A Long-Term Electricity Dispatch Model with the TIMES Framework

Kannan, Ravindran; Turton, Hal

doi:10.1007/s10666-012-9346-y

Cited by 78 publications

(57 citation statements)

References 16 publications

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“…In the capacity factor equation, P is nominal capacity of the hydropower station and T is number of hours in a month. We choose to assess the monthly capacity factor since hydroclimatic conditions are generally integrated into energy system models by exogenously defining the capacity factor of hydropower power generation technologies to characterise their availability according to inter-annual runoff seasonality (Gargiulo 2009;Kannan and Turton 2011;IFE 2013). Uncertainty in monthly hydropower production is inferred from the frequency distribution associated with the inflows obtained with GCM ensemble results and quantified by the magnitude of the standard deviation.…”

Section: Hydropower Electricity Modelmentioning

confidence: 99%

Assessing uncertainty of climate change impacts on long-term hydropower generation using the CMIP5 ensemble—the case of Ecuador

et al. 2017

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This study presents a method to assess the sensitivity of hydropower generation to uncertain water resource availability driven by future climate change. A hydrology-electricity modelling framework was developed and applied to six rivers where 10 hydropower stations operate, which together represent over 85% of Ecuador's installed hydropower capacity. The modelling framework was then forced with bias-corrected output from 40 individual global circulation model experiments from the Coupled Model Intercomparison Project 5 for the Representative Concentration Pathway 4.5 scenario. Impacts of changing climate on hydropower resource were quantified for 2071-2100 relative to a baseline period 1971-2000. Results show a wide annual average inflow range from + 277% to − 85% when individual climate experiments are assessed. The analysis also show that hydropower generation in Ecuador is highly uncertain and sensitive to climate change since variations in inflow to hydropower stations would directly result in changes in the expected hydropower potential. Annual hydroelectric power production in Ecuador is found to vary between − 55 and + 39% of the mean historical output when considering future inflow patterns to hydroelectric reservoirs covering one standard deviation of the CMIP5 RCP4.5 climate ensemble.

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Section: Hydropower Electricity Modelmentioning

confidence: 99%

Assessing uncertainty of climate change impacts on long-term hydropower generation using the CMIP5 ensemble—the case of Ecuador

et al. 2017

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“…The model also has a range of user-defined constraints to reflect historical operational patterns, technical and resources availability, market share, and so on. A full description and documentation of the model can be found in Kannan and Turton (2011).…”

Section: Swiss Times Electricity Model (St)mentioning

confidence: 99%

“…In SMM, this variation is represented in aggregate, by dividing the annual load curve into six different sub-periods (or "timeslices"). Thus, we couple SMM with an experimental TIMES (The Integrated MARKAL EFOM System) model of the Swiss electricity sector to provide complementary insights (Kannan and Turton, 2011). This Swiss TIMES electricity model (ST model) has an hourly electric load curve for several representative seasons and days, over a long time horizon.…”

Section: Introductionmentioning

confidence: 99%

Swiss Climate Change and Nuclear Policy: A Comparative Analysis Using an Energy System Approach and a Sectoral Electricity Model

Weidmann

Kannan

Turton

2012

Swiss J Economics Statistics

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Summary Decisions on climate change and nuclear policies are likely to have major influences on the future evolution of the Swiss energy system. To understand the implications of selected future policy decisions, we analyse the development of the Swiss energy system with a bottom-up technology-rich least-cost optimisation modelling framework. We use the Swiss MARKAL energy system model and analyse a stringent climate change mitigation policy with two policy variants on the availability of nuclear energy, i.e. with and without nuclear new builds. The energy system modelling approach provides insights into system-wide energy pathways, technology choice and cross-sectoral trade-offs like resource competition, electrification, and CO2 mitigation options across supply and demand sectors. To complement the full system approach, we apply an experimental TIMES model — a successor to MARKAL — of the Swiss electricity sector with a detailed representation of the electricity load curve accounting for diurnal and seasonal variations in demand and resource supply. The analytical results from both modelling approaches are presented and the electricity sector results compared to illustrate the complementary policy insights. The implications for realising an ambitious climate target with and without investment in new nuclear plants are discussed, and a number of areas for possible policy support identified.

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“…Furthermore, the storage feature has been elaborated, as TIMES allows commodities to be stored in one time slice and discharged in another, whereas MARKAL only supports night-to-day-storage. STEM-E is an single-region instance of the TIMES framework covering the entire Swiss electricity system and the interconnection with neighbouring countries [14,15]. Its aim was to analyse the long-term development of the national electricity system and to explore TIMES' suitability as an electricity dispatch model.…”

Section: Timesmentioning

confidence: 99%

“…Parameters and variables are disaggregated and specified accordingly, keeping constant values at segment level. Consequently, this inter-annual subdivision should be sufficiently detailed to capture key characteristics and peaks in time profiles [15]. Time slices aggregate time intervals over the year with similar conditions and thus have no inherent chronology, whereas time steps are sequential uniform paces in time.…”

Section: Temporal Detailmentioning

confidence: 99%

Towards low carbon business park energy systems: Classification of techno-economic energy models

Timmerman

Vandevelde

Eetvelde

2014

Energy

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To mitigate climate destabilisation, human-induced greenhouse gas emissions urgently need to be curbed. A major share of these emissions originates from the industry and energy sectors. Hence, a low carbon shift in industrial and business park energy systems is called for. Low carbon business parks minimise energy-related carbon dioxide emissions by maximal exploitation of local renewable energy production, enhanced energy efficiency, and inter-firm heat exchange, combined in a collective energy system. The holistic approach of techno-economic energy models facilitates the design of such systems, while yielding an optimal trade-off between energetic, economic and environmental performances. However, no models custom-tailored for industrial park energy systems are detected in literature. In this paper, existing energy model classifications are scanned for adequate model characteristics and accordingly, a confined number of models are selected and described. Subsequently, a practical typology is proposed, existing of energy system evolution, optimisation, simulation, accounting and integration models, and key model features are compared. Finally, important features for a business park energy model are identified. IntroductionFossil fuel based energy generation in the manufacturing industry and the sector's consumption of externally produced electricity and heat, are responsible for about 25% of total greenhouse gas emissions on European level [1]. Therefore, a low carbon shift in the energy system of industrial parks must be initiated. Low carbon business parks envision a collective energy system that employs energy efficient technologies, maximises the integration of local renewable energy sources and enables heat exchange between companies [2]. Technoeconomic energy models provide a holistic approach towards the configuration and operation of such systems, and facilitate the optimal trade-off between energetic, economic and environmental performances. To our knowledge, there is no energy model available that has been custom tailored for industrial parks and therefore, the development of such a model by adapting an existing model or by developing a new one is of high priority.Starting from the viewpoint of low carbon business park energy systems, this paper attempts to unravel the plethora of energy models, proposes a pragmatic model categorisation and identifies key model features. Section 2 describes the configuration of a business park energy system and its components and assesses the need for a holistic modelling approach. In section 3, several existing classifications of techno-economic energy models are screened for appropriate model features and based thereon a new classification is proposed. Its model categories are presented and exemplified throughout sections 4 to 9. Section 10 provides a clear comparison between these model types per key characteristic. In section 11, features for efficiently modelling business park energy systems are distilled. Finally, section 13 provides a summary.

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A Long-Term Electricity Dispatch Model with the TIMES Framework

Cited by 78 publications

References 16 publications

Assessing uncertainty of climate change impacts on long-term hydropower generation using the CMIP5 ensemble—the case of Ecuador

Assessing uncertainty of climate change impacts on long-term hydropower generation using the CMIP5 ensemble—the case of Ecuador

Swiss Climate Change and Nuclear Policy: A Comparative Analysis Using an Energy System Approach and a Sectoral Electricity Model

Towards low carbon business park energy systems: Classification of techno-economic energy models

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