Analysis of a Micro-CHP Unit with in-series SOFC Stacks Fed by Biogas

Kupecki, Jakub; Skrzypkiewicz, Marek; Wierzbicki, Michał; Stępień, Michał

doi:10.1016/j.egypro.2015.07.265

Cited by 14 publications

(4 citation statements)

References 6 publications

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“…The agents are equipped with local anaerobic digesters, distributed generation units by means of micro Combined Heat and Power (µ-CHP) devices, heat buffers, fuel cells, and decentralized gas storage devices. The µ-CHP devices run on biogas generated from organic waste using local anaerobic digesters [12], [13], [14]. The biogas µ-CHP devices are switched on to satisfy the local power and heat demand.…”

Section: A Considered Settingmentioning

confidence: 99%

“…• It can be used as a fuel for running the µ-CHP devices in order to satisfy the prosumers' local heat and power demands [14]. It can also be used to help the connected prosumers to satisfy their local demands.…”

Section: A a Micro Grid Of Prosumersmentioning

confidence: 99%

“…, t a > 0 defines the relative importance of maintaining the inside temperature close to the given target T a (k) compared to other control goals. (14), and (16) − (18).…”

Section: Objectivesmentioning

confidence: 99%

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Asynchronous Distributed Control of Biogas Supply and Multienergy Demand

Alkano

Scherpen

Chorfi

2017

IEEE Trans. Automat. Sci. Eng.

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In this paper we study the coordination between biogas producers who can either use the biogas themselves, exchange biogas with their neighbors, or deliver it to the various energy grids, such as the low pressure gas grid or the power grid. These producers are called prosumers. In this setting gas storage, fuel cells, micro combined heat power systems, and heat buffers are all part of the prosumers' node. We aim to optimize the imbalance, profit, and comfort levels per prosumer, while taking the constraints of the energy grids into account, and while allowing prosumers to exchange energy with each other. This results in a two-layer optimization problem formulation. In addition, in practice, communication between prosumers among each other and with grid operators is done in an asynchronous manner. In this paper we study the problem of two-layer optimization for biogas prosumers embedded in multiple energy grids, while the (bidirectional) communication between the various partners is done asynchronously. We prove the convergence of the asynchronous coordination algorithm that uses both the inputs and the states. We conduct simulations for the biogas prosumer setting, using realistic data to illustrate the convergence of the algorithm and to study its practical implementation. Note to Practitioners-This paper is motivated and supported by a smart gas grid project of the Energy Delta Gas Research (EDGaR) consortium in the Netherlands. The project deals with investigating the capacity of smart grid technologies to facilitate the introduction of new gases into the distribution grids, with diverse gas qualities and multiple injection points. The gas distribution grid will have to move from a passive to an active distribution system that dynamically control bidirectional flows between end-users and the grid operators. As the endusers may be equipped with energy converters, other energy distribution grids also need to transform to active distribution systems. Existing approaches are distributed, where each enduser and energy grid operator can locally solve their optimal control problem. In this paper, we consider the fact that both endusers and grid operators do not have access to a common clock when solving their problem and when sharing their information. The information includes some of their states and controllable inputs. The asynchronous information exchange problem was pointed out by DNV GL Netherlands, Gasunie, and Gasterra which are companies we collaborate with within the EDGaR consortium. It is highly relevant for practical implementation of our distributed algorithms. In future research, we will include practical control considerations due to on-off constraints of

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Section: A Considered Settingmentioning

confidence: 99%

Section: A a Micro Grid Of Prosumersmentioning

confidence: 99%

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Asynchronous Distributed Control of Biogas Supply and Multienergy Demand

Alkano

Scherpen

Chorfi

2017

IEEE Trans. Automat. Sci. Eng.

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“…Therefore, it was concluded that there have to be a trade-off between voltage, effi ciency and power with respect to current density to match effi ciency and costs 6 . Numerical analysis of the complete system including fuel processor, SOFC stacks and Balance of Plant, BoP, components fed by biogas were performed by Kupecki et al 10 . Two identical commercial electrolyte supported SOFC stacks in parallel and in-series connections were evaluated in Aspen HYSYS 8.0.…”

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confidence: 99%

Simulation of SOFCs based power generation system using Aspen

Pianko‐Oprych

Palus

2017

Polish Journal of Chemical Technology

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This study presents a thermodynamic Aspen simulation model for Solid Oxide Fuel Cells, SOFCs, based power generation system. In the fi rst step, a steady-state SOFCs system model was developed. The model includes the electrochemistry and the diffusion phenomena. The electrochemical model gives good agreement with experimental data in a wide operating range. Then, a parametric study has been conducted to estimate effects of the oxygen to carbon ratio, O/C, on reformer temperature, fuel cell temperature, fuel utilization, overall fuel cell performance, and the results are discussed in this paper. In the second step, a dynamic analysis of SOFCs characteristic has been developed. The aim of dynamic modelling was to fi nd the response of the system against the fuel utilization and the O/C ratio variations. From the simulations, it was concluded that both developed models in the steady and dynamic state were reasonably accurate and can be used for system level optimization studies of the SOFC based power generation system.

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