Potential for demand side management in automotive manufacturing

Emec, Soner; Kuschke, Maren; Chemnitz, Moritz; Strunz, Kai

doi:10.1109/isgteurope.2013.6695303

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…Dababneh et al [19] and Jin et al [20] used the average, respectively rated power of machines as heating sources in the HVAC planning to reduce peak power demand. For the automotive manufacturing industry, Emec et al [21] researched the load shift and process optimization potential, and concluded a 20% energy consumption and cost savings potential. Tristán et al [22] researched the introduction of an energy management system for three industrial systems in combination with combined heat and power, as well as a photovoltaic array for energy flexible applications.…”

Section: Background and State-of-the-artmentioning

confidence: 99%

Physics-Based Modeling and Parameter Tracing for Industrial Demand-Side Management Applications: A Novel Approach

Leherbauer,

Hehenberger

2024

Sustainability

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The transition to sustainable energy sources presents significant challenges for energy distribution and consumption systems. Specifically, the intermittent availability of renewable energy sources and the decreasing usage of fossil fuels pose challenges to energy flexibility and efficiency. An approach to tackle these challenges is demand-side management, aiming to adapt energy consumption and demand. A key requirement for demand-side management is the traceability of the energy flow among individual energy consumers. In recent years, advancements in industrial information and communication technology have provided additional potential for data acquisition. Complementary to acquired data, a physics-based modeling and analysis approach is proposed, which describes the energy consumption with physical parameters. This results in comprehensive options for monitoring actual energy consumption and planning future energy demand supporting energy efficiency and demand-response goals. To validate the proposed approach, a case study with a 3D printer covering approximately 110 h of active printing time is conducted. The medium-term study results indicate a consistent parameter trend over time, suggesting its conceptual suitability for industrial application. The approach helps to monitor energy efficiency among manufacturing assets by identifying peak loads and consumption hotspots, and provides parameters to estimate energy consumption of manufacturing processes. Results indicate up to 50% energy savings when switching the printing material and indicate further potentials.

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Section: Background and State-of-the-artmentioning

confidence: 99%

Physics-Based Modeling and Parameter Tracing for Industrial Demand-Side Management Applications: A Novel Approach

Leherbauer,

Hehenberger

2024

Sustainability

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“…2) необходимость обеспечения мгновенного баланса между параметрами производства и потребления электроэнергии, в случае рассогласования которого происходит снижение качества электроэнергии и повышение аварийности в электроэнергетической системе [7];…”

Section: теоретическая базаunclassified

Integrated Demand Management for Energy Resources at Industrial Enterprises and in the Region

Дзюба¹

2019

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Рис. 6. Графики почасового спроса на потребление электрической энергии и природного газа различными типами промышленных предприятий Дзюба А.И. Комплексное управление спросом на энергоресурсы на промышленных предприятиях и в регионе

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“…The recent availability of smart home appliances supported by communicant networking was the main force behind the growing interest in developing advanced DSM [1]–[3]. While there has been a great deal of work done, particularly on wireless communication technologies for smart grid [4]–[11], the main challenge is the use of DSM as an efficient tool for load shaping in order to allow electrical appliances to operate during certain time frames (e.g.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Appliances Scheduling in Collaborative MicroGrids System

Bilil

Aniba

Gharavi

2017

IEEE Trans. Power Syst.

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In this paper a new approach which is based on a collaborative system of MicroGrids (MG’s), is proposed to enable household appliance scheduling. To achieve this, appliances are categorized into flexible and non-flexible Deferrable Loads (DL’s), according to their electrical components. We propose a dynamic scheduling algorithm where users can systematically manage the operation of their electric appliances. The main challenge is to develop a flattening function calculus (reshaping) for both flexible and non-flexible DL’s. In addition, implementation of the proposed algorithm would require dynamically analyzing two successive multi-objective optimization (MOO) problems. The first targets the activation schedule of non-flexible DL’s and the second deals with the power profiles of flexible DL’s. The MOO problems are resolved by using a fast and elitist multi-objective genetic algorithm (NSGA-II). Finally, in order to show the efficiency of the proposed approach, a case study of a collaborative system that consists of 40 MG’s registered in the load curve for the flattening program has been developed. The results verify that the load curve can indeed become very flat by applying the proposed scheduling approach.

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Potential for demand side management in automotive manufacturing

Cited by 7 publications

References 5 publications

Physics-Based Modeling and Parameter Tracing for Industrial Demand-Side Management Applications: A Novel Approach

Physics-Based Modeling and Parameter Tracing for Industrial Demand-Side Management Applications: A Novel Approach

Integrated Demand Management for Energy Resources at Industrial Enterprises and in the Region

Dynamic Appliances Scheduling in Collaborative MicroGrids System

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