Detail publikace

Towards data-driven process integration for renewable energy planning

KONG, K. HOW, B. TENG, S. LEONG, W. FOO, D. TAN, R. SUNARSO, J.

Anglický název

Towards data-driven process integration for renewable energy planning

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

en

Originální abstrakt

Process integration (PI) is a sub-area within the chemical engineering discipline that was established in the 1970s. It focuses on the development and use of tools for the holistic design of chemical processes; emphasis is placed on the system-level interdependencies among process units. More recently, PI tools have been applied to renewable energy planning due to mounting concerns about climate change. This article reviews recent developments in PI tools for renewable energy planning, covering both pinch analysis and mathematical programming, and discusses promising prospects for future research. In particular, the role of artificial intelligence in enabling data-driven energy planning with PI is discussed as a priority topic.

Anglický abstrakt

Process integration (PI) is a sub-area within the chemical engineering discipline that was established in the 1970s. It focuses on the development and use of tools for the holistic design of chemical processes; emphasis is placed on the system-level interdependencies among process units. More recently, PI tools have been applied to renewable energy planning due to mounting concerns about climate change. This article reviews recent developments in PI tools for renewable energy planning, covering both pinch analysis and mathematical programming, and discusses promising prospects for future research. In particular, the role of artificial intelligence in enabling data-driven energy planning with PI is discussed as a priority topic.

Klíčová slova anglicky

process integration; renewable energy; optimization

Vydáno

01.03.2021

Nakladatel

ELSEVIER SCI LTD

Místo

OXFORD

ISSN

2211-3398

Ročník

31

Číslo

1

Strany od–do

100665-1–100665-6

Počet stran

6

BIBTEX


@article{BUT177018,
  author="Karen Gah Hie {Kong} and Bing Shen {How} and Sin Yong {Teng} and Wei Dong {Leong} and Dominic CY {Foo} and Raymond R {Tan} and Jaka {Sunarso},
  title="Towards data-driven process integration for renewable energy planning",
  year="2021",
  volume="31",
  number="1",
  month="March",
  pages="100665-1--100665-6",
  publisher="ELSEVIER SCI LTD",
  address="OXFORD",
  issn="2211-3398"
}