The EFOM 12C energy supply model within the EC modelling system

Voort, E. van der

doi:10.1016/0305-0483(82)90007-x

Cited by 35 publications

(13 citation statements)

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“…As highlighted above, this review focuses on the TSA methods in bottom-up energy system optimization models that include generation expansion planning (GEP), as well as unit commitment (UC) and have constantly emerged and evolved since the late 1970s and 1980s [9,11]. Among the early model frameworks, one group focuses on long-term system planning and has usually only one time step per year such as LEAP [43], EFOM [44], and BESOM [45], which are not subject to aggregation techniques and thus neglected in the following. The temporal dimension of the other major group of early bottom-up ESMs such as TIMES [46][47][48][49] and its predecessors MARKAL [50], MESSAGE [12,51], IKARUS [9], and PERSEUS [52] are based on time slice formulations (in the case of PERSEUS called "time slots"), which are explained in more detail in Section 3.2.1.…”

Section: Methodology and Structure Of The Reviewmentioning

confidence: 99%

“…The temporal dimension of the other major group of early bottom-up ESMs such as TIMES [46][47][48][49] and its predecessors MARKAL [50], MESSAGE [12,51], IKARUS [9], and PERSEUS [52] are based on time slice formulations (in the case of PERSEUS called "time slots"), which are explained in more detail in Section 3.2.1. Although the long-term planning models with only one time step per year were consecutively combined with models with a higher temporal resolution, as is the case for TIMES [46][47][48][49] as a combination of MARKAL [50] and EFOM [44], the time slice approach, which is based on the modeler's experience only, remained unchanged for decades. With the first approaches to classify and group demand curves using unsupervised learning techniques, which the authors traced back to 1999 [53], new techniques for defining the temporal dimension of ESMs arose.…”

Section: Methodology and Structure Of The Reviewmentioning

confidence: 99%

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A Review on Time Series Aggregation Methods for Energy System Models

et al. 2020

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Due to the high degree of intermittency of renewable energy sources (RES) and the growing interdependences amongst formerly separated energy pathways, the modeling of adequate energy systems is crucial to evaluate existing energy systems and to forecast viable future ones. However, this corresponds to the rising complexity of energy system models (ESMs) and often results in computationally intractable programs. To overcome this problem, time series aggregation (TSA) is frequently used to reduce ESM complexity. As these methods aim at the reduction of input data and preserving the main information about the time series, but are not based on mathematically equivalent transformations, the performance of each method depends on the justifiability of its assumptions. This review systematically categorizes the TSA methods applied in 130 different publications to highlight the underlying assumptions and to evaluate the impact of these on the respective case studies. Moreover, the review analyzes current trends in TSA and formulates subjects for future research. This analysis reveals that the future of TSA is clearly feature-based including clustering and other machine learning techniques which are capable of dealing with the growing amount of input data for ESMs. Further, a growing number of publications focus on bounding the TSA induced error of the ESM optimization result. Thus, this study can be used as both an introduction to the topic and for revealing remaining research gaps.

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Section: Methodology and Structure Of The Reviewmentioning

confidence: 99%

Section: Methodology and Structure Of The Reviewmentioning

confidence: 99%

A Review on Time Series Aggregation Methods for Energy System Models

et al. 2020

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“…Many researchers including [131][132][133][134][135][136][137][138][139][140] applied MARKAL energy model for large scale energy planning. The EFOM energy model was used in different states including [141][142][143][144][145][146][147][148]. There are also other energy planning models including LEAP, New Earth 21 and National Energy Modeling Systems which have been established and applied in many countries including [149][150][151][152][153][154][155][156].…”

Section: Review Of Literaturementioning

confidence: 99%

Recent Updates on Energy Planning Models - A Review

Hafeez

Gulshan

Tahira

2020

Journal of Mechanical and Energy Engineering

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Energy is the most important part for community and financial growth of any country. Energy planning models play a vital role in strategy formulation and power sector progress. In this paper a systematic review and comparison of energy planning models developed and applied from 1977-2019 has been presented. The review indicates that most of the energy planning models has been presented and applied in developed nations. Only few numbers of energy planning models have been presented and applied in under developing countries. The review also shows the comparison of energy planning models applied in developed and under-developed countries. This review article will assistance the energy managers, scholars and strategy makers broadly.

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“…In clean evaluation aspect, the support indexes include clean energy ration to primary energy consumption, sulfur dioxide discharge strength, sulfur dioxide discharge value, environmental pollution control investment ration to GDP, clean energy generate electricity ration and other indices. In the high effective aspect, the support indexes include energy loss per GDP, energy processing and transforming efficiency, power energy ration to terminal energy consumption [10]- [13]. …”

Section: B Indicator System Of Energy Supply and Demand Patternmentioning

confidence: 99%

High Proportion Renewable Energy Supply and Demand Structure Model in 2050

Xiong¹,

Liu²,

Wei³

et al. 2017

JOCET

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Abstract-In considering of high proportion of renewable energy supply in 2050, the accelerating of energy consumption gross, source and environment can affect the energy system restrict affection are stronger. Add wind and solar to electricity energy with large amount of energy source exploitation. The energy source amount per person is lower. Considering the renewable energy amount and supply, primary energy storage and structure problem is standing out. Before the wide spread of renewable energy, Using the high-carbon energy in China can pollute seriously. Chinese energy supply and demand problem is research key point. This paper researches Chinese energy supply and demand pattern system and evaluation methodology, gives out the inner and outer influencing elements. And evaluate Chinese energy supply and demand pattern from energy gross, structure, distribution and transportation. Use energy supply synthesize radar comparison chart in certain time period. From energy security, economy, clean and efficiency, analyze the benefit comparisons of Chinese energy supply and demand pattern. This energy supply and demand pattern model will give one certain theoretical analysis and practice reference to the further high proportion of renewable energy.Key words-Benefit, high proportion of renewable energy supply, inner and outer element, power grid affection, supply and demand pattern.

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The EFOM 12C energy supply model within the EC modelling system

Cited by 35 publications

References 1 publication

A Review on Time Series Aggregation Methods for Energy System Models

A Review on Time Series Aggregation Methods for Energy System Models

Recent Updates on Energy Planning Models - A Review

High Proportion Renewable Energy Supply and Demand Structure Model in 2050

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