American Journal of Electrical and Electronic Engineering

ISSN (Print): 2328-7365

ISSN (Online): 2328-7357

Editor-in-Chief: Naima kaabouch




An Optimization Technique Based on Profit of Investment and Market Clearing in Wind Power Systems

1Department of Visual Communication Design in Art and Architecture, Islamic Azad University - Tehran Central Branch, Tehran, Iran

2Department of Electrical and Computer Engineering, Shiraz University of Technology, Shiraz, Iran

3Department of Electrical and Computer Engineering, Northern Illinoise University, DeKalb, IL

4Department of Electrical and Computer Engineering, University of Florida, Giansville, FL

American Journal of Electrical and Electronic Engineering. 2016, 4(3), 85-91
doi: 10.12691/ajeee-4-3-3
Copyright © 2016 Science and Education Publishing

Cite this paper:
Maryam Ashkaboosi, Seyed Mehdi Nourani, Peyman Khazaei, Morteza Dabbaghjamanesh, Amirhossein Moeini. An Optimization Technique Based on Profit of Investment and Market Clearing in Wind Power Systems. American Journal of Electrical and Electronic Engineering. 2016; 4(3):85-91. doi: 10.12691/ajeee-4-3-3.

Correspondence to: Morteza  Dabbaghjamanesh, Department of Electrical and Computer Engineering, Northern Illinoise University, DeKalb, IL. Email:


Recently, renewable energies are widely used instead of the fuel energies due to their individual potentials such as its availability, low price and environmentally friendly. One of the most important renewable energies is wind power. As a result, investment in wind power is one of the most interesting research to maximize the profit of the investment and market clearing. In this paper, bi-level optimization technique is proposed to maximize the investment problem and market clearing for the wind power at the same time and in one single problem. Then, karush–kuhn–tucker (KKT) conditions and mathematical programming with equilibrium constraints (MPEC) are applied and tried to find one level optimization problem. Due to the nonlinearity of the optimization equation, the Fortuny-Amat & McCarl (FM) linearization technique is used to linearize the model. Finally, the proposed technique is applied to the IEEE 24 buses. The result proves that the optimization analysis is very easy, fast and accurate due to the linear characteristic of the system. All the simulation results are carried out in MATLAB and GAMS softwares.



[1]  B. Fox, “Wind Power Integration: Connection and System Operational Aspects”, Institution of Engineering and Technology, 2007.
[2]  L. Baringo and A. J. Conejo, “Wind Power Investment: A Benders Decomposition Approach,” in IEEE Transactions on Power Systems, vol. 27, no. 1, pp. 433-441, Feb. 2012.
[3]  Xiu-Xing Yin, Yong-Gang Lin, Wei Li, Hong-wei Liu and Ya-Jing Gu, “Fuzzy-Logic Sliding-Mode Control Strategy for Extracting Maximum Wind Power,” in IEEE Transactions on Energy Conversion, vol. 30, no. 4, pp. 1267-1278, Dec. 2015.
[4]  Thomas, Gary E. “The interstellar wind and its influence on the interplanetary environment.” Annual review of earth and planetary sciences 6 (1978): 173-204.
[5]  J.L.C. Meza, Multicriteria analysis of power generation expansion planning, Ph.D thesis, Wichita State University, 2006.
Show More References
[6]  S. Nakamura, “A review of electric production simulation and capacity expansion planning programs”, Int. J. Energy Research, vol. 8, pp. 231-240, 1984.
[7]  C. L. Chen, “Optimal Wind–Thermal Generating Unit Commitment,” in IEEE Transactions on Energy Conversion, vol. 23, no. 1, pp. 273-280, March 2008
[8]  Zheng, Guo-qiang, Hai Bao, and Shu-yong Chen. “Amending algorithm for wind farm penetration optimization based on approximate linear programming method.” PROCEEDINGS-CHINESE SOCIETY OF ELECTRICAL ENGINEERING 24.10 (2004): 68-71.
[9]  J. J. Hargreaves and B. F. Hobbs, “Commitment and Dispatch With Uncertain Wind Generation by Dynamic Programming,” in IEEE Transactions on Sustainable Energy, vol. 3, no. 4, pp. 724-734, Oct. 2012.
[10]  M. Esmaeeli Shahrakht and A. Kazemi, “Stochastic unit commitment of wind farms based on mixed-integer linear formulation,” Electrical Engineering (ICEE), 2012 20th Iranian Conference on, Tehran, 2012, pp. 380-385.
[11]  A.J. Pereira, J.T. Saraiva, “Generation expansion planning (GEP)–A long-term approach using system dynamics and genetic algorithms (GAs)”, J. Energy, vol. 36, pp. 5180-5199, 2011.
[12]  J. L. Ceciliano Meza, M. B. Yildirim and A. S. M. Masud, “A Multiobjective Evolutionary Programming Algorithm and Its Applications to Power Generation Expansion Planning,” in IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 39, no. 5, pp. 1086-1096, Sept. 2009.
[13]  S.-L. Chen, T.-S. Zhan, M.-T. Tsay, “Generation expansion planning of the utility with refined immune algorithm”, J. Electric power systems research, vol. 76, pp. 251-258, 2006.
[14]  P. Murugan, “Modified particle swarm optimisation with a novel initialisation for finding optimal solution to the transmission expansion planning problem”, IET. J. Generation, Transmission & Distribution, vol. 6, pp. 1132-1142, 2012.
[15]  A. Soroudi, M. Afrasiab, “Binary PSO-based dynamic multi-objective model for distributed generation planning under uncertainty”, IET. J. Renewable Power Generation, vol. 6, pp. 67-78, 2012.
[16]  M. El Mokadem, V. Courtecuisse, C. Saudemont, B. Robyns and J. Deuse, “Fuzzy Logic Supervisor-Based Primary Frequency Control Experiments of a Variable-Speed Wind Generator,” in IEEE Transactions on Power Systems, vol. 24, no. 1, pp. 407-417, Feb. 2009.
[17]  M. Dabbaghjamanesh, A. Moeini , M. Ashkaboosi , P. Khazaei, K. Mirzapalangi,”High Performance Control of Grid Connected Cascaded H-Bridge Active Rectifier Based on Type II-Fuzzy Logic Controller with Low Frequency Modulation Technique”,International Journal of Electrical and Computer Engineering (IJECE),Vol. 6, No. 2, April 2016, pp. 484~494,
[18]  S. S. Reddy, A. R. Abhyankar and P. R. Bijwe, “Market clearing for a wind-thermal power system incorporating wind generation and load forecast uncertainties,” 2012 IEEE Power and Energy Society General Meeting, San Diego, CA, 2012, pp. 1-8.
[19]  N. Zhang et al., “A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty,” in IEEE Transactions on Power Systems, vol. 30, no. 3, pp. 1582-1592, May 2015
[20]  S. S. Reddy, P. R. Bijwe and A. R. Abhyankar, “Joint Energy and Spinning Reserve Market Clearing Incorporating Wind Power and Load Forecast Uncertainties,” in IEEE Systems Journal, vol. 9, no. 1, pp. 152-164, March 2015.
[21]  Saberi, Hossein, Mehran Sabahi, Mohammad BB Sharifian, and Mohammadreza Feyzi. “Improved sensorless direct torque control method using adaptive flux observer.” Power Electronics, IET 7, no. 7 (2014): 1675-1684.
[22]  Saberi, H., & Sharifian, M. B. B. (2012, October). An improved direct torque control using fuzzy logic controllers and adaptive observer. In Computer and Knowledge Engineering (ICCKE), 2012 2nd International eConference on (pp. 83-88). IEEE.
[23]  Amiri, M., Feyzi, M., & Saberi, H. (2013, February). A modified torque control approach for load sharing application using V/F induction motor drives. In Power Electronics, Drive Systems and Technologies Conference (PEDSTC), 2013 4th (pp. 1-6). IEEE.
[24]  A. Asadinejad, K. Tomsovic, M.G. Varzaneh, “Examination of incentive based demand response in western connection reduced model,” IEEE NAPS, Charlotte, NC, Oct. 4-6, 2015, pp. 1-6.
[25]  A. Asadinejad, M.G. Varzaneh, S. Mohajeryami, M. Abedi, “Using Biomass in Power Generation for Supplying Electrical and Thermal Energy in Iran and Evaluation of Environmental Pollution Spread,” Journal of Energy and Power Engineering , Volume 10, Issue 1, pp. 55-63.
[26]  S. Mohajeryami, A. Asadinejad, M. Doostan, “An Investigation of the Relationship between Accuracy of Customer Baseline Calculation and Efficiency of Peak Time Rebate Program,” IEEE PECI, IL, Feb. 23-24, 2016.
[27]  A. Sahba, R. Sahba, and W.-M. Lin, “Improving IPC in Simultaneous Multi-Threading (SMT) Processors by Capping IQ Utilization According to Dispatched Memory Instructions,” presented at the 2014 World Automation Congress, Waikoloa Village, HI, 2014.
[28]  A. Sahba, Y. Zhang, M. Hays and W.-M. Lin, “A Real-Time Per-Thread IQ-Capping Technique for Simultaneous MultiThreading (SMT) Processors”, In the Proceedings of the 11th International Conference on Information Technology New Generation (lTNG 2014), April 2014.
[29]  M. Bagheri, M. Madani, R. Sahba, and A. Sahba, “Real time object detection using a novel adaptive color thresholding method”, International ACM workshop on Ubiquitous meta user interfaces (Ubi-MUI'11), Scottsdale, AZ, November 2011.
[30]  Hajinoroozi, Mehdi, et al. “Prediction of driver's drowsy and alert states from EEG signals with deep learning” Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015 IEEE 6th International Workshop.
[31]  Hajinoroozi, Mehdi, et al. “Feature extraction with deep belief networks for driver's cognitive states prediction from EEG data.” Signal and Information Processing (ChinaSIP), 2015 IEEE China Summit and International Conference on. IEEE, 2015.
[32]  Grigoryan, Artyom M., and Mehdi Hajinoroozi. “Image and audio signal filtration with discrete Heap transforms.” Applied Mathematics and Sciences: An International Journal (MathSJ) 1.1 (2014): 1-18.
[33]  Grigoryan, Artyom M., and Mehdi Hajinoroozi. “A novel method of filtration by the discrete heap transforms.” IS&T/SPIE Electronic Imaging. International Society for Optics and Photonics, 2014.
[34]  Jenkinson, J., Grigoryan, A., Hajinoroozi, M., Diaz Hernandez, R., Peregrina Barreto, H., Ortiz Esquivel, A., ... & Chavushyan, V. (2014, October). Machine learning and image processing in astronomy with sparse data sets. In Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on (pp. 200-203). IEEE.
[35]  Rakhshan, Mohsen, Navid Vafamand, Mokhtar Shasadeghi, Morteza Dabbaghjamanesh, and Amirhossein Moeini. “Design of networked polynomial control systems with random delays: sum of squares approach.” International Journal of Automation and Control 10, no. 1 (2016): 73-86.
Show Less References


Analytical Review of Power Flow Tracing in Deregulated Power System

1Department of Electrical Engineering, Veer Surendra Sai University of Technology (VSSUT), Burla, India

2Department of Electrical Engineering, Bhadrak Institute of Engineering and Technology, Bhadrak, India

American Journal of Electrical and Electronic Engineering. 2016, 4(3), 92-101
doi: 10.12691/ajeee-4-3-4
Copyright © 2016 Science and Education Publishing

Cite this paper:
P. K. Hota, A. P. Naik. Analytical Review of Power Flow Tracing in Deregulated Power System. American Journal of Electrical and Electronic Engineering. 2016; 4(3):92-101. doi: 10.12691/ajeee-4-3-4.

Correspondence to: P.  K. Hota, Department of Electrical Engineering, Veer Surendra Sai University of Technology (VSSUT), Burla, India. Email:


Electric Power starts flowing when there is a Source and Sink gets connected. Transmission corridor facilitates that power to flow. The problem arises in the analysis of individual power through a common transmission corridor of a larger system which is called power flow tracing. In the pre-deregulated system, due to the monopolistic nature of governance, the consumer was nothing to say about the tariff or choosing its service provider. But in the free-market or deregulated market system, the price to be charged must be based on fair and transparent manner. So analysis of individual customer’s power in a common supply corridor is a major contribution towards the fair and transparent analysis of price. Efficient power flow tracing would make it possible to charge the generators and/or consumers on the basis of actual transmission facility used. This paper deals with the detailed procedure for obtaining active and reactive power tracing for the actual active and reactive power transmitted through a common corridor between generators and loads. Initially, from the Newton-Raphson based load flows, the line flows are computed and then the multiplying factors of the lossy lines are calculated using proportional sharing method. Finally, based on the multiplying factors, the contributions of each line to concerned loads are obtained for both active and reactive power flow tracing. The method is used elaborately in a Six-bus system and subsequently applied to standard IEEE-14 and IEEE-30 Bus test systems and the results are presented.



[1]  J.Yang, M.D. Anderson, “Tracing the flow of power in transmission networks for use-of-transmission-system changes and congestion management”, Proceedings of IEEE PES, Winter meeting, Vol.1, January 31-Feb 4, 1999, pp.399-405.
[2]  A.R. Shirani, H. Siahkali, “Traceable flow method in determination of congestion cost assignment in open access power system network”, Proceedings of IEEE PES, Transmission and Distribution Conference, Yokahama, Japan, October 2002, pp.734-738.
[3]  A.G. Exposito, J.M.R. Santos, T.G. Garcia, E.R. Velasco, “Fair allocation of transmission power losses”, IEEE Trans. on Power Syst., Vol.15, February-2000, pp.184-188.
[4]  G. Strbac, D. Kirschen, S. Ahmed, “Allocating transmission system usage on the basis of traceable contributions of generators and loads to flows”, IEEE Trans. on Power Syst., Vol.13, May-1998, pp.527-534.
[5]  D. Kirschen, G. Strbac, “Tracing active and reactive power between generators and loads using real and imaginary currents”, IEEE Trans. on Power Syst., Vol.14, November- 1999, pp.1312-1319.
Show More References
[6]  A.J. Canejo, F.D. Galiana, I. Kockar, “Z-buss loss allocation”, IEEE Trans. on Power Syst., Vol.16, February-2001, pp.105-110.
[7]  A.M. Leite, J.G. Carvalho Costa, “Transmission loss allocation. Part-I: Single energy market”, IEEE Trans. on Power Syst., Vol.18, November-2003, pp.1389-1394.
[8]  A. Canejo, N. Alguacil, G.F. Ruiz,, “Allocation of the cost of transmission losses using a radial equivalent network”, IEEE Trans. on Power Syst., Vol.18, November-2003, pp.1353-1358.
[9]  A.J. Canejo, J.M. Arroyo, N. Alguacil, A.L. Guijarro, “Transmission loss allocation: a comparison of different practical algorithms”, IEEE Trans. on Power Syst., Vol.17, August-2002, pp.571-576.
[10]  G. Gross, S. Tao, “A physical-flow-based approach framework”, IEEE Trans. on Power Syst., Vol.15, No.2, May-2000, pp.631-637.
[11]  A.M. Leite, J.G. Carvalho Costa, “Transmission loss allocation. Part-II: Single energy market”, IEEE Trans. on Power Syst., Vol.18, November-2003, pp.1395-1401.
[12]  J.W. Bialek, S. Zeimianek, R. Wallace, “A methodology for allocating transmission losses due to cross-border trades”, IEEE Trans. on Power Syst., Vol.19, August-2004, pp.1255-1262.
[13]  S. Abdelkader, “Transmission loss allocation in a deregulated electrical energy market”, Electric Power Systems Research, Vol.76, 2006, pp.962-967.
[14]  Mohd. Herwan Sulaiman, Mohd. Wazir Mustafa, Hussain Shareef, Saiful Nizam Abd. Khalid, “An application artificial bee colony algorithm with least squares support vector machine for real and reactive power tracing in deregulated power system”, Electrical Power and Energy Systems, Vol.37, 2012, pp.67-77.
[15]  Hadi Saadat, “Power System Analysis”, Tata McGraw-Hill, New Delhi, 2002.
Show Less References


A Simple Current Control Strategy for Single-Stage Grid Connected Three-Phase PV Inverter

1Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla, India

2School of Electrical Engineering, KIIT University, Bhubaneswar, India

American Journal of Electrical and Electronic Engineering. 2016, 4(4), 102-109
doi: 10.12691/ajeee-4-4-1
Copyright © 2016 Science and Education Publishing

Cite this paper:
P. K. Hota, Babita Panda, Bhagabat Panda. A Simple Current Control Strategy for Single-Stage Grid Connected Three-Phase PV Inverter. American Journal of Electrical and Electronic Engineering. 2016; 4(4):102-109. doi: 10.12691/ajeee-4-4-1.

Correspondence to: P.  K. Hota, Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla, India. Email:


This paper presents a new simple method of current control strategy of grid connected PV system. As the solar irradiation is a nonlinear quantity, so the connection of PV system with the grid is a difficult task. The objective of this work is to develop a model of the photovoltaic system with MPPT connected to 11KV grid by implementing new control technique so that maximum active power transfer from PV inverter to grid can be taken place without injection of harmonics. This paper also demonstrates the dynamic model of single-stage three-phase grid connected inverter. Here, for simplification the PV system is realized as a constant DC voltage source by using maximum power point tracking (MPPT) and boost converter. A current control strategy with pulse width modulation (PWM) technique is proposed to provide pulse for voltage-source inverter (VSI). The analysis and control design of grid connected PV inverter using PI control technique is done in synchronous d-q rotating reference frame to achieve maximum output voltage response and active power. The considered system consists of a VSI, 3-Φ filter, a control system, a distribution network, load and grid. As PV inverter should inject only active power, so reactive power injected to the grid is made zero with the help of this control technique. There after the final model is simulated by using MATLAB/SIMULINK and different output waveforms are analyzed for three different conditions.



[1]  F.Blaabjerg, R.Teodorescu, M.Liserre, A.V.Timbus, “Overview of control and grid synchronization for distributed power generation systems”, IEEE Transactions on Industrial Electronics, Vol.53, Issue.5, 2006, pp.1398-1409.
[2]  C.N.M.Ho, V.S.P.Cheung, H.S.H.Chung, “Constant-frequency hysteresis current control of grid-connected VSI without bandwidth control”, IEEE Trans. on Power Electronics, Vol. 24, No.11, 2009, pp.2484-2495.
[3]  P.N.Tekwani, R.S.Kanchan, K.Gopakumar, “Current-error space vector-based hysteresis PWM controller for three-level voltage source inverter fed drives”, Proceedings of Electric Power Applications, IEE, Vol.152, Issue.5, 2005, pp.1283-1295.
[4]  F.Blaabjerg, Z.Chen, S.B.Kjaer, “Power electronics as efficient interface in dispersed power generation systems”, IEEE Transactions on Power Electronics, Vol.19, No.5, September-2004, pp.1184-1194.
[5]  M.F.Schonardie, D.C.Martins, "Application of the dq0 transformation in the three-phase grid-connected PV systems with active and reactive power control", IEEE International Conference on Sustainable Energy Technologies, Singapore, 2008, pp.18-23.
Show More References
[6]  M.A.Rahman, T.S. Radwan, A.M.Osheiba, A.E.Lashine, “Analysis of current controllers for voltage-source inverter”, IEEE Trans. on Industrial Electronics, Vol.44, No.4, 1997, pp.477-4 85.
[7]  M.P.Kazmier kowaski, L.Malesani:, “PWM Current Control Techniques of voltage source converters-A Survey”, IEEE. Trans. on Industrial Electronics, Vol.45, No.5, October-1998, pp.691-703.
[8]  A. Yazdani, P. P. Dash, "A control methodology and characterization of dynamics for a photovoltaic (PV) system interfaced with a distribution network", IEEE Transactions on Power Delivery, Vol.24, No.3, July-2009, pp.1538-1551.
[9]  Krismadinata, N.A. Rahim, J. Selvaraj, “Implementation of hysteresis current control for single-phase grid connected inverter”, Inter. Conf. on Power Electronics and Drive Systems,. PEDS '07, 2007, pp.1097-1101.
[10]  S.H. Habeebullah, S.A. Daniel, “New control paradigm for integration of photovoltaic energy sources with utility network”, International Journal of Electric Power Energy System, 2010.
[11]  D.Xunjiang, C.Qin, “The research of photovoltaic grid-connected inverter based on adaptive current hysteresis band control scheme”, International Conference on Sustainable Power Generation and Supply, SUPERGEN’09, 2009, pp.1-8.
Show Less References