Reserve Constrained Economic Dispatch Incorporating Solar Farm using Particle Swarm Optimization

Suresh Velamuri, Sreejith S

Abstract


Static Economic Dispatch (SED)  with combined Solar Thermal generation systems incorporating spinning reserve cost is presented in this paper. Particle Swarm Optimization (PSO) algorithm is used as the optimization tool here. Spinning reserve is an  essential requirement in power system network to handle the situations arising during generation or transmission outages. Therefore, incorporation of spinning reserve cost and capacity can provide more realistic dispatch. B-coefficients method is used to determine the losses from the generators for solving the SED. Based on historical data, the output of solar farm is forecasted in this case. Beta distribution function which is the best suited probability density function for irradiance modeling is used to model the output of the solar farm. The uncertainty in solar energy with various seasonal effect is also discussed. Comparative analysis without and with the incorporation of solar farm is carried out. The proposed methodology is tested and validated in IEEE 30 bus test system and South Indian Utility 89 bus test system.

Keywords


Solar; Economic Dispatch; Beta distribution function; PSO; Spinning reserve

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References


Meng, Jie, Gengyin Li, and Yajing Du. "Economic dispatch for power systems with wind and solar energy integration considering reserve risk." Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific. IEEE, 2013.

Hetzer, John, David C. Yu, and Kalu Bhattarai. "An economic dispatch model incorporating wind power." Energy Conversion, IEEE Transactions on 23.2 (2008): 603-611.

Damousis, Ioannis G., et al. "A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation." Energy Conversion, IEEE Transactions on 19.2 (2004): 352-361.

Jeyakumar, D. N., T. Jayabarathi, and T. Raghunathan. "Particle swarm optimization for various types of economic dispatch problems." International Journal of Electrical Power & Energy Systems 28.1 (2006): 36-42.

Gaing, Zwe-Lee. "Particle swarm optimization to solving the economic dispatch considering the generator constraints." Power Systems, IEEE Transactions on18.3 (2003): 1187-1195.

Chowdhury, Badrul H., and Saifur Rahman. "A review of recent advances in economic dispatch." Institute of Electrical and Electronics Engineers, 1990.

Lim, Shi Yao, Mohammad Montakhab, and Hassan Nouri. "Economic dispatch of power system using particle swarm optimization with constriction factor."International Journal of Innovations in Energy Systems and Power 4.2 (2009): 29-34.

Sonmez, Y. "Multi-objective environmental/economic dispatch solution with penalty factor using Artificial Bee Colony algorithm." Scientific Research and Essays 6.13 (2011): 2824-2831.

Brini, Saoussen, Hsan Hadj Abdallah, and Abderrazak Ouali. "Economic dispatch for power system included wind and solar thermal energy." Leonardo Journal of Sciences 14 (2009): 204-220.

Sreejith, S., Sishaj P. Simon, and M. P. Selvan. "Analysis of FACTS devices on Security Constrained Unit Commitment problem." International Journal of Electrical Power & Energy Systems 66 (2015): 280-293.

Al-Awami, A. T., E. Sortomme, and M. A. El-Sharkawi. "Optimizing economic/environmental dispatch with wind and thermal units." Power & Energy Society General Meeting, 2009. PES'09. IEEE. IEEE, 2009.

Eberhart, Russ C., and James Kennedy. "A new optimizer using particle swarm theory." Proceedings of the sixth international symposium on micro machine and human science. Vol. 1. 1995.

Park, Jong-Bae, et al. "A particle swarm optimization for economic dispatch with nonsmooth cost functions." Power Systems, IEEE Transactions on 20.1 (2005): 34-42.

Ramesh, V., et al. "A novel selective particle swarm optimization approach for combined heat and power economic dispatch." Electric Power Components and Systems 37.11 (2009): 1231-1240.

Teng, Jen-Hao, et al. "Optimal charging/discharging scheduling of battery storage systems for distribution systems interconnected with sizeable PV generation systems." Power Systems, IEEE Transactions on 28.2 (2013): 1425-1433.

Sreejith, Sekharan, and Sishaj P. Simon. "Cost benefit analysis on SVC and UPFC in a dynamic economic dispatch problem." International Journal of Energy Sector Management 8, no. 3 (2014): 395-428.

Reddy, S. Surender, B. K. Panigrahi, Rupam Kundu, Rohan Mukherjee, and Shantanab Debchoudhury. "Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique."International Journal of Electrical Power & Energy Systems 53 (2013): 113-122.

Velamuri, Suresh, and S. Sreejith. "Economic dispatch and cost analysis on a Power system network interconnected with Solar Farm." International Journal of Renewable Energy Research (IJRER) 5, no. 4 (2015): 1098-1105.

http://rredc.nrel.gov/solar/new_data/India/nearestcell.cgi.

Saadat, Hadi. Power system analysis. WCB/McGraw-Hill, 1999.




DOI (PDF): https://doi.org/10.20508/ijrer.v6i1.3262.g6769

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