Systematic Approach to Better Understanding Integration Costs: Preprint
Abstract
When someone mentions integration costs, thoughts of the costs of integrating renewable generation into an existing system come to mind. We think about how variability and uncertainty can increase power system cycling costs as increasing amounts of wind or solar generation are incorporated into the generation mix. However, seldom do we think about what happens to system costs when new baseload generation is added to an existing system or when generation self-schedules. What happens when a highly flexible combined-cycle plant is added? Do system costs go up, or do they go down? Are other, non-cycling, maintenance costs impacted? In this paper we investigate six technologies and operating practices--including VG, baseload generation, generation mix, gas prices, self-scheduling, and fast-start generation--and how changes in these areas can impact a system's operating costs. This paper provides a working definition of integration costs and four components of variable costs. It describes the study approach and how a production cost modeling-based method was used to determine the cost effects, and, as a part of the study approach section, it describes the test system and data used for the comparisons. Finally, it presents the research findings, and, in closing, suggests three areas for future work.
- Authors:
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- OSTI Identifier:
- 1225309
- Report Number(s):
- NREL/CP-5D00-64930
- DOE Contract Number:
- AC36-08GO28308
- Resource Type:
- Conference
- Resource Relation:
- Conference: Energy Policy Research Conference;Denver, Colorado;09/01/2015 - 09/11/2015
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 17 WIND ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; integration costs; variable generation; renewables; National Renewable Energy Laboratory; NREL
Citation Formats
Stark, Gregory B. Systematic Approach to Better Understanding Integration Costs: Preprint. United States: N. p., 2015.
Web.
Stark, Gregory B. Systematic Approach to Better Understanding Integration Costs: Preprint. United States.
Stark, Gregory B. 2015.
"Systematic Approach to Better Understanding Integration Costs: Preprint". United States. https://www.osti.gov/servlets/purl/1225309.
@article{osti_1225309,
title = {Systematic Approach to Better Understanding Integration Costs: Preprint},
author = {Stark, Gregory B.},
abstractNote = {When someone mentions integration costs, thoughts of the costs of integrating renewable generation into an existing system come to mind. We think about how variability and uncertainty can increase power system cycling costs as increasing amounts of wind or solar generation are incorporated into the generation mix. However, seldom do we think about what happens to system costs when new baseload generation is added to an existing system or when generation self-schedules. What happens when a highly flexible combined-cycle plant is added? Do system costs go up, or do they go down? Are other, non-cycling, maintenance costs impacted? In this paper we investigate six technologies and operating practices--including VG, baseload generation, generation mix, gas prices, self-scheduling, and fast-start generation--and how changes in these areas can impact a system's operating costs. This paper provides a working definition of integration costs and four components of variable costs. It describes the study approach and how a production cost modeling-based method was used to determine the cost effects, and, as a part of the study approach section, it describes the test system and data used for the comparisons. Finally, it presents the research findings, and, in closing, suggests three areas for future work.},
doi = {},
url = {https://www.osti.gov/biblio/1225309},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Sep 28 00:00:00 EDT 2015},
month = {Mon Sep 28 00:00:00 EDT 2015}
}