An important tool for the energy management system (EMS) is state estimation. Based on measurements taken throughout the network, state estimation gives an estimation of the state variables of the power system while checking that these estimates are consistent with the measurements. Currently, in the Cameroon power system, state estimates have been provided by ad hoc supervisory control and data acquisition (SCADA) systems. A disadvantage is that the measurements are not synchronised, which means that state estimation is not very precise during dynamic phenomena in the network. In this paper, real-time phasor measurement units (PMUs) that provide synchronised phasor measurements are proposed for integration into the power system. This approach addresses two important issues associated with the power system state estimation, namely, that of measurement accuracy and that of optimization of the number of measurement sites, their location, and the importance given to their measurements on the dynamic state estimation. 1. Introduction The electricity sector in Cameroon has been undergoing gradual deregulation in the last few years. AES-SONEL, which took over the generation, transmission, and distribution of electricity in the country in 2001, disposes of a total installed capacity of 933？MW (721？MW from hydroelectricity sources and 212 from thermal sources including 24？MW of isolated capacity) [1]. The transportation network has 480？km of 225？kV lines, 337？km of 110？kV lines, and 1064？km of 90？kV lines, with 24 sub-stations. The need for better utilization of power system facilities has increased significantly in the last decade and will continue, as the electricity market is becoming more complex and competitive. More real-time data from substations and generating plants is required to support SCADA (supervisory control and data acquisition) and EMS (energy management system) in utility control centres. There has been a significant increase in interest in planning, operating, equipment, and maintenance personnel for real-time events and archived data. This wide interest demonstrates the need for the use of real-time state estimators. The system control centre in Mangombe is responsible for the load dispatch and reliability of the main 225？kV grid. Tanyi and Mbinkar have proposed that four area control centres can be located throughout the regions covering the southern interconnected grid (SIG) to be responsible for the operation and maintenance procedures on the transmission, subtransmission, and distribution networks in their respective areas [2]. There
References
[1]
A. Siewe, “Communications sub-director, AES-SONEL,” Cameroon Tribune, 14 pages, 2010.
[2]
E. Tanyi and E. Mbinkar, “A wide area network for data acquisition and real-time control of the cameroon power system,” Journal of Control Engineering and Applied Informatics, vol. 13, no. 1, pp. 5–11, 2011.
[3]
A. Jain and N. R. Shivakumar, “Impact of pmu in dynamic state estimation of power systems,” in Proceedings of the 40th North American Power Symposium (NAPS '08), Calgary, Canada, September 2008, report no. IIIT/TR/2009/50.
[4]
D. M. Falcao, F. F. Wu, and L. Murphy, “Parallel and distributed state estimation,” IEEE Transactions on Power Systems, vol. 10, no. 2, pp. 724–730, 1995.
[5]
C. Rakpenthai, S. Premrudeepreechacharn, S. Uatrongjit, and N. R. Watson, “Measurement placement for power system state estimation using decomposition technique,” Electric Power Systems Research, vol. 75, no. 1, pp. 41–49, 2005.
[6]
F. G. Stremler, Introduction to Communication Systems, Addison-Wesley, Reading, Mass, USA, 1992.
[7]
A. G. Phadke, “Synchronized phasor measurements in power systems,” IEEE Computer Applications in Power, vol. 6, no. 2, pp. 10–15, 1993.
[8]
E. Karam, Implementation and simulation of communication network for wide area monitoring and control systems in OPNET [M.S. thesis], OPNET, Stockholm, Sweden, 2008.
[9]
ABB, Wide Area Measurement, Monitoring, Protection and Control, Industrial IT for Energy System Operation, Utility Automation Systems, ABB, Zurich, Switzerland, 2003, http://www.abb.com/substationautomation/.
[10]
E. Tonye, E-Gouvernance—Présentation Générale, Séminaire d’Information du Publique sur les Produits et Technologies Microsoft, Ecole Nationale Supérieure Polytechnique Yaoundé, 2010.
[11]
C. Madtharad, S. Premrudeepreechacharn, N. R. Watson, and D. Saenrak, “Measurement placement method for power system state estimation: part I,” in Proceedings of the IEEE Power Engineering Society General Meeting, pp. 1629–1632, July 2003.
[12]
J. M. Ngundam, Power Sector Development Plan 2005–2030, Transmission, Distribution and Capacity Issues (PDSE2030), Ministry of Energy and Water Resources, Yaoundé, Cameroon, 2006.
[13]
J. Zhang, G. Welch, G. Bishop, and Z. Huang, “Optimal PMU pacement evaluation for power system dynamic state estimation,” in Pacific Northwest National Laboratory Review, pp. 27599–23175, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 2010.
[14]
S. Chakrabarti, G. K. Venayagamoorthy, and E. Kyriakides, PMU Placement for Power System Observability Using Binary Particle Swarm Optimization, University of Cyprus Review, Nicosia, Cyprus, 2006.
[15]
A. Abur, “Distributed state estimation for MEGA grids,” in Proceedings of the 15th Power Systems Computation Conference (PSCC '05), pp. 22–26, Liege, Belgium, August 2005, session 5, paper 1.
[16]
M. Hurtgen and J. C. Maun, “Advantages of power system state estimation using Phasor Measurement Units,” in Proceedings of the 16th Power Systems Computation Conference (PSCC '08), Glasgow, Scotland, July 2008.
