Reliability Constrained Optimal Sizing and Examining Capacity Credit and Alternatives for Renewable Energy Sources
Abstract
The growing penetration of renewable energy resources (RES) is changing its role from supplementary to alternative energy resources. If not properly planned, this transformation can significantly increase uncertainty due to the intermittent and non-dispatchable nature of resources such as solar irradiation and wind speed, potentially jeopardizing reliability of power supply. In this paper, a multi-objective approach is introduced to simultaneously optimize reliability and cost. Also, to deal with multiple types of RESs, a new concept, cost credit, is proposed as a supplement or alternative to capacity credit. Cost credit is a parameter that can be used to quantify the cost during planning and increase the reliability of the system. The overall objective is to combine and size the RESs, i.e., photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS), to meet the customer demand based on the total cost and reliability of the system. Two optimization methods, multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm (NSGA-II), are explored for grid connected and stand-alone systems. The best combined size that gives optimal reliability and cost, is then obtained from their outputs utilizing a Fuzzy technique. Then, capacity and cost credit are assessed for the obtained optimal solution.more »
- Authors:
-
[1];
[1]
- Department of Electrical Engineering, Texas A&,M University, College Station, TX, USA
- Publication Date:
- Research Org.:
- Washington State Univ., Pullman, WA (United States)
- Sponsoring Org.:
- USDOE Office of International Affairs (IA)
- OSTI Identifier:
- 1875947
- Alternate Identifier(s):
- OSTI ID: 1875948; OSTI ID: 1980388
- Grant/Contract Number:
- IA0000025
- Resource Type:
- Published Article
- Journal Name:
- IEEE Access
- Additional Journal Information:
- Journal Name: IEEE Access Journal Volume: 10; Journal ID: ISSN 2169-3536
- Publisher:
- Institute of Electrical and Electronics Engineers
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 42 ENGINEERING; Computer Science; Engineering; Telecommunications; Capacity credit; Cost credit; Grid-connected; Hybrid PV-WT-battery system; Optimal sizing method; Stand-alone; Reliability; Wind turbines; Batteries; Renewable energy sources; Maintenance engineering
Citation Formats
Muaddi, Saad A., and Singh, Chanan. Reliability Constrained Optimal Sizing and Examining Capacity Credit and Alternatives for Renewable Energy Sources. United States: N. p., 2022.
Web. doi:10.1109/ACCESS.2022.3188676.
Muaddi, Saad A., & Singh, Chanan. Reliability Constrained Optimal Sizing and Examining Capacity Credit and Alternatives for Renewable Energy Sources. United States. https://doi.org/10.1109/ACCESS.2022.3188676
Muaddi, Saad A., and Singh, Chanan. Sat .
"Reliability Constrained Optimal Sizing and Examining Capacity Credit and Alternatives for Renewable Energy Sources". United States. https://doi.org/10.1109/ACCESS.2022.3188676.
@article{osti_1875947,
title = {Reliability Constrained Optimal Sizing and Examining Capacity Credit and Alternatives for Renewable Energy Sources},
author = {Muaddi, Saad A. and Singh, Chanan},
abstractNote = {The growing penetration of renewable energy resources (RES) is changing its role from supplementary to alternative energy resources. If not properly planned, this transformation can significantly increase uncertainty due to the intermittent and non-dispatchable nature of resources such as solar irradiation and wind speed, potentially jeopardizing reliability of power supply. In this paper, a multi-objective approach is introduced to simultaneously optimize reliability and cost. Also, to deal with multiple types of RESs, a new concept, cost credit, is proposed as a supplement or alternative to capacity credit. Cost credit is a parameter that can be used to quantify the cost during planning and increase the reliability of the system. The overall objective is to combine and size the RESs, i.e., photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS), to meet the customer demand based on the total cost and reliability of the system. Two optimization methods, multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm (NSGA-II), are explored for grid connected and stand-alone systems. The best combined size that gives optimal reliability and cost, is then obtained from their outputs utilizing a Fuzzy technique. Then, capacity and cost credit are assessed for the obtained optimal solution. Finally, sensitivity analysis is conducted to examine the impact of changing different parameters, purchasing/selling price, capacity of grid-connected, and swept area of RES, on the system size.},
doi = {10.1109/ACCESS.2022.3188676},
journal = {IEEE Access},
number = ,
volume = 10,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 2022},
month = {Sat Jan 01 00:00:00 EST 2022}
}
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