Corporate greenhouse gas inventories, guarantees of origin and combined heat and power production – Analysis of impacts on total carbon dioxide emissions

Nordenstam, Lena; Ilić, Danica Djurić; Ödlund, Louise

doi:10.1016/j.jclepro.2018.03.034

Cited by 15 publications

(8 citation statements)

References 15 publications

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“…The energy carriers used by the industrial companies in the case study were diesel, liquified petroleum gas (LPG), heavy oil, district heating, and electricity. Different energy carriers have different emission factors, which may also vary with the region and seasons especially for electricity and district heating [38]. The CO 2 emission factors used for the study are mentioned in Table 2.…”

Section: Methodsmentioning

confidence: 99%

“…Emission factors for fossil fuels in this study are taken from the Swedish Environmental Protection Agency [40]. Electricity is considered to be the Nordic electricity mix, as the supply comes through Nordpool, and the emission factor for district heating is taken from the Swedish mix, as district heating markets are more local [38]. Additionally, the CO 2 emission factors for electricity and district heating vary throughout the year, so two scenarios were considered for the study.…”

Section: Methodsmentioning

confidence: 99%

“…Another key detail to be discussed is the difference in CO 2 emissions while considering different scenarios. The emissions in scenario 2 are very high compared to the emissions in scenario 1, due to the fact that the energy used at the marginal level is electricity produced in coal power plants and district heating produced in the oil-fired CHPs [38,42].…”

Section: Significance Of Eeu and Co 2 Emissions In Processesmentioning

confidence: 99%

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Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry

et al. 2020

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Energy efficiency (EE) improvement is one of the most crucial elements in the decarbonization of industry. EE potential within industries largely remains untapped due to the lack of information regarding potential EE measures (EEM), knowledge regarding energy use, and due to the existence of some inconsistencies in the evaluation of energy use. Classification of energy end-using processes would increase the understanding of energy use, which in turn would increase the detection and deployment of EEMs. The study presents a novel taxonomy with hierarchical levels for energy end-use in manufacturing operations for the engineering industry, analyzes processes in terms of energy end-use (EEU) and CO2 emissions, and scrutinizes energy performance indicators (EnPIs), as well as proposing potential new EnPIs that are suitable for the engineering industry. Even though the study has been conducted with a focus on the Swedish engineering industry, the study may be generalizable to the engineering industry beyond Sweden.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Significance Of Eeu and Co 2 Emissions In Processesmentioning

confidence: 99%

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Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry

et al. 2020

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“…The type of 'peak-shaving' DH plants in DHSs differs from country-to-country, mostly due to the fuel market conditions. For example, while the common 'peak-shaving' plants in China are coal-fired boilers [50], in Sweden 'peak-shaving' plants are oil-fired, and in Germany gas-fired boilers are utilized for this purpose [139]. The 'peak-shaving' ('peak load') heat boilers are usually characterized by low investment costs and flexible adjustment, but by high operation costs.…”

Section: Complementing Dh Production and 'Peak Shaving' Dh Sourcesmentioning

confidence: 99%

Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review

Ilić

2020

Energies

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The highly varying character of district heating (DH) demand results in low capacity utilization of the DH plants, as well as increased use of fossil fuels during peak demand. The aim of this study is to present an overview and a comprehensive classification of measures intended to manage these load variations. A systematic literature review was conducted based on previously defined search strings as well as inclusion and exclusion criteria. Two scientific databases were used as data sources. Based on 96 detected publications, the measures were categorized as (1) complementing DH production in heat-only boilers (HOBs), or geothermal or booster heat pumps (HPs) (usually controlled by the DH company), (2) thermal energy (TE) storage in storage units or in the network (controlled by the company), and (3) demand side measures, which can be strategic demand increase, direct demand response (DR), or indirect DR. While the company has control over direct DR (e.g., thermal storage in the thermal mass of the buildings), indirect DR is based on communication between the customer and the company, where the customer has complete control. The multi-disciplinary nature of this topic requires an interdisciplinary approach.

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“…Increased population growth and industrial demands have caused an urgent need for not only the better planning of energy resources but also optimal generation rules [1]. Hydropower energy production is one of the real challenges for decision-makers and policymakers.…”

Section: Introductionmentioning

confidence: 99%

New Evolutionary Algorithm for Optimizing Hydropower Generation Considering Multireservoir Systems

et al. 2019

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In recent decades, solving complex real-life optimization problems has attracted the full attention of researchers. Dam and reservoir operation rules are considered one of the most complicated optimization engineering problems. In fact, the operation rules of dams and reservoirs are multisystematic and highly stochastic and have highly nonlinear system constraints due to the direct influence of environmental conditions: Therefore, these rules are considered highly complex optimization problems. Recently, metaheuristic methods inferred from nature have been broadly utilized to elucidate the way optimal solutions are provided for several complex optimization engineering applications, and these methods have achieved interesting results. The major advantage of these metaheuristic methods over conventional methods is the unnecessity to identify a particular initial condition, convexity, continuity, or differentiability. The present study investigated the potential of using a new metaheuristic method (i.e., the crow algorithm (CA)) to provide optimal operations for multireservoir systems, with the aim of optimally improving hydropower generation. A multireservoir system in China was considered to examine the performance of the proposed optimization algorithm for several operation scenarios. The results obtained the average hydropower generation by considering all examined operation scenarios based on the operation rule achieved using the CA, which outperformed the other metaheuristic methods. In addition, compared to other metaheuristic methods, the proposed CA lessened the time required to search for the optimal solution. In conclusion, the proposed CA has high potential for achieving optimal solutions to complex optimization problems associated with dam and reservoir operations.

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Corporate greenhouse gas inventories, guarantees of origin and combined heat and power production – Analysis of impacts on total carbon dioxide emissions

Cited by 15 publications

References 15 publications

Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry

Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry

Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review

New Evolutionary Algorithm for Optimizing Hydropower Generation Considering Multireservoir Systems

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