Publication result detail

Towards data-driven process integration for renewable energy planning

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

Original Title

Towards data-driven process integration for renewable energy planning

English Title

Towards data-driven process integration for renewable energy planning

Type

WoS Article

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

process integration; renewable energy; optimization

Key words in English

process integration; renewable energy; optimization

Authors

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

RIV year

2022

Released

01.03.2021

Publisher

ELSEVIER SCI LTD

Location

OXFORD

ISBN

2211-3398

Periodical

Current Opinion in Chemical Engineering

Volume

31

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

100665-1

Pages to

100665-6

Pages count

6

URL

https://www.sciencedirect.com/science/article/pii/S221133982030068X

Documents

1-s2.0-S221133982030068X-main