Document Type : Research Articles

Author

Department of Electrical Engineering of Islamic Azad University

Abstract

a new algorithm is presented to reduce the uncertainty effects of wind farms power generation (WFPG) and photo-voltaic generation (PVG) in both day-ahead energy and ancillary services markets. Firstly, this research tries to predict the uncertainty of short-term WFPG with acceptable accuracy. Indeed, it uses the hybrid method of wavelet transform (WT) in order to reduce the fluctuations in the input historical data along with the improved artificial neural network (ANN) based on the nonlinear structure for better training and learning.
In addition, regarding the high-level penetration of wind farms (WFs) on the power system, cascaded hydro units (CHUs) and pump-storage units (PSUs) are taken for the first time as supplementary units. Therefore, they are coordinated with WFs and photo-voltaic (PV) operations. Considering uncertainties of energy price, spinning and non-spinning reserves in the electricity market, WFPG, PVG and the availability of WFs, PV, CHUs and PSUs along with their effects on energy supply reliability lead to a scenario-based stochastic optimization problem. The aim of this problem is to increase the profit and decrease the financial risk (FR) of all of the units. The proposed method is implemented on WFs, PV, CHUs and PSUs of IEEE 118-bus standard system. Studying the results of profit and FR in the coordinated operation (CO) and the independent operation (IO) confirms that the profit is increased and the FR is reduced in the CO. Hence, the ability and merit of hybrid method of WT-ANN-ICA is verified.

Keywords

Main Subjects

[1] Ali Sefidgar-dezfouli Mahmood Joorabian Elaheh Mashhour,
“Microgrid optimal scheduling considering normal and
emergency operation,” 10.22111/IECO.2019.27484.1100.

[2] Mehrdad Ahmadi Kamarposhti, “Optimal Control of Islanded
Micro grid Using Particle Swarm Optimization Algorithm,”
10.22111/IECO.2018.24354.1022.

[3] Reza Safipour 1 Mahmoud Oukati Sadegh, “Optimal Planning
of Energy Storage Systems using Symbiotic Organisms
Search Algorithm,” 10.22111/IECO.2018.23950.1004.

[4] Pousinho. H.M.I., Mendes. V.M.F., Catalão.J.P.S, “A hybrid
PSOANFIS approach for short-term wind power prediction
in Portugal,” Energy Conversion and Management,
52:397e402, 2011.

[5] Mohandes. M., Rehman. S., Rahman. S.M., “Estimation of
wind speed profile using adaptive Neuro-Fuzzy inference
system (ANFIS),” Applied Energy, vol. 88, Issue 11,
pp.4024-4032, 2011.

[6] Lijie Wang, Lei Dong, Ying Hao, Xiaozhong Liao, “Wind
Power Prediction Using Wavelet Transform and Chaotic
Characteristics,” IEEE Conf, 2009.

[7] Vahid Khorani, Nafiseh Forouzideh, Ali Motie Nasrabadi,
“Artificial Neural Network Weights Optimization Using ICA,
GA, ICA-GA and R-ICA-GA: Comparing Performances,”
IEEE Conf, 2011.

[8] Amin Shokri Gazafroudi, Nooshin Bigdeli, Mostafa Yousefi
Ramandi, Arim Afshar, “A hybrid model for wind power
prediction composed of ANN and imperialist competitive
algorithm (ICA),” The 22nd Iranian Conference on Electrical
Engineering (ICEE 2014), May 20-22, 2014.

[9] Juan M. Morales, Antonio J. Conejo, Juan Perez-Ruiz, “short
term trading for a wind power producer,” IEEE Trans. Power
Syst., vol. 25, no. 1, Feb 2010.

[10] L. Bayón, J.M. Grau, M.M. Ruiz, P.M. Suárez, A
comparative economic study of two configurations of hydro-
wind power plants, Energy, 112: 8e16, 2016.

[11] A. Tiohy, P. Meibom, E. Denny, and M. O’Malley, “Unit
Commitment for Systems with Significant Wind Penetration,”
IEEE Trans. on Power Syst, vol. 24, no. 2, pp. 592601, May
2009.
[12] J. M. Morales, A. J. Conejo, and J. Pérez-Ruiz, “Economic
Valuation of Reserves in Power Systems with High
Penetration of Wind Power,” IEEE Trans. on Power Syst, vol.
24, no. 2, pp. 900910, May 2009.

[13] Mansour Hosseini-Firouz, “Optimal offering strategy
considering the risk management for wind power producers
in electricity market,” Int J Electr Power Energy Syst 49-359-
368, 2013.

[14] K. Lakshmi, S. Vasantharathna, “Gencos windthermal
scheduling problem using Artificial Immune System
algorithm,” Int J Electr Power Energy Syst 54:112-122, 2014.

[15] Huajie Ding, Zechun Hu, Yonghua Song, “Stochastic
optimization of the daily operation of wind farm and
pumped-hydro-storage plant,” Renewable Energy 48-
571e578, 2012.

[16] Lisias V. L. Abreu, Mohammad E. Khodayar, Mohammad
Shahidehpour and Lei Wu, “Risk-Constrained Coordination
of Cascaded Hydro Units with Variable Wind Power
Generation,” IEEE Trans. on Sustainable Energy, vol. 3, no.
3, July 2012.

[17] Huajie Ding, Zechun Hu, Yonghua Song, “Rolling
Optimization of Wind Farm and Energy Storage System in
Electricity Markets,” IEEE Trans. on Power Syst, vol. 30, no.
5, September 2015.

[18] Moein Parastegari, Rahmat-Allah Hooshmand, Amin
Khodabakhshian, Amir-Hossein Zare, “Joint operation of
wind farm, photovoltaic, pump-storage and energy storage
devices in energy and reserve markets,” Int J Electr Power
Energy Syst 64-275-284, 2015.

[19] J.P.S. Catalão, H.M.I. Pousinho, J. Contreras, “Optimal hydro
scheduling and offering strategies considering price
uncertainty and risk management,” Energy, 37: 237e244,
2012.

[20] E. Jafari, S. Soleymani, B. Mozafari, T. Amraee, “Optimal
operation of a micro-grid containing energy resources and
demand response program” Int. J. Environ. Sci. Techno, DOI
10.1007/s13762-017-1525-6, 2018.

[21] E. Jafari. "Determining Optimal Strategy of a Micro-Grid
through Hybrid Method of Nash Equilibrium Genetic
Algorithm", International J. Emerging Electric Power
Systems, DOI: 10.1515/ijeeps-2017-0148, 2019.
[22] Karki R, Hu P, Billinton R, “Reliability Evaluation
Considering Wind and Hydro Power Coordination,” IEEE
Trans. on Power Syst, vol. 25, pp. 685-693, 2010.

[23] Mosayeb Afshari Igder, Taher Niknam, Mohammad-Hassan
Khooban, “Bidding strategies of the joint wind, hydro, and
pumped-storage in generation company using novel
improved clonal selection optimization algorithm,”
10.1049/IET-SMT.2017.0014.

[24] Amjady N. and Vahidinasab V, “Security-constrained self-
scheduling of generation companies in day-ahead electricity
markets considering financial risk,” Energy Conversion and
Management, vol. 65, pp. 164-172, 2013.

[25] Parastegari M, Hooshmand R-A, Khodabakhshian A,
Forghani Z. “Joint operation of wind farms and pump-storage
units in the electricity markets: modeling, simulation and
evaluation,” Simulat Modell Pract Theory, 37(11):5669,
2013.

[26] Hooman Khaloie Amir Abdollahi, “Risk-Averse Pre-
Extreme Weather Events Self-Scheduling of a Wind Power
Plant: A Hybrid Possibilistic-Scenario Model,
10.22111/IECO.2018.24149.1010.