Abstract
Economic, social and environmental requirements make planning for a sustainable electricity generation mix a demanding endeavour. Technological innovation offers a range of renewable generation and energy management options which require fine tuning and accurate control to be successful, which calls for the use of large-scale, detailed datasets. In this paper, we focus on the UK and use Multi-Criteria Decision Making (MCDM)to evaluate electricity generation options against technical, environmental and social criteria. Data incompleteness and redundancy, usual in large-scale datasets, as well as expert opinion ambiguity are dealt with using a comprehensive grey TOPSIS model. We used evaluation scores to develop a multi-objective optimization model to maximize the technical, environmental and social utility of the electricity generation mix and to enable a larger role for innovative technologies. Demand uncertainty was handled with an interval range and we developed our problem with multi-objective grey linear programming (MOGLP). Solving the mathematical model provided us with the electricity generation mix for every 5 min of the period under study. Our results indicate that nuclear and renewable energy options, specifically wind, solar, and hydro, but not biomass energy, perform better against all criteria indicating that interindustry architectural innovation in the power generation mix is key to sustainable UK electricity production and supply.
| Original language | English |
|---|---|
| Pages (from-to) | 381-393 |
| Number of pages | 13 |
| Journal | Technological Forecasting and Social Change |
| Volume | 144 |
| DOIs | |
| Publication status | Published - 9 May 2018 |
Bibliographical note
Funding Information:The specific study has been funded under the project TILOS (Horizon 2020 Low Carbon Energy Local/small-scale storage LCE-08-2014). This project has received funding from the European Union & Horizon 2020 research and innovation programme under Grant Agreement No. 646529.
Funding Information:
Nishikant Mishra is a Professor in Operations and Supply Chain Management at Hull University Business School, University of Hull. He has worked on numerous consultancy projects funded by British Council, Biotechnology and Biological Sciences Research Council (BBSRC), British Academy (BA), Innovate UK, Department for Environment, Food and Rural Affairs (DEFRA), Higher Education Academy (HEA) and Meat Promotion Wales (HCC). His research articles have been published in various renowned journals of Operations Research and Operations & Supply chain Management.
Funding Information:
The specific study has been funded under the project TILOS ( Horizon 2020 Low Carbon Energy Local/small-scale storage LCE-08-2014). This project has received funding from the European Union & Horizon 2020 research and innovation programme under Grant Agreement No. 646529 .
Publisher Copyright:
© 2018 Elsevier Inc.
Keywords
- Energy innovation
- Fuel mix
- Grey TOPSIS, grey linear programming
- Interindustry architectural innovation
- Sustainable energy