System Profit Improvement of a Thermal–Wind–CAES Hybrid System Considering Imbalance Cost in the Electricity Market

Mitul Ranjan Chakraborty, Subhojit Dawn (), Pradip Kumar Saha, Jayanta Bhusan Basu and Taha Selim Ustun ()
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Mitul Ranjan Chakraborty: Department of Electrical Engineering, Siliguri Institute of Technology, Darjeeling 734009, West Bengal, India
Subhojit Dawn: Department of Electrical & Electronics Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada 520007, Andhra Pradesh, India
Pradip Kumar Saha: Department of Electrical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri 735102, West Bengal, India
Jayanta Bhusan Basu: Department of Electrical Engineering, Siliguri Institute of Technology, Darjeeling 734009, West Bengal, India
Taha Selim Ustun: Fukushima Renewable Energy Institute, AIST (FREA), Koriyama 963-0298, Japan

Energies, 2022, vol. 15, issue 24, 1-25

Abstract: Studying a renewable energy integrated power system’s features is essential, especially for deregulated systems. The unpredictability of renewable sources is the main barrier to integrating renewable energy-producing units with the current electrical grid. Due to its unpredictable nature, integrating wind power into an existing power system requires significant consideration. In a deregulated electricity market, this paper examines the implications of wind farm (WF) integration with CAES on electric losses, voltage profile, generation costs, and system economics. Comparative research was done to determine the impact of wind farm integration on regulated and deregulated environments. Four randomly chosen locations in India were chosen for this investigation, together with real-time information on each location’s real wind speed (RWS) and predicted wind speed (PWS). Surplus charge rates and deficit charge rates were created to assess the imbalance cost arising from the discrepancy between predicted and real wind speeds to calculate the system economics. When the effect of imbalance cost is considered, the daily system profit shows a variation of about 1.9% for the locations under study. Customers are always seeking electricity that is dependable, affordable, and efficient due to the reorganization of the power system. As a result, the system security limit could be exceeded or the system might function dangerously. The final section of this paper presents an economic risk analysis using heuristic algorithms such as sequential quadratic programming (SQP), artificial bee colony algorithms (ABC), and moth flame optimization algorithms (MFO). It also discusses how the CAES is used to correct the deviation of WF integration in the real-time electricity market. Economic risk analysis tools include value-at-risk (VaR) and conditional value-at-risk (CVaR). The entire piece of work was validated using a modified IEEE 30-bus test system. This works shows that with a three-fold increase in wind generation, the risk coefficient values improves by 1%.

Keywords: regulated system; deregulated system; wind energy; compressed air energy storage; system profit; value-at-risk; conditional value-at-risk (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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