Modeling an industrial energy system: Perspectives on regional heat cooperation

Klugman, Sofia; Karlsson, Magnus; Moshfegh, Bahram

doi:10.1002/er.1392

Cited by 19 publications

(13 citation statements)

References 8 publications

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“…MIND is a method for optimisation of dynamic energy systems, based on mixed integer linear programming (MILP) [31]. Areas where MIND has been used include analysis of forest industry [32,33], steel industry [34], and interaction between industries and DH networks [35,36].…”

Section: Optimisation Modelmentioning

confidence: 99%

Biomass gasification opportunities in a district heating system

Difs

Wetterlund

Trygg

et al. 2010

Biomass and Bioenergy

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This paper evaluates the economic eects and the potential for reduced CO 2 emissions when biomass gasication applications are introduced in a Swedish district heating (DH) system. The gasication applications included in the study deliver heat to the DH network while producing renewable electricity or biofuels. Gasication applications included are: external superheater for steam from waste incineration (waste boost, WB), gas engine CHP (BIGGE), combined cycle CHP (BIGCC) and production of synthetic natural gas (SNG) for use as transportation fuel. Six scenarios are used, employing two time-perspectivesshort-term and medium-term -and diering in economic input data, investment options and technical system. To evaluate the economic performance an optimisation model is used to identify the most protable alternatives regarding investments and plant operation while meeting the DH demand. This study shows that introducing biomass gasication in the DH system will lead to economic benets for the DH supplier as well as reduce global CO 2 emissions. Biomass gasication signicantly increases the potential for production of high value products (electricity or SNG) in the DH system. However, which form of investment that is most protable is shown to be highly dependent on the level of policy instruments for biofuels and renewable electricity. Biomass gasication applications can thus be highly interesting for DH suppliers in the future, and may be a vital measure to reach the 2020 targets for greenhouse gases and renewable energy, given continued technology development and long-term policy instruments.

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Section: Optimisation Modelmentioning

confidence: 99%

Biomass gasification opportunities in a district heating system

Difs

Wetterlund

Trygg

et al. 2010

Biomass and Bioenergy

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“…Process integration methods provide useful tools for evaluating possible process alternatives. Several studies of paper and pulp mills have been carried out by using pinch analysis [1][2][3][4][5][6][7] and mathematical programming [8][9][10][11][12][13]. However, the scope of modelling and simulation has not been as complete as it is in many other process industries.…”

Section: Introductionmentioning

confidence: 99%

Simulation and energy optimization of a pulp and paper mill – Evaporation plant and digester

Lundgren

Wang³

et al. 2012

Applied Energy

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A mathematical process integration model of a pulp and paper mill in the Northern Sweden has been developed. The main modelling focus has been put on the two main steam consumers (the evaporation plant and the digester), for which detailed material and energy balances have been established. Operational data have been used to validate the simulation results. By implementing these submodels into the complete plant model, the influence of different operation parameters on the overall plant performance has been investigated. Furthermore, introductory studies with the main objective to minimize the plant energy cost have been carried out. The correlation and differences between economic and energy have been discussed. KeywordsPulp and paper mill, evaporation plant, digester

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“…It was also shown that mixed-integer linear programming (MILP) provides a methodology for determining optimal strategies in order to minimise the overall energy costs in such industries [16]. Studies using such a methodology in a Swedish context include for example [17][18][19][20][21][22][23][24], where MIND (Method for analysis of INDustrial energy systems) was used. MIND is a method developed for optimization of dynamic industrial energy systems [17].…”

Section: Introductionmentioning

confidence: 99%

“…These studies comprise large energy-intensive sites such as Swedish pulp and paper mills and steelworks, e.g. [17][18][19][20][21][22][23][24]. The need to apply the method in other sectors, including small and medium-sized manufacturers such as the Swedish foundry industry, cannot be understated.…”

Section: Introductionmentioning

confidence: 99%

Optimization as investment decision support in a Swedish medium-sized iron foundry – A move beyond traditional energy auditing

2009

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Due to increased globalisation, industries are facing greater competition that is pressing companies into decreasing their expenses in order to increase their profits. As regards Swedish industry, it has been faced with substantial increases in energy prices in recent years. Barriers to energy efficiency such as imperfect information inhibit investments in energy efficiency measures, energy audits being one means of reducing barriers and overcoming imperfect information. However, an evaluation of such energy audits in Sweden reveals that it is chiefly low-cost measures that are undertaken as a result of an audit. Moreover, these audits often tend to focus on support processes such as ventilation, lighting, air compressors etc., while measures impacting production processes are often not as extensively covered, which underlines the need for further support in addition to energy audits. Decision support is practised in a variety of different disciplines such as optimization and simulation and the aim of this paper is to explore whether investment decision support practices may be used successfully towards small and medium-sized manufacturers in Sweden when complex production-related investment decisions are taken. The optimization results from the different cases, involving a foundry's investment in a new melting unit, indicate that with no electricity price fluctuations over the day, the investment seems sound as it lowers the overall energy costs. However, with fluctuating electricity prices, there are no large differences in energy costs between the option of retaining the existing five melting furnaces at the foundry and investing in a twin furnace and removing the holding furnaces -which was the initial investment plan for the foundry in the study. It would not have been possible to achieve this outcome without the use of investment decision support such as MIND. One of the main conclusions in this paper is that investment decision support, when strategic investment decisions are to be taken, may be a means of emphasising energy efficiency for energy-intensive SMEs beyond the level of traditional energy auditing. Keywords

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Modeling an industrial energy system: Perspectives on regional heat cooperation

Cited by 19 publications

References 8 publications

Biomass gasification opportunities in a district heating system

Biomass gasification opportunities in a district heating system

Simulation and energy optimization of a pulp and paper mill – Evaporation plant and digester

Optimization as investment decision support in a Swedish medium-sized iron foundry – A move beyond traditional energy auditing

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