Integrated grey relational analysis and multi objective grey linear programming for sustainable electricity generation planning

Malekpoor, Hanif; Chalvatzis, Konstantinos; Mishra, Nishikant; Mehlawat, Mukesh Kumar; Zafirakis, D.; Song, Malin

doi:10.1007/s10479-017-2566-4

Cited by 71 publications

(40 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regional markets with innovative technologies have the capacity to facilitate progress while not compromising emission control commitments [99]. the role of industrial electrification and subsequently the electrification options and decisions [106] that are required to control and impact on energy and industrial emissions intensity. This may further spring interest in the innovation interplay between utilities and energy users [107].…”

Section: Discussionmentioning

confidence: 99%

Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia

et al. 2018

View full text Add to dashboard Cite

Highlights• Emissions intensity higher in India and SE Asia countries compared to China.• India's emissions intensity triple that of China in non-metallic minerals industry.• India's emissions intensity double that of China in iron and steel industry.• Indonesia's emissions intensity double that of China in non-metallic minerals sector.• Paris Agreement INDC commitments to be challenged by industrial relocation. Abstract 1The potential relocation of various industrial sectors from China to India and countries of the SE Asian region presents low cost opportunities for manufacturers, but also risks rising for energy demand and CO2 emissions. A cross-country shift of industrial output would present challenges for controlling emissions since India and SE Asian countries present higher industrial emissions intensity than China. We find that although there is a convergence in emissions intensity in the machinery manufacturing and paper and pulp industries, there are significant variations in all other industrial sectors. Indian emissions intensity is double that of China in the iron and steel and textile and leather industries and almost triple in the cement industry; Indonesian emissions intensity is almost double that of China in the non-metallic minerals and textile and leather industries and 50% higher in the chemical and petrochemical industry. We demonstrate that the expected higher emissions are driven by both a higher carbon fuel mix intensity in the recipient countries 1 and higher energy intensity in their industrial activities. While industrial relocation could benefit certain countries financially, it would impose considerable threats to their energy supply security and capacity to comply with their Paris Agreement commitments.

show abstract

Section: Discussionmentioning

confidence: 99%

Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The increasing contribution of renewables (with fewer curtailments) can effectively reduce carbon intensity of power generation. Certainly, sustainable electricity sector planning needs to consider a wider range of parameters and embed effective climate change targets [52]. Domestically, there is clear trend that China is moving away from coal-fired based power generation to a low-carbon power generation pathway.…”

Section: Discussionmentioning

confidence: 99%

Life cycle greenhouse gas emissions from power generation in China’s provinces in 2020

Chalvatzis

Pappas

2018

Applied Energy

View full text Add to dashboard Cite

Carbon intensity of power generation is an important indicator to show the direct competitiveness of electricity against the combustion of fossil fuels. In this study, we estimate the carbon intensities of power generation in China's provinces. Most provinces are likely to have a carbon intensity per unit of power generation between 500 and 700 grams CO2/kWh in 2020, which justifies the progress of electrification from the power generation perspective. With the growing share of low carbon power generation, most provinces show trends of decline in carbon intensity between 2015 and 2020. However, some provinces are expected to see increase in carbon intensity due to increasing share of coal power generation in their power mixes. Coal is still a major growth contributor in most provinces, despite significant growths of low carbon energy sources. Furthermore, renewable energy sources can help reduce the carbon intensity of power generation, but a better coordination among provinces is required, alongside with strong government support and direction.

show abstract

“…Compared with the previously mentioned subjective valuation methods such as AHP and expert scoring, entropy weight methods have higher precision, are better able to explain the obtained results, are adaptable, and can be used in any process that needs weight determinations [35]. Grey relational analysis (GRA), which is a grey system with incomplete information, has been widely used in agriculture, industry, the economy, management, and other disciplines and has achieved good results [36][37][38]. GRA has a simple structure, a small amount of calculation, and the distribution data law does not need to be considered in the analysis [39].…”

Section: Research On Sustainable Evaluation Methodsmentioning

confidence: 99%

Evaluation and Policy Research on the Sustainable Development of China’s Rare Earth Resources

Liang

Yang

et al. 2018

Sustainability

View full text Add to dashboard Cite

As rare earth resources are indispensable raw materials for modern society, they have become strategic global reserve resources. Even though China is the world’s largest producer and exporter of rare earth, the industry has low efficiency and severe problems with over-exploitation and environmental pollution; therefore, there needs to be a greater focus on the sustainable exploitation of rare earth resources. This paper establishes an innovative evaluation index system for the sustainable development of China’s rare earth resources from six main aspects; economic development, social progress, environmental protection, technological innovation, rare earth development and utilization, and rare earth protection in which the indicators are assessed using an entropy method. Grey correlation analysis was used to evaluate China’s rare earth sustainable development level from 2006–2016, from which it was found that sustainable development was poor from 2006–2010 and marginally better from 2011–2016. The main factor affecting rare earth sustainable development in China was found to be the lag in the development of environment protection system and rare earth protection system. Policy recommendations for improving China’s rare earth protection, environmental protection, and technological innovation are proposed to guide government regulations and assist rare earth industry personnel.

show abstract

Integrated grey relational analysis and multi objective grey linear programming for sustainable electricity generation planning

Cited by 71 publications

References 62 publications

Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia

Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia

Life cycle greenhouse gas emissions from power generation in China’s provinces in 2020

Evaluation and Policy Research on the Sustainable Development of China’s Rare Earth Resources

Contact Info

Product

Resources

About