TY - JOUR
T1 - Including operational aspects in the planning of power systems with large amounts of variable generation
T2 - A review of modeling approaches
AU - Helistö, Niina
AU - Kiviluoma, Juha
AU - Holttinen, Hannele
AU - Lara, Jose Daniel
AU - Hodge, Bri Mathias
N1 - Funding Information:
This paper is part of international collaboration under International Energy Agency Technology Collaboration Programme IEAWIND Task 25 Design and operation of power systems with large amounts of wind power. N.H., J.K., and H.H. acknowledge funding from the Academy of Finland project ?Improving the value of variable and uncertain power generation in energy systems? (VaGe; grant number 284973), which is part of the New Energy program. N.H. also acknowledges funding from Jenny and Antti Wihuri Foundation. This work was authored in part by Alliance for Sustainable Energy, LLC, the Manager and Operator of the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding was provided by U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Wind Energy Technologies Office. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The authors would like to thank Michael Craig, Kaushik Das and Damian Flynn for their valuable comments.
Publisher Copyright:
© 2019 Wiley Periodicals, Inc.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2019/9
Y1 - 2019/9
N2 - In the past, power system planning was based on meeting the load duration curve at minimum cost. The increasing share of variable generation (VG) makes operational constraints more important in the planning problem, and there is more and more interest in considering aspects such as sufficient ramping capability, sufficient reserve procurement, power system stability, storage behavior, and the integration of other energy sectors often through demand response assets. In VG integration studies, several methods have been applied to combine the planning and operational timescales. We present a four-level categorization for the modeling methods, in order of increasing complexity: (1a) investment model only, (1b) operational model only, (2) unidirectionally soft-linked investment and operational models, (3a) bidirectionally soft-linked investment and operational models, (3b) operational model with an investment update algorithm, and (4) co-optimization of investments and operation. The review shows that using a low temporal resolution or only few representative days will not suffice in order to determine the optimal generation portfolio. In addition, considering operational effects proves to be important in order to get a more optimal generation portfolio and more realistic estimations of system costs. However, operational details appear to be less significant than the temporal representation. Furthermore, the benefits and impacts of more advanced modeling techniques on the resulting generation capacity mix significantly depend on the system properties. Thus, the choice of the model should depend on the purpose of the study as well as on system characteristics. This article is categorized under: Wind Power > Systems and Infrastructure Energy Systems Analysis > Economics and Policy Energy Policy and Planning > Economics and Policy.
AB - In the past, power system planning was based on meeting the load duration curve at minimum cost. The increasing share of variable generation (VG) makes operational constraints more important in the planning problem, and there is more and more interest in considering aspects such as sufficient ramping capability, sufficient reserve procurement, power system stability, storage behavior, and the integration of other energy sectors often through demand response assets. In VG integration studies, several methods have been applied to combine the planning and operational timescales. We present a four-level categorization for the modeling methods, in order of increasing complexity: (1a) investment model only, (1b) operational model only, (2) unidirectionally soft-linked investment and operational models, (3a) bidirectionally soft-linked investment and operational models, (3b) operational model with an investment update algorithm, and (4) co-optimization of investments and operation. The review shows that using a low temporal resolution or only few representative days will not suffice in order to determine the optimal generation portfolio. In addition, considering operational effects proves to be important in order to get a more optimal generation portfolio and more realistic estimations of system costs. However, operational details appear to be less significant than the temporal representation. Furthermore, the benefits and impacts of more advanced modeling techniques on the resulting generation capacity mix significantly depend on the system properties. Thus, the choice of the model should depend on the purpose of the study as well as on system characteristics. This article is categorized under: Wind Power > Systems and Infrastructure Energy Systems Analysis > Economics and Policy Energy Policy and Planning > Economics and Policy.
KW - generation expansion planning
KW - integration of renewable energy sources
KW - operational constraints
KW - power system planning
KW - temporal representation
UR - http://www.scopus.com/inward/record.url?scp=85062786712&partnerID=8YFLogxK
U2 - 10.1002/wene.341
DO - 10.1002/wene.341
M3 - Article
AN - SCOPUS:85062786712
SN - 2041-8396
VL - 8
JO - Wiley Interdisciplinary Reviews: Energy and Environment
JF - Wiley Interdisciplinary Reviews: Energy and Environment
IS - 5
M1 - e341
ER -