Incorporating life cycle external cost in optimization of the electricity generation mix

Rentizelas, Athanasios; Georgakellos, Dimitrios A.

doi:10.1016/j.enpol.2013.10.023

Cited by 47 publications

(24 citation statements)

References 68 publications

(66 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Most programs such as WASP IV, EMCAS, UPLAN, and AURORAxmp use such functions [25,26]. On the other hand, recent studies have considered not only such nominal costs of power generation but also the external costs or policy objectives-such as environmental effects [6][7][8][9], energy security [2,10,11], related risk [3,[12][13][14], future uncertainty [15], and other energy policy goals [16][17][18]-as additional constraints. Most of these studies utilize a multi-objective optimization model or portfolio theory.…”

Section: Literature Review: Optimal Electricity Generation MIXmentioning

confidence: 99%

“…Examples of such external costs include human health problems, environmental degradation, energy security, dangers of a major accident with a power plant, etc. In recent years, recognition and responsibility for such external costs of electricity and their internalization have become an important policy issue [5], and thus, recent studies have proposed an electricity mix developed under various constraints [2,3,[6][7][8][9][10][11][12][13][14][15][16][17][18]. This context might explain the global phenomenon in which the proportion of renewable energy is increasing even though it has a lower economic feasibility than conventional energy sources.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences

Huh

Lee

2017

Energies

View full text Add to dashboard Cite

Abstract:Public support is an important factor in failure or success of the government decisions with respect to the electricity generation mix, which highlights the necessity of developing an electricity mix that reflects social preferences and acceptance. This study explores heterogeneity in social preferences for power sources and develops an electricity mix from a demand-side perspective. The study utilizes the choice-based conjoint survey and latent class model, and bases its empirical analysis on South Korea's electric power sector. Results demonstrate that preferences for power sources in Korean society consist of two classes: one that is sensitive to the environment and one that is sensitive to risk. An electricity mix for Korea that reflects social preferences is 16.5-19.8% coal-fired, 13.3-24.9% liquefied natural gas (LNG), 9.0-11.2% oil, 22.3-32.9% nuclear, and 18.5-38.9% renewables, depending on the scenario. The study confirms that renewables are the power source with the least potential to cause social conflict, compared to nuclear and coal-fired sources. Moreover, increasing the proportion of renewables (currently only 3.9%) while decreasing the proportion of coal-fired power sources (currently 39.9%) to less than half its current level will result in an electricity mix that is accordance with social preferences in the long run.

show abstract

Section: Literature Review: Optimal Electricity Generation MIXmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences

Huh

Lee

2017

Energies

View full text Add to dashboard Cite

show abstract

“…The current work goes beyond previous research by Rentizelas and Georgakellos [10] and others in several respects. First, a MILP multiperiod model up to 2060 has been developed that can optimise electricity supply on both life cycle costs and environmental impacts, allowing for their trade-offs to be explored.…”

Section: Introductionmentioning

confidence: 92%

“…A recent work by Rentizelas and Georgakellos [10], while taking a life cycle approach, did not use MILP but linear programming, which was applied to plan generation capacity in Greece up to 2050. Furthermore, the authors considered environmental impacts related only to air pollution, assigning them a monetary value to estimate the externalities from electricity generation.…”

Section: Introductionmentioning

confidence: 99%

A multi-period mixed-integer linear optimisation of future electricity supply considering life cycle costs and environmental impacts

et al. 2014

View full text Add to dashboard Cite

An MILP model developed for life cycle optimisation of electricity supply up to 2060. The model can optimise on costs and a number of life cycle environmental impacts. Optimising on costs alone leads to suboptimal solutions. Optimising on GWP reduces both costs and other environmental impacts. Multi-objective optimisation crucial for identifying sustainable electricity futures. a b s t r a c tA multi-period mixed-integer linear programming model has been developed to help explore future pathways for electricity supply where costs and carbon reduction are a priority. The model follows a life cycle approach and can optimise on costs and on a number of environmental objectives. To illustrate the application, the model has been optimised on two objectives: whole system costs and global warming potential (GWP) using the UK as an example. Four different scenarios have been considered up to 2060, each assuming different electricity demand and carbon reduction targets. When optimising on system costs, they range from £156.6 bn for the least carbon-constrained scenario with moderate increase in electricity demand to £269.9 bn for the scenario with high demand and requiring 100% decarbonisation of electricity supply by 2035. In optimisation on GWP, negative carbon emissions are achieved in all scenarios, ranging from À0.5 to À1.28 Gt CO 2 eq. over the period, owing to biomass carbon capture and storage. Optimising on the GWP also reduces significantly other environmental impacts at costs comparable to optimised costs. This research shows that meeting carbon targets will require careful planning and consideration of objectives other than costs alone to ensure that optimal rather than suboptimal solutions are found for a more sustainable electricity supply.

show abstract

“…Rentizelas incorporated life cycle external costs in optimization of the electricity generation mix. The results indicated that renewable energy, especially wind and biomass, should be the new generating capacity [17]. Since biomass power generation project is still on the primary stage, external costs of biomass co-fired with coal power generation are estimated in many studies [18][19][20][21].…”

Section: Literature Reviewmentioning

confidence: 99%

Monetization of External Costs Using Lifecycle Analysis—A Comparative Case Study of Coal-Fired and Biomass Power Plants in Northeast China

Wang

Watanabe

Xu³

2015

Energies

View full text Add to dashboard Cite

Abstract:In this study, the structures of external costs are built in line with coal-fired and biomass power plant life cycle activities in Northeast China. The external cost of coal-fired and biomass power plants was compared, using the lifecycle approach. In addition, the external costs of a biomass power plant are calculated for each stage for comparison with those of a coal-fired power plant. The results highlight that the external costs of a coal-fired plant are 0.072 US $/kWh, which are much higher than that of a biomass power plant, 0.00012 US$/kWh. The external cost of coal-fired power generation is as much as 90% of the current price of electricity generated by coal, while the external cost of a biomass power plant is 1/1000 of the current price of electricity generated by biomass. In addition, for a biomass power plant, the external cost associated with SO2, NOX, and PM2.5 are particularly lower than those of a coal-fired power plant. The prospect of establishing precise estimations for external cost mechanisms and sustainable energy policies is discussed to show a possible direction for future energy schemes in China. The paper has significant value for supporting the biomass power industry and taxing or regulating coal-fired power industry to optimize the energy structure in China. OPEN ACCESSEnergies 2015, 8 1441

show abstract

Incorporating life cycle external cost in optimization of the electricity generation mix

Cited by 47 publications

References 68 publications

A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences

A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences

A multi-period mixed-integer linear optimisation of future electricity supply considering life cycle costs and environmental impacts

Monetization of External Costs Using Lifecycle Analysis—A Comparative Case Study of Coal-Fired and Biomass Power Plants in Northeast China

Contact Info

Product

Resources

About