The need to supply the ever-increasing load demand in combination with the requirement of environmental preservation has introduced variable renewable generation in the generation mix of the modern power grid. Nevertheless, due to the transience and dependency of these renewable energy sources on unpredictable environmental factors the dynamics and priorities of generation expansion planning requires meticulous modifications and enhancements. This paper aims to develop and propose an optimal strategy for generation expansion model considering wind turbine (WTG) generation system. The problem is formulated on the concept of multi-area power system standards and the derivation of an optimal location of the WTG with compressed air energy storage system (CAESS) in the energy mix of the power network. Ensuring that a maximum capacity credit is achieved with WTG incorporation. The objective function in this study, is based on the effective load carrying capability (ELCC) that is utilized to quantify the efficacy of the capacity credit methodology. The ELCC parametric index ensures the reliability standards of the existent system in concurrence with the introduction of additional loads, that is basically grid expansion. Therefore, an evaluative analytical study is performed to increase the dispatchability and availability of the renewable energy sources. The proposed methodology is evaluated and validated on a multi-area system wherein, each area has a pre-existing capacity, load profile, wind generation profile, and reliability data sets.
|Title of host publication
|Proceedings of 2021 IEEE PES Innovative Smart Grid Technologies Europe
|Subtitle of host publication
|Smart Grids: Toward a Carbon-Free Future, ISGT Europe 2021
|Institute of Electrical and Electronics Engineers Inc.
|Published - 2021
|Proceedings of 2021 IEEE PES Innovative Smart Grid Technologies Europe: Smart Grids: Toward a Carbon-Free Future, ISGT Europe 2021
Bibliographical notePublisher Copyright:
© 2021 IEEE.
- Capacity credit
- compressed air energy storage systems
- distribution network
- load flow analysis
- optimal allocation
- wind power generation
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Information Systems and Management
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Artificial Intelligence