Transmission Congestion Management Considering Modeling of Solar Photovoltaic Distributed Generator in Deregulated Power System
Anu Singla1, Kanwardeep Singh2,Vinod Kumar Yadav3
1Anu Singla*, 1Research Scholar, I.K. Gujral PTU, Kapurthala, 2Department of Electrical Engineering, Chitkara University Institute of Engineering and Technology, Punjab, India.
2Kanwardeep Singh, Department of Electrical Engineering, Guru Nanak Dev Engineering College, Ludhiana, (I.K. Gujral PTU, Kapurthala), Punjab, India.
3Vinod Kumar Yadav, Department of Electrical Engineering, Delhi Technological University, Delhi, India.
Manuscript received on 6 August 2019. | Revised Manuscript received on 12 August 2019. | Manuscript published on 30 September 2019. | PP: 2086-2093 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4549098319/19©BEIESP | DOI: 10.35940/ijrte.C4549.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents an effective methodology for transmission congestion management (TCM) in deregulated power system considering random nature of solar photovoltaic distributed generator (SPVDG). Solar photovoltaic power generation has gained popularity worldwide. Its’ optimal sitting in the grid can provide congestion relief and reduce line losses etc. However, to maximize the potential benefits of this renewable energy source, its’ stochastic power output which mainly depends on solar irradiance needs due consideration. In this paper, seasonal variations of solar irradiance have been modeled using beta probability density function to determine expected power output of SPVDG over various seasons of one year. TCM problem has been formulated as a non-linear programming with the objective of social welfare maximization of electricity market subject to equality and inequality constraints incorporating seasonal load demand variations. The optimal siting of SPVDG integration in the grid has been discussed. The proposed methodology has been simulated by incorporating practical data of a real-life SPVDG in standard IEEE 30-bus, IEEE 118-bus and practical Indian Utility 62-bus systems. Simulation results show the benefits of proposed methodology on market indices. The effectiveness of proposed approach is also discussed in comparison with existing methodology of distributed generation modeling.
Keywords: Beta probability density function, locational marginal pricing, solar photovoltaic distributed generator, transmission congestion.
Scope of the Article: Wireless Power Transmission