Modelling carbon emissions in electric systems

Lau, Eng Tseng; Yang, Qingping; Forbes, Alistair; Wright, P.S.; Livina, Valerie N.

doi:10.1016/j.enconman.2014.01.045

Cited by 24 publications

(12 citation statements)

References 21 publications

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“…For example, in China, by the end of 2012, the installed capacity arrived at 1144.91 GW, and it will be approximate 1600-1650 GW in 2020 forecasted by China Electricity Council. In addition, power industry is one of the most greenhouse gas emission sectors [1]. Especially fired generators would produce numerous greenhouse gases (mainly CO 2 ) into the air, that lead to global warming, climate change, sea level rise, and adverse effects on biodiversity.…”

Section: Introductionmentioning

confidence: 99%

Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty

Zhang

Huang

et al. 2015

Energy Conversion and Management

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Section: Introductionmentioning

confidence: 99%

Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty

Zhang

Huang

et al. 2015

Energy Conversion and Management

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“…According to [1], carbon factors are reported in kilograms of carbon dioxide (CO 2 ) equivalent per unit of energy (kWh). The EGCF refers to the average carbon factor across the energy grid according to fuel mix from different power plant generations (renewables and nonrenewables) [2], [3].…”

Section: Electricity Grid Carbon Factormentioning

confidence: 99%

Application of Ensemble Kalman Filter in Forecasting the Electricity Grid Carbon Factor

Lau¹,

Yang²,

Forbes³

et al. 2015

IJOEE

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Several publications have discussed the application of Ensemble Kalman Filter (EnKF) in history matching problems. The EnKF provides updated approximations based on the conditioned constraints to the historical data. In this paper we show how the EnKF is capable of forecasting/recovering the unpredictable trends of Electricity Grid Carbon Factor (EGCF). We adopt the EGCF scenario in the UK based on the available energy data provided by the Balancing Mechanism Reporting System (BMRS). We apply EnKF for forecasting the incomplete datasets in the UK EGCF in 2014. We present the ability of EnKF to recover the EGCF.

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“…Researchers have also reflected the correlation of emission market prices with energy market prices, considering the direct link arising due to overlapping goals [17][18][19]. Empirical researches suggest that electricity, emission and fuel market (coal, natural gas, etc.)…”

Section: Introductionmentioning

confidence: 99%

GenCo's optimal power portfolio selection under emission price risk

Mathuria

Bhakar

2015

Electric Power Systems Research

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a b s t r a c tCarbon markets are a world-wide accepted market mechanism to promote emission reduction. Increasing stress on emission reduction from the power industry has led to a shift in the market mechanism, from free allocation to full auction. Consequent increase in volatility of emission market and its interdependency with electricity market is predominantly affecting the fossil-fuel generation companies (GenCos). For accurate realization of their optimal electricity trading portfolio selection, GenCos need to incorporate cost side uncertainties arising from fuel and emission market volatilities. This paper proposes a novel framework for electricity trading portfolio optimization of a GenCo, considering uncertainties of electricity, fuel and emission markets, to secure its future trading position. This optimization problem is modeled using mean variance portfolio theory, considering spot market, bilateral contracts as electricity trading options. Results show that considering correlation effects of electricity market with emission markets, the proposed framework is capable of improving profit risk trade-off for the portfolio. Positively correlated electricity, emission market prices lead to an increased trading in spot market. In such a situation, the model reflects that spot selling could offer higher risk protection vis-à-vis bilateral contracts, and can prominently help high emission GenCos to minimize their market risks.

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Modelling carbon emissions in electric systems

Cited by 24 publications

References 21 publications

Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty

Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty

Application of Ensemble Kalman Filter in Forecasting the Electricity Grid Carbon Factor

GenCo's optimal power portfolio selection under emission price risk

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