Design and optimization of district energy systems

Weber, Céline; Maréchal, François; Favrat, Daniel

doi:10.1016/s1570-7946(07)80212-4

Cited by 54 publications

(35 citation statements)

References 2 publications

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“…District scale models have been the dominant choice of spatial optimisation since at least the year 2000 [179][180][181][182][183][184][185][186][187][188][189] whilst others have focused on building stock models [190][191][192][193]. It is reflective of the recent advances in both programming software and computational hardware that some researchers have increasingly pushed from district scales towards urban scale models [194][195][196][197][198][199][200][201].…”

Section: ] Citesmentioning

confidence: 99%

A review of urban energy system models: Approaches, challenges and opportunities

Keirstead

Jennings

Sivakumar

2012

Renewable and Sustainable Energy Reviews

530

238

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Energy use in cities has attracted significant research in recent years. However such a broad topic inevitably results in number of alternative interpretations of the problem domain and the modelling tools used in its study. This paper seeks to pull together these strands by proposing a theoretical definition of an urban energy system model and then evaluating the state of current practice. Drawing on a review of 219 papers, five key areas of practice were identified -technology design, building design, urban climate, systems design, and policy assessment -each with distinct and incomplete interpretations of the problem domain. We also highlight a sixth field, land use and transportation modelling, which has direct relevance to the use of energy in cities but has been somewhat overlooked by the literature to date.Despite their diversity, these approaches to urban energy system modelling share four common challenges in understanding model complexity, data quality and uncertainty, model integration, and policy relevance. We then examine the opportunities for improving current practice in urban energy systems * Corresponding author Email addresses: j.keirstead@imperial.ac.uk (James Keirstead), m.jennings09@imperial.ac.uk (Mark Jennings), a.sivakumar@imperial.ac.uk (Aruna Sivakumar) Preprint submitted to Renewable and Sustainable Energy ReviewsOctober 5, 2011modelling, focusing on the potential of sensitivity analysis and cloud computing, data collection and integration techniques, and the use of activity-based modelling as an integrating framework. The results indicate that there is significant potential for urban energy systems modelling to move beyond single disciplinary approaches towards a sophisticated integrated perspective that more fully captures the theoretical intricacy of urban energy systems.

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Section: ] Citesmentioning

confidence: 99%

A review of urban energy system models: Approaches, challenges and opportunities

Keirstead

Jennings

Sivakumar

2012

Renewable and Sustainable Energy Reviews

530

238

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“…The basic concept of the developed model is the decomposition of the problem into several parts, as illustrated in Figure 1. Three major steps (Weber et al [2007]) are; a Structuring phase in which required data will be collected and structured. Secondly the Multi-objective nonlinear optimization phase will solve the district energy system design and produce results in the form of a Pareto frontier.…”

Section: Methodsmentioning

confidence: 99%

“…Poly-generation technologies, joined with the integration of DHN, have a good potential for CO 2 emissions reduction (Weber et al [2007]). A systematic optimization procedure is needed to select and size the equipments and design the physical distribution heating networks.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective, multi-period optimization of district energy systems: Networks design

Fazlollahi

Becker

Guichard

et al. 2013

Computer Aided Chemical Engineering

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A systematic procedure, including process design and integration techniques for designing district heating networks (DHN) is presented in this paper. In the developed model a simultaneous multi objectives and multi-period optimization is principally investigated. The proposed method helps the decision maker to decide; which type and configuration of poly-generation technologies, centralized or decentralized, are best suited for the district, where in the district shall these equipments be implemented (geographically), what are the optimal flow, supply and return temperatures of the networks, taking into account the heat losses, the district's requirements and the technical limits of equipments. The design and the extension of DHN based on the geographical information system (GIS) is the novelty of this work. Finally the proposed model is demonstrated by means of a case study.

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“…The methodology used by OSMOSE can be applied for the optimisation of one or more processes in an industrial plant or for the preliminary design of thermal energy networks between industrial processes at industrial sites or clusters [32,33]. Other applications are the optimisation of the layout and the energy supply system of district energy systems [34], and the design of energy conversion systems in urban areas [35].…”

Section: Osmosementioning

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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Design and optimization of district energy systems

Cited by 54 publications

References 2 publications

A review of urban energy system models: Approaches, challenges and opportunities

A review of urban energy system models: Approaches, challenges and opportunities

Multi-objective, multi-period optimization of district energy systems: Networks design

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

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