Achieving Effective Power System Observability in Optimal PMUs Placement Using GA-EHBSA
- 1 Department of EEE, Government College of Technology, Coimbatore, India
- 2 Department of EEE, Government College of Technology, Coimbatore, India
Abstract
Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of the power system is considered with the measurement of time-synchronized of the voltage and current. In order to have an efficient placement solution for the issue, a novel method is needed with the optimal approach. For complete power network observability of PMU optimal placement a new method is implemented. However, the process of placement and connection of the buses is considered at various places with the same cost of installation. GA based Enhanced Harmony and Binary Search Algorithm (GA-EHBSA) is proposed and utilized with the improvement to have least PMU placement and better optimization approach for finding the optimal location. To evaluate the optimal placement of PMUs the proposed approach is implemented in the standard test systems of IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 39-bus and IEEE 57-bus. The simulation results are evaluated and compared with existing algorithm to show the efficient process of optimal PMUs placement with better optimization, minimum cost and redundancy than the existing.
- Nazari-Heris, M. and Mohammadi-Ivatloo, B. (2015) Application of Heuristic Algorithms to Optimal PMU Placement in Electric Power Systems: An Updated Review. Renewable and Sustainable Energy Reviews, 50, 214-228. http://dx.doi.org/10.1016/j.rser.2015.04.152
- Lashkari, H.D. and Sarvaiya, J.B. (2014) Matlab Based Simulink Model of Phasor Measurement Unit and Optimal Placement Strategy for PMU Placement. IJSRD—International Journal for Scientific Research & Development, 2, 135-138.
- Singh, S.P. and Singh, S.P. (2014) Optimal PMU Placement in Power System Considering the Measurement Redundancy. Advance in Electronic and Electric Engineering, 4, 593-598.
- Abbasy, N.H. and Ismail, H.M. (2009) A Unified Approach for the Optimal PMU Location for Power System State Estimation. IEEE Transactions on Power Systems, 24, 806-813. http://dx.doi.org/10.1109/tpwrs.2009.2016596
- Khiabani, V., Erdem, E., Farahmand, K. and Nygard, K. (2014) Smart Grid PMU Allocation Using Genetic Algorithm. Journal of Network and Innovative Computing, 2, 30-40.
- Sathyasaraj, K. and Soundarajan, A. (2014) PV Fed Induction Motor Drive System Using Transformer Less High Gain Boost Converter. International Journal of Advanced Information Science and Technology (IJAIST), 26.
- Saini, R., Mam, M. and Saini, M.Kr. (2008) Optimal Placement of Phasor Measurement Units for Power System Observability. International Journal of Power System Operation and Energy Management, 2, 10-13.
- Theodorakatos, N.P., Manousakis, N.M. and Korres, G.N. (2014) Optimal PMU Placement Using Nonlinear Programming. OPT-i—An International Conference on Engineering and Applied Sciences Optimization, Kos Island, Greece, 4-6 June 2014.
- Rihan, M., Ahmad, M. and Beg, M.S. (2013) Optimal Multistage Placement of PMUs with Limited Channel Capacity for a Smart Grid. Electrical and Electronic Engineering, 3, 133-138.
- Khiabani, V. and Farahmand, K. (2013) Max Covering Phasor Measurement Units Placement for Partial Power System Observability. Engineering Management Research, 2.
- Bányai, T. and Veres, P. (2013) Optimisation of Knapsack Problem with Matlab, Based on Harmony Search Algorithm. Advanced Logistic Systems, 7, 13-20.
- Amin, M.M., Moussa, H.B. and Mohammed, O.A. (2012) Wide Area Measurement System for Smart Grid Applications Involving Hybrid Energy Sources. Energy System, 3, 3-21.