Abstract
The power industry has been pushing forward the adoption of synchrophasor technology for wide-area monitoring and situational awareness. Many applications have been developed to take advantage of the GPS time-stamped synchrophasor data. Linear state estimator (LSE) is one of the recent developments in the synchrophasor industry that has been gradually accepted and adopted by several US utilities under pilot projects. This chapter first introduces the theory of LSE using Phasor Measurement Unit (PMU) data and then demonstrates the implementation of LSE toward a production-grade application for real-time operation at control center. The other major highlight of this chapter is to demonstrate the benefits and use cases of the LSE application based on firsthand implementation and successful deployment experience at utilities. The LSE can (1) validate and condition PMU data , (2) provide an independent non-iterative state estimator to complement the State Estimator (SE) in Energy Management System (EMS) for situational awareness, data analytics, and grid resiliency, and (3) expand synchrophasor measurement observability for downstream synchrophasor applications. Several use cases are demonstrated in real time by pilot projects deployed at Bonneville Power Administration (BPA), Duke Energy, and Southern California Edison (SCE). LSE application’s use cases and business values are presented to illustrate its successful deployment and operational experience in wide-area monitoring and situational awareness system.
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References
Abur A, Exposito AG (2004) Power system state estimation: theory and implementation. Marcel Dekker Inc
Phadke AG, Thorp JS (2008) Synchronized phasor measurements and their applications. Springer, New York, pp 150–163
Phadke AG, Thorp JS, Nuqui RF, Zhou M Recent developments in state estimation with phasor measurements. In: Proceedings of 2009 IEEE power systems conference and exposition conference, pp 1–7
Yang T, Sun H, Bose A (2011) Transition to a two-level linear state estimator—Part I: architecture. IEEE Trans Power Syst 26(1):46–53
Yang T, Sun H, Bose A (2011) Transition to a two-level linear state estimator—Part II: algorithm. IEEE Trans Power Syst 26(1):54–62
Zhang L, Bose A, Jampala A, Madani V, Giri J (2017) Design, testing, and implementation of a linear state estimator in a real power system. IEEE Trans Smart Grid 8(4):1782–1789
Zhang L, Chen H, Martin K, Faris A, Vutsinas M, Bradberry T, Phillips E, Abu-Jaradeh B, Bui J Successful deployment and operational experience of using linear state estimator in wide-area monitoring and situational awareness projects. IET Gener Transm Distrib. https://doi.org/10.1049/iet-gtd.2016.2028
Chen H, Zhang L, Mo J, Martin K (2016) Synchrophasor-based real-time state estimation and situational awareness system for power system operation. J Mod Power Syst Clean Energy 4(3):370–382
Zhang L, Chen H, Martin KE, Faris A Practical issues of implementation of linear state estimator in WECC. In: IEEE PES innovative smart grid technologies conferences (ISGT), Sept 2016. Minneapolis
Zhang L (2014) Validation, testing, and implementation of the linear state estimator in a real power system. PhD dissertation, School Electrical Engineering, Washington State University, Pullman
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Zhang, L. et al. (2019). Implementation of Synchrophasor-Based Linear State Estimator for Real-Time Operations. In: Nuthalapati, S. (eds) Power System Grid Operation Using Synchrophasor Technology . Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-89378-5_14
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DOI: https://doi.org/10.1007/978-3-319-89378-5_14
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