Process synthesis involving multi-period operations by the P-graph framework

Heckl, István; Halász, László; Szlama, Adrián; Cabezas, Heriberto; Friedler, Ferenc

doi:10.1016/j.compchemeng.2015.04.037

Cited by 41 publications

(15 citation statements)

References 28 publications

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“…This method allows the optimisation of local energy and material demands and supplies situations represented in energy technology networks. Seasonal variations in resource provision and consumptions are treated by a multiperiodic option of the PNS [40].…”

Section: Optimal Energy Systemmentioning

confidence: 99%

Smart energy systems for smart city districts: case study Reininghaus District

Maier

2016

Energ Sustain Soc

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Background: Dense settlement structures in cities have high demands of energy. Usually, these demands exceed the local resource availability. Individually developed supply options to cover these demands differ from place to place and can also vary within the boundaries of a city. In a common sense of European governance, cities are pushed to save energy, increase renewables and reduce import dependency on fossil fuels. There are many innovative concepts and technologies available to tackle these needs. The paper provides a comprehensive methodology for planning and assessing the development of 'smart' energy systems leading to complex energy provision technology networks using different on-site as well as off-site resources. Methods: The use of the P-graph (process-graph) method allows the optimisation of energy systems by using different energy sources for heating, storing and cooling. This paper discusses this method in the development of an urban brown field, the premises of the Reininghaus District, a former brewery in the city of Graz in Austria. The case study is interesting as it combines on-site energy sources (e.g. solar heat and photovoltaic) with nearby industrial waste heat and cooling at different temperatures and grid-based resources such as existing district heating, natural gas, and electricity. The case study also includes the competition between centralised technologies (e.g. large scale combined heat and power and heat pumps with district heating grids) and decentralised technologies (e.g. small scale combined heat and power, single building gas boilers, solar collectors, etc. in buildings). Ecological assessment with the Energetic Long-Term Analysis of Settlement Structures (ELAS) calculator provides an evaluation of the ecological impact of the developed energy systems. Results: Different scenarios based on two building standards OIB (low energy house standard) and NZE (passive house standard) as well as different prices for key energy resources were developed for an urban development concept for the Reininghaus District. The results of these scenarios show a very wide spectrum of structures of the energy system with strong variations often caused by small changes in cost or prices. The optimisation shows that small changes in the setup of the price/cost structure can cause dramatic differences in the optimal energy system to supply a smart city district. However, decentralised systems with low-temperature waste heat and decentralised heat pumps in the building groups show the financially most feasible and, compared to alternatives, most ecological way to supply the new buildings.

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Section: Optimal Energy Systemmentioning

confidence: 99%

Smart energy systems for smart city districts: case study Reininghaus District

Maier

2016

Energ Sustain Soc

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“…The multi-periodic modeling technique itself was first applied to a real world case study where corn production was investigated, for which the supplies and demands both change throughout the year [42]. In another model formulation, the method was used to optimize annual electricity production for various demands and sources.…”

Section: Applicationsmentioning

confidence: 99%

Evaluation of the Energy Supply Options of a Manufacturing Plant by the Application of the P-Graph Framework

et al. 2019

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Industrial applications nowadays are facing the complexity of the problem of finding an optimal energy supply composition. Heating and electricity needs vary throughout a year and need to be addressed. There is usually power available from the market, but a company has other investment options to consider, such as solar power, or utilization of local biomass. Fixed and proportional investment and operational costs must be compared to long-term cost-efficiency. The P-Graph framework is an effective tool in the design and synthesis of process networks, and is capable of showing optimal decisions. In the present work, a new P-Graph model was implemented to address the synthesis of the energy supply options of a manufacturing plant in Hungary. Compared to the original approach, a multi-periodic scheme was applied for heating and electricity demands. Also, the pelletizer and biogas plant investments are modeled in the P-Graph with a new technique that better reflects equipment capacities and flexible input ratios. The best solutions in this case study in terms of total costs are listed. It can be concluded that a long-term investment horizon is needed for the incorporation of sustainable energy sources into the system to be cost-efficient.

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“…Chong et al [43] proposed a novel P-graph method based on carbon capture and storage (CCS) technology to reduce the increased unit cost caused by CCS technology and carbon dioxide emission. [45] This paper extended the range of application of the P-graph from single target to multi-objective problems. This was the first time that the P-graph was used to obtain a dynamic model and stability analysis.…”

Section: P-graph Applications Authorsmentioning

confidence: 99%

Raw material management networks based on an improved P‐graph integrated carbon emission pinch analysis (CEPA‐P‐graph) method

Han

et al. 2019

Can J Chem Eng

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Raw material management plays an essential role in the environment production and carbon emission problem. A P-graph is an effective tool that can be used to solve the raw material management problem. However, raw material management based on the P-graph is complicated and inaccurate. Therefore, this paper proposes an improved P-graph integrating carbon emission pinch analysis (CEPA-P-graph) method to resolve raw material management problem with simpler structures and less results. The proposed method is applied in raw material planning in terms of the regional energy planning problem, and two ethylene plants under carbon emission constraints are examined. As the parameter information of the problem is utilized by pinch technology, the search domain of structure optimization is further reduced, and the computing complexity is reduced, while the advantages of the P-graph multi-solution are guaranteed. The experimental results demonstrate the validity of the proposed method. Furthermore, the CEPA-P-graph could reduce the complexity of solution structure generation by~70% and reduce the carbon emission per unit product by 17%. K E Y W O R D Scarbon emission pinch analysis, P-graph

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Process synthesis involving multi-period operations by the P-graph framework

Cited by 41 publications

References 28 publications

Smart energy systems for smart city districts: case study Reininghaus District

Smart energy systems for smart city districts: case study Reininghaus District

Evaluation of the Energy Supply Options of a Manufacturing Plant by the Application of the P-Graph Framework

Raw material management networks based on an improved P‐graph integrated carbon emission pinch analysis (CEPA‐P‐graph) method

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