LAPSE:2023.19381
Published Article

LAPSE:2023.19381
Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints
March 9, 2023
Abstract
This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, acceptable system reliability, and satisfactory CO2 emissions for the coming decades, a complex multi-period mixed integer linear programming (MILP) model needs to be formulated and solved with individual unit characteristics along with hourly power balance constraints. This problem requires huge computational effort since there are thousands of possible scenarios with millions of variables in a single calculation. However, in this paper, instead of finding the globally optimal solutions of such MILPs directly, a simplification process is proposed, breaking it down into multiple LP subproblems, which are easier to solve. In each subproblem, constraints relating to renewable energy generation profiles, charge-discharge patterns of ESSs, and system reliability can be included. The proposed process is tested against Thailand’s power development plan. The obtained solution is almost identical to that of the actual plan, but with less computational effort. The impacts of uncertainties as well as ESSs on GEP, e.g., system reliability, electricity cost, and CO2 emission, are also discussed.
This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, acceptable system reliability, and satisfactory CO2 emissions for the coming decades, a complex multi-period mixed integer linear programming (MILP) model needs to be formulated and solved with individual unit characteristics along with hourly power balance constraints. This problem requires huge computational effort since there are thousands of possible scenarios with millions of variables in a single calculation. However, in this paper, instead of finding the globally optimal solutions of such MILPs directly, a simplification process is proposed, breaking it down into multiple LP subproblems, which are easier to solve. In each subproblem, constraints relating to renewable energy generation profiles, charge-discharge patterns of ESSs, and system reliability can be included. The proposed process is tested against Thailand’s power development plan. The obtained solution is almost identical to that of the actual plan, but with less computational effort. The impacts of uncertainties as well as ESSs on GEP, e.g., system reliability, electricity cost, and CO2 emission, are also discussed.
Record ID
Keywords
energy storage systems, generation expansion planning, MILP decomposition, power development plan
Subject
Suggested Citation
Diewvilai R, Audomvongseree K. Generation Expansion Planning with Energy Storage Systems Considering Renewable Energy Generation Profiles and Full-Year Hourly Power Balance Constraints. (2023). LAPSE:2023.19381
Author Affiliations
Diewvilai R: Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand
Audomvongseree K: Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand; Energy Research Institute, Chulalongkorn University, Bangkok 10330, Thailand
Audomvongseree K: Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand; Energy Research Institute, Chulalongkorn University, Bangkok 10330, Thailand
Journal Name
Energies
Volume
14
Issue
18
First Page
5733
Year
2021
Publication Date
2021-09-11
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14185733, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.19381
This Record
External Link

https://doi.org/10.3390/en14185733
Publisher Version
Download
Meta
Record Statistics
Record Views
229
Version History
[v1] (Original Submission)
Mar 9, 2023
Verified by curator on
Mar 9, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.19381
Record Owner
Auto Uploader for LAPSE
Links to Related Works
