Optimal Power Flow Solution in the Presence of Renewable Energy Sources

In the present work, the renewable energy sources are integrated into the power system. For this purpose, the wind-rich locations and sunny areas are identified in the considered system. A novel persistence-extreme learning machine algorithm is proposed. The wind speed and solar insolations are forecasted in short-term and long-term time periods in the identified areas using the proposed method. With the penetration of wind and solar powers in the system, the optimal power flow problem is solved in 12 different identified cases. The results are analyzed in the prospective of voltage deviation and active power loss. It is observed that the voltage deviation is more in the short-term as well as long-term time horizons with wind and solar integration, but the active power losses are less compared to remaining cases. The analysis is carried out by considering Andhra Pradesh—14-bus system and a 124-bus Indian utility real time system (IND-124). The entire simulation is carried out with the help of MATLAB 2013a.

[1]  Jianxiao Zou,et al.  An Ultra-Short-Term Pre-Plan Power Curve based Smoothing Control Approach for Grid-connected Wind-Solar-Battery Hybrid Power System , 2017 .

[2]  Saša Mujović,et al.  CONOPT solver embedded in GAMS for optimal power flow , 2019, Journal of Renewable and Sustainable Energy.

[3]  Fabrizio Dabbene,et al.  AC optimal power flow in the presence of renewable sources and uncertain loads , 2017, 1702.02967.

[4]  Mukund Patel,et al.  Book Review: Wind and Solar Power Systems—Design, Analysis, and Operation , 2006 .

[5]  Duraisamy,et al.  Efficient Energy Management System for Integrated Renewable Power Generation Systems , 2015 .

[6]  Alain Bensoussan,et al.  Improvement in artificial neural network-based estimation of grid connected photovoltaic power output , 2016 .

[7]  shilaja chandrasekaran,et al.  Optimal Power Flow considering intermittent Wind Power using Particle Swarm optimization , 2016, International Journal of Renewable Energy Research.

[8]  N. V. Lahari,et al.  Integration of grid connected PMG wind energy and solar energy systems using different control stratagies , 2015, 2015 International Conference on Power and Advanced Control Engineering (ICPACE).

[9]  S. Surender Reddy,et al.  Optimal power flow with renewable energy resources including storage , 2016, Electrical Engineering.

[10]  Thomas Ackermann,et al.  Wind Power in Power Systems: Ackermann/Wind Power in Power Systems , 2005 .

[11]  S. Sivanagaraju,et al.  Short term solar insolation prediction: P-ELM approach , 2018, Int. J. Parallel Emergent Distributed Syst..

[12]  Chul-Hwan Kim,et al.  Determination Method of Insolation Prediction With Fuzzy and Applying Neural Network for Long-Term Ahead PV Power Output Correction , 2013, IEEE Transactions on Sustainable Energy.

[13]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[14]  Roberto Cárdenas,et al.  Guest Editorial Control and Grid Integration of MW-Range Wind and Solar Energy Conversion Systems , 2017, IEEE Trans. Ind. Electron..

[15]  R. P. Kumudini Devi,et al.  Optimal power flow model incorporating wind, solar, and bundled solar-thermal power in the restructured Indian power system , 2017 .

[16]  Jan Johansson,et al.  Comprehensive Evaluation on Employee Satisfaction of Mine Occupational Health and Safety Management System Based on Improved AHP and 2-Tuple Linguistic Information , 2017 .

[17]  Thomas Ackermann,et al.  Wind Power in Power Systems , 2005 .

[18]  Douglas H. Werner,et al.  The Wind Driven Optimization Technique and its Application in Electromagnetics , 2013, IEEE Transactions on Antennas and Propagation.

[19]  D. M. Vinod Kumar,et al.  Security-constrained optimal power flow with wind and thermal power generators using fuzzy adaptive artificial physics optimization algorithm , 2016, Neural Computing and Applications.

[20]  Baseem Khan,et al.  Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis , 2017 .

[21]  Amirhossein Khazali,et al.  Optimal generation dispatch incorporating wind power and responsive loads: A chance-constrained framework , 2015 .

[22]  Kiran Teeparthi,et al.  Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators , 2017 .

[23]  Alireza Khaligh,et al.  Energy Harvesting: Solar, Wind, and Ocean Energy Conversion Systems , 2009 .

[24]  John Boland,et al.  Predictive Models for Photovoltaic Electricity Production in Hot Weather Conditions , 2017 .

[25]  Tomonobu Senjyu,et al.  Hybrid Genetic Algorithm Fuzzy-Based Control Schemes for Small Power System with High-Penetration Wind Farms , 2018 .

[26]  Ponnuthurai Nagaratnam Suganthan,et al.  Optimal power flow solutions incorporating stochastic wind and solar power , 2017 .

[27]  R. Venkata Rao,et al.  An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems , 2012, Sci. Iran..

[28]  Wei Tian,et al.  A Hybrid Method for Short-Term Wind Speed Forecasting , 2017 .