Publication detail

Towards data-driven process integration for renewable energy planning

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

English title

Towards data-driven process integration for renewable energy planning

Type

journal article in Web of Science

Language

en

Original abstract

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.

English abstract

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.

Keywords in English

process integration; renewable energy; optimization

Released

01.03.2021

Publisher

ELSEVIER SCI LTD

Location

OXFORD

ISSN

2211-3398

Volume

31

Number

1

Pages from–to

100665-1–100665-6

Pages count

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"
}