TY - JOUR
T1 - Real-time and day-ahead risk averse multi-objective operational scheduling of virtual power plant using modified Harris Hawk's optimization
AU - Pandey, Anubhav Kumar
AU - Jadoun, Vinay Kumar
AU - N․S․, Jayalakshmi
N1 - Funding Information:
The first author is grateful to the funding body for providing DST sponsored INSPIRE Fellowship, Government of India, [INSPIRE Code: IF 190938] to carry out the envisioned research work. The authors also recognize their gratitude to the host University Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India for providing a favourable research atmosphere to continue the anticipated research work.
Funding Information:
The first author is grateful to the funding body for providing DST sponsored INSPIRE Fellowship, Government of India , [INSPIRE Code: IF 190938 ] to carry out the envisioned research work. The authors also recognize their gratitude to the host University Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India for providing a favourable research atmosphere to continue the anticipated research work.
Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/7
Y1 - 2023/7
N2 - This paper addresses optimal scheduling of a virtual power plant (VPP) to enhance the economic and environmental aspect of the anticipated VPP network comprise of renewable sources i.e., solar PV, wind power and fuel cell (FC) along with a cogeneration combined heat and power (CHP) unit. A provision of storage is also provided in the form of electric vehicle (EV) as a flexible reserve and energy storage system (ESS) as a spinning reserve to increase the system reliability and security. To improve the economy, risk management concept is incorporated in which a popular risk measure technique conditional value at risk (CVaR) is also utilized to ameliorate low profit scenarios by employing a modified version of recently developed Harris Hawk's optimization (MHHO). A comprehensive analysis is conducted by considering two types of scheduling into account i.e., day ahead scheduling followed by 5-minute interval which has been developed for the selected problem formulation. Single as well as multi-objective optimized scheduling is performed and numerical results are compared with the published work. The developed approach responds well to the proposed formulation and the statistical results indicates the effectiveness and suitability of the anticipated technique in terms of net-profit and environmental feasibility.
AB - This paper addresses optimal scheduling of a virtual power plant (VPP) to enhance the economic and environmental aspect of the anticipated VPP network comprise of renewable sources i.e., solar PV, wind power and fuel cell (FC) along with a cogeneration combined heat and power (CHP) unit. A provision of storage is also provided in the form of electric vehicle (EV) as a flexible reserve and energy storage system (ESS) as a spinning reserve to increase the system reliability and security. To improve the economy, risk management concept is incorporated in which a popular risk measure technique conditional value at risk (CVaR) is also utilized to ameliorate low profit scenarios by employing a modified version of recently developed Harris Hawk's optimization (MHHO). A comprehensive analysis is conducted by considering two types of scheduling into account i.e., day ahead scheduling followed by 5-minute interval which has been developed for the selected problem formulation. Single as well as multi-objective optimized scheduling is performed and numerical results are compared with the published work. The developed approach responds well to the proposed formulation and the statistical results indicates the effectiveness and suitability of the anticipated technique in terms of net-profit and environmental feasibility.
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U2 - 10.1016/j.epsr.2023.109285
DO - 10.1016/j.epsr.2023.109285
M3 - Article
AN - SCOPUS:85150207587
SN - 0378-7796
VL - 220
JO - Electric Power Systems Research
JF - Electric Power Systems Research
M1 - 109285
ER -
