Environmentally friendly energy system models using material circulation and energy cascade—the optimization work

Akisawa, Atushi; Kang, Y.T; Shimazaki, Yumi; Kashiwagi, Takao

doi:10.1016/s0360-5442(99)00023-7

Cited by 22 publications

(9 citation statements)

References 2 publications

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“…The thermal energy flows from a higher temperature level to the ambient temperature. During this downfall, the heat can be utilized in multiple processes [4]. Thereby the quality of the energy flow decreases gradually with increasing duration of utilization.…”

Section: Energy Flow and Machine Ecosystemsmentioning

confidence: 99%

Towards energy and resource efficient manufacturing: A processes and systems approach

Duflou¹,

et al. 2012

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Section: Energy Flow and Machine Ecosystemsmentioning

confidence: 99%

Towards energy and resource efficient manufacturing: A processes and systems approach

Duflou¹,

et al. 2012

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“…Energy is critical in supporting people's daily life and continued human development [8]. Although great successes have been achieved, more than two billion people are still lacking of sufficient energy supply throughout the world [6,8,10,12,57]. Particularly, for communities in developing countries or remote areas in developed countries, large-scale fossil fuel supply and grid extension might be impractical due to economic and environmental concerns.…”

Section: Effects Of Climate Change On Rem Systemsmentioning

confidence: 99%

A modeling approach for investigating climate change impacts on renewable energy utilization

Cai

Huang

Yeh

et al. 2011

Int. J. Energy Res.

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SUMMARY In this study, an integrated community‐scale energy model (ICEM) was developed for supporting renewable energy management (REM) systems planning with the consideration of changing climatic conditions. Through quantitatively reflecting interactive relationships among various renewable energy resources under climate change, not only the impacts of climate change on each individual renewable energy but also the combined effects on power‐generation sector from renewable energy resources could be incorporated within a general modeling framework. Also, discrete probability levels associated with various climate change impacts on the REM system could be generated. Moreover, the ICEM could facilitate capacity–expansion planning for energy‐production facilities within a multi‐period and multi‐option context in order to reduce energy‐shortage risks under a number of climate change scenarios. The generated solutions can be used for examining various decision options that are associated with different probability levels when availabilities of renewable energy resources are affected by the changing climatic conditions. A series of probability levels of hydropower‐, wind‐ and solar‐energy availabilities can be integrated into the optimization process. The developed method has been applied to a case of long‐term REM planning for three communities. The generated solutions can provide desired energy resource/service allocation and capacity–expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs, renewable energy availabilities and energy‐shortage risks can also be tackled with the consideration of climate change, which would have both positive and negative impacts on the system cost, energy supply and greenhouse‐gas emission. Copyright © 2011 John Wiley & Sons, Ltd.

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“…There were also a number of software packages, such as Long-range Energy Alternatives Planning System, New Earth 21 Model, National Energy Modeling System and Energy 2020, which were developed to evaluate environmental and economic effects of various energy activities [17,[39][40][41][42][43]. Moreover, in order to deal with facility-expansion issues within energy systems planning problems, mixed integer linear programming (MILP) through the adoption of binary variables was frequently employed to help decide whether or not particular facility-expansion options should be undertaken [44][45][46][47][48]. However, most of these studies could hardly reflect complex linkages that exist among different energy activities and their socio-economic and environmental implications in a multi-sector, multi-period and multi-objective context.…”

Section: Introductionmentioning

confidence: 99%

An inexact optimization model for regional energy systems planning in the mixed stochastic and fuzzy environment

Cai

Huang

Tan

2009

Int. J. Energy Res.

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SUMMARYIn this study, an interval-parameter superiority-inferiority-based regional energy management model has been developed for supporting regional energy management (REM) systems planning under uncertainty. This method is based on an integration of the existing interval mathematical programming, superiority-inferiority-based fuzzy-stochastic programming and mixed integer linear programming techniques. It can explicitly address the system uncertainties that can be expressed as fuzzy-random variables and/or interval numbers. In addition, dynamic interrelationships among system parameters can be successfully reflected through the introduction of fuzzy-random variables and the associated transition probabilities. The developed method has then been applied to a case of long-term REM planning. Useful solutions for the planning of energy management systems have been generated, which can be used for generating decision alternatives and thus help resource managers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired plans for energy resource/ service allocation and facility capacity expansion with a minimized system cost, maximized system reliability and maximized energy security. Tradeoffs between system costs and constraint-violation risk levels can also be tackled. Higher costs will increase system stability, while a desire for lower system costs will run into a risk of potential instability of the management system. The results also suggest that the proposed methodology is applicable to practical problems that are associated with uncertain information.

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Environmentally friendly energy system models using material circulation and energy cascade—the optimization work

Cited by 22 publications

References 2 publications

Towards energy and resource efficient manufacturing: A processes and systems approach

Towards energy and resource efficient manufacturing: A processes and systems approach

A modeling approach for investigating climate change impacts on renewable energy utilization

An inexact optimization model for regional energy systems planning in the mixed stochastic and fuzzy environment

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