Hydrogen-based self-sustaining integrated renewable electricity network (HySIREN) using a supply-demand forecasting model and deep-learning algorithms
- 1. Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Søltofts Plads 229, 2800 Kgs. Lyngby (Denmark)
- 2. Department of Environmental Science and Engineering, Center for Environmental Studies, Kyung Hee University, Yongin-Si 446-701 (Korea, Republic of)
Description
Highlights: • A mathematical model of a self-sustaining energy system is designed. • Renewable forecasting models are developed by a hybrid EMD-DL model. • Surplus renewable electricity and renewable electricity shortage are separated. • A smart hydrogen balance is achieved by an integrated hydrogen production process. • A case study of Jeju Island is applied for the proposed model. -- Abstract: Electricity generation from renewable resources such as wind and solar energy inevitably involve intermittency due to the variable nature of wind speed and solar radiation. In this study, a mathematical model of a hydrogen-based self-sustaining integrated renewable electricity network (HySIREN) employing a supply-demand forecasting model and deep-learning (DL) algorithms is developed. The proposed model is implemented as follows: an empirical model decomposition is applied to decompose historical renewable electricity supply-demand data into a number of sub-layers; DL models are utilized to predict renewable electricity supply-demand patterns using the disclosed sub-layers; the predicted surplus renewable electricity and the predicted renewable electricity shortage are explicitly divided through a comparison of forecasting renewable electricity supply-demand data; and according to the results from forecasting models, a smart hydrogen balance is designed by an integrated hydrogen production process encompassing the steam methane reforming process and electrolyzers. Finally, a self-sustaining energy system is constructed and the system flexibility is enhanced, where the predicted surplus renewable electricity is used to convert produced and stored hydrogen into electricity to satisfy predicted renewable electricity shortages. The suggested model was validated by a case study of Jeju Island in the Republic of Korea and the feasibility of the HySIREN model was evaluated. Approximately 64.5% of the total environmental costs were eliminated. The results of this study suggest it would be beneficial to construct environmentally benign strategies for self-sustaining energy systems based on renewable resources.
Additional details
Identifiers
- DOI
- 10.1016/j.enconman.2019.02.017;
- PII
- S0196890419301992;
Publishing Information
- Journal Title
- Energy Conversion and Management
- Journal Volume
- 185
- Journal Page Range
- p. 353-367
- ISSN
- 0196-8904
- CODEN
- ECMADL
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55005122
- Subject category
- S42: ENGINEERING;
- Descriptors DEI
- BIOMASS; DESIGN; ELECTRICITY; ENERGY SYSTEMS; HYDROGEN PRODUCTION; MACHINE LEARNING; MATHEMATICAL MODELS; METHANE; OPTIMIZATION; SOLAR ENERGY; SOLAR RADIATION
- Descriptors DEC
- ALGORITHMS; ALKANES; ARTIFICIAL INTELLIGENCE; ENERGY; ENERGY SOURCES; HYDROCARBONS; LEARNING; MATHEMATICAL LOGIC; ORGANIC COMPOUNDS; RADIATIONS; RENEWABLE ENERGY SOURCES; STELLAR RADIATION
Optional Information
- Copyright
- Copyright (c) 2019 Elsevier Ltd. All rights reserved.