especially in terms of overall reliability and security, is a key issue in the smart grid development. Hence, it is necessary to develop new strategies to cope with increasing uncertainties arising from the fast changing ways power systems are being operated. This paper presents a comprehensive approach to determine an optimal transmission network expansion plan considering the enhancement of small-signal stability through wide-scale deployment of the existing and planned transmission system assets. The dynamic model of the transmission network operational planning (TNOP) is solved based on a combination of the Mean-Variance Mapping Optimization (MVMO), and the classic dynamic programming method embedded with a heuristic procedure. Besides, a probabilistic eigenanalysis-based recursive method is proposed to determine the optimal control strategies that are highly relevant to the enhancement of the system small-signal stability performance throughout the planning horizon. Numerical results demonstrate the viewpoint and the effectiveness of the proposed approach in providing optimal strategies of minimum cost while avoiding the instability risk associated to poorly damped low-frequency electromechanical oscillations.

[1]  Istvan Erlich,et al.  Probabilistic framework for risk analysis of power system small-signal stability , 2012 .

[2]  CARMEN L. T. BORGES,et al.  Parallel Genetic Algorithms Applied to Damping Controllers Tuning on a Linux Cluster of PCs , 2002 .

[3]  Christian Rehtanz,et al.  Valuing the dynamic power flow control of FACTS devices under uncertainties , 2011, 2011 IEEE Trondheim PowerTech.

[4]  V. Miranda.  Evolutionary Algorithms with Particle Swarm Movements , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[5]  G. N. Taranto,et al.  SHORT-TERM TRANSMISSION EXPANSION PLANNING WITH AC NETWORK MODEL AND SECURITY CONSTRAINTS , 2008 .

[6]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[7]  Ariovaldo V. Garcia,et al.  Power system transmission network expansion planning using AC model , 2007 .

[8]  I. Erlich,et al.  Optimal dispatch of reactive sources in wind farms , 2011, 2011 IEEE Power and Energy Society General Meeting.

[9]  Janusz Bialek,et al.  Power System Dynamics: Stability and Control , 2008 .

[10]  I. Erlich,et al.  Assessment and Enhancement of Small Signal Stability Considering Uncertainties , 2009, IEEE Transactions on Power Systems.

[11]  K. R. Padiyar,et al.  ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY , 1990 .

[12]  Eric Allen,et al.  Importance of dynamic stability phenomena in power system planning , 2009, 2009 IEEE Power & Energy Society General Meeting.

[13]  Xiao-Ping Zhang,et al.  Flexible AC Transmission Systems: Modelling and Control , 2006 .

[14]  G. Latorre,et al.  AN OPTIMIZATION MODEL FOR LONG TERM EXPANSION PLANNING OF ELECTRIC POWER TRANSMISSION NETWORKS , 2005 .

[15]  István Erlich,et al.  A Mean-Variance Optimization algorithm , 2010, IEEE Congress on Evolutionary Computation.

[16]  Worawat Nakawiro,et al.  A NEW ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHM FOR VOLTAGE STABILITY CONSTRAINED OPTIMAL POWER FLOW , 2011 .

[17]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[18]  Ganesh K. Venayagamoorthy,et al.  Dynamic, Stochastic, Computational, and Scalable Technologies for Smart Grids , 2011, IEEE Computational Intelligence Magazine.

[19]  Zhenyu Huang,et al.  Improving small signal stability through operating point adjustment , 2010, IEEE PES General Meeting.

[20]  Worawat Nakawiro,et al.  A novel optimization algorithm for optimal reactive power dispatch: A comparative study , 2011, 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT).