Geldermann, Jutta

[["dc.bibliographiccitation.firstpage","12"],["dc.bibliographiccitation.journal","Computers & Industrial Engineering"],["dc.bibliographiccitation.lastpage","23"],["dc.bibliographiccitation.volume","124"],["dc.contributor.author","Lauven, Lars-Peter"],["dc.contributor.author","Karschin, Ingo"],["dc.contributor.author","Geldermann, Jutta"],["dc.date.accessioned","2020-12-10T14:23:06Z"],["dc.date.available","2020-12-10T14:23:06Z"],["dc.date.issued","2018"],["dc.description.abstract","Advanced biomass conversion plants can replace fossil resources in the electricity, heat, transportation fuels and chemicals sectors, but they face specific challenges with regard to their economic operation. When choosing a capacity for a biomass conversion plant, economies of scale must be weighed against the transportation costs for the widely-distributed input materials.\r\n\r\nHere, we model the problem of determining the optimal capacity for plants with a single product or a fixed set of products using a single optimization variable and two alternative economic objective functions. To identify the factors that most strongly influence economic plant operation, we perform a sensitivity analysis of various model parameters to determine their impact on the optimal solution using the Envelope Theorem. We also present an optimization approach for simultaneously planning the capacity and configuration of multi-product plants. By modeling economies of scale on a process-specific level, our nonlinear optimization approach makes it possible to determine the optimal configurations, and thus ranges of products, for changing plant capacities. An examination of the obtained feasible solutions shows that the optimization problem is neither convex nor concave."],["dc.identifier.doi","10.1016/j.cie.2018.07.014"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71835"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Professur für Produktion und Logistik"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Simultaneously optimizing the capacity and configuration of biorefineries"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1005"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","European Journal of Operational Research"],["dc.bibliographiccitation.lastpage","1019"],["dc.bibliographiccitation.volume","264"],["dc.contributor.author","Schröder, Tim"],["dc.contributor.author","Lauven, Lars-Peter"],["dc.contributor.author","Geldermann, Jutta"],["dc.date.accessioned","2020-12-10T14:23:40Z"],["dc.date.available","2020-12-10T14:23:40Z"],["dc.date.issued","2018"],["dc.description.abstract","Biorefineries can provide a product portfolio from renewable biomass similar to that of crude oil refineries. To operate biorefineries of any kind, however, the availability of biomass inputs is crucial and must be considered during planning. Here, we develop a planning approach that uses Geographic Information Systems (GIS) to account for spatially scattered biomass when optimizing a biorefinery’s location, capacity, and configuration. To deal with the challenges of a non-smooth objective function arising from the geographic data, higher dimensionality, and strict constraints, the planning problem is repeatedly decomposed by nesting an exact nonlinear program (NLP) inside an evolutionary strategy (ES) heuristic, which handles the spatial data from the GIS. We demonstrate the functionality of the algorithm and show how including spatial data improves the planning process by optimizing a synthesis gas biorefinery using this new planning approach."],["dc.identifier.doi","10.1016/j.ejor.2017.01.016"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/72009"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Professur für Produktion und Logistik"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Improving biorefinery planning: Integration of spatial data using exact optimization nested in an evolutionary strategy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1502"],["dc.bibliographiccitation.journal","Journal of Cleaner Production"],["dc.bibliographiccitation.lastpage","1516"],["dc.bibliographiccitation.volume","211"],["dc.contributor.author","Schröder, T."],["dc.contributor.author","Lauven, Lars-Peter"],["dc.contributor.author","Sowlati, T."],["dc.contributor.author","Geldermann, J."],["dc.date.accessioned","2020-12-10T14:24:57Z"],["dc.date.available","2020-12-10T14:24:57Z"],["dc.date.issued","2019"],["dc.description.abstract","Products derived from crude oil form the basis for large segments of energy and production systems. However, the availability of crude oil is limited and the combustion of fossil fuels contributes to global warming. Biorefineries can produce a product portfolio similar to that of crude-oil refineries from renewable resources and thus promote transformation towards a more sustainable bioeconomy. The actual product portfolio of a given biorefinery, however, depends on the choice and capacity of the production units used to upgrade raw materials to marketable products. Thus, to improve biorefinery product competitiveness, we apply an algorithm that combines an exact optimization algorithm nested in an Evolutionary Strategy with Geographic Information Systems to determine a wood-based biorefinery's optimal configuration, capacity, and location within the Cariboo District in Canada. The results indicate that there are numerous locations with similarly attractive economic potentials for biorefineries with 450,000 to 550,000 tons of biomass input capacity in the investigated area."],["dc.identifier.doi","10.1016/j.jclepro.2018.12.004"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/72395"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Professur für Produktion und Logistik"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Strategic planning of a multi-product wood-biorefinery production system"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","287"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Central European Journal of Operations Research"],["dc.bibliographiccitation.lastpage","309"],["dc.bibliographiccitation.volume","27"],["dc.contributor.author","Schröder, Tim"],["dc.contributor.author","Lauven, Lars-Peter"],["dc.contributor.author","Beyer, Beatriz"],["dc.contributor.author","Lerche, Nils"],["dc.contributor.author","Geldermann, Jutta"],["dc.date.accessioned","2020-12-10T14:11:10Z"],["dc.date.available","2020-12-10T14:11:10Z"],["dc.date.issued","2019"],["dc.description.abstract","Investment and policy decisions in the context of sustainable development are classic application areas for multi-criteria decision analysis. Ranking various pathways, i.e. conversion routes, for biomass use in the energy sector is particularly challenging. Depending on how ecological, economic, and social criteria are weighed, a multi-criteria decision analysis can lead to significantly contrasting recommendations. In this paper, we present a decision support for eleven energy pathways using decision criteria drawn from all three sustainability dimensions—ecological, economic, and social. For the graphical presentation of the relatively large number of pathways and criteria weightings, we introduce a novel visualization approach that combines the results of both PROMETHEE I and II. This visualization approach permits stakeholders to quickly and intuitively gather insights about the result structure and the consequences of different input parameters, for instance different criteria weightings."],["dc.identifier.doi","10.1007/s10100-018-0590-3"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/70989"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Professur für Produktion und Logistik"],["dc.rights","CC BY 4.0"],["dc.title","Using PROMETHEE to assess bioenergy pathways"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1246"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Applied Thermal Engineering"],["dc.bibliographiccitation.lastpage","1252"],["dc.bibliographiccitation.volume","70"],["dc.contributor.author","Lauven, Lars-Peter"],["dc.contributor.author","Liu, Beibei"],["dc.contributor.author","Geldermann, Jutta"],["dc.date.accessioned","2018-11-07T09:35:06Z"],["dc.date.available","2018-11-07T09:35:06Z"],["dc.date.issued","2014"],["dc.description.abstract","The successful realization of biofuel plants depends on a number of economic and ecological factors. In this work, the production of bioethanol from cassava in China's Guangxi province is investigated by combining an economic optimization approach with results from corresponding Life Cycle Assessments. By using the potential plant's capacity as the optimization variable, it becomes possible to show the trade-offs associated with different capacities, especially with regard to the achievable profitability and the corresponding greenhouse gas emissions. In contrast to distinct case studies, this approach aims for the identification of optimal capacities from a continuous range of potential capacities. The combined assessment is then applied to a Chinese scenario to determine the effects of factors such as fertilizer application and of the conversion of fresh cassava to cassava chips to identify favorable options for potential future cassava-to-ethanol plants. In general, such modeling approaches are expected to facilitate the bioenergy plant planning by approximating the economic and ecological consequences of plants of different capacities. (C) 2014 Elsevier Ltd. All rights reserved."],["dc.identifier.doi","10.1016/j.applthermaleng.2014.05.009"],["dc.identifier.isi","000341556200020"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/32319"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1359-4311"],["dc.relation.orgunit","Professur für Produktion und Logistik"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Determinants of economically optimal cassava-to-ethanol plant capacities with consideration of GHG emissions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","402"],["dc.bibliographiccitation.journal","Energy Policy"],["dc.bibliographiccitation.lastpage","410"],["dc.bibliographiccitation.volume","128"],["dc.contributor.author","Lauven, Lars-Peter"],["dc.contributor.author","Geldermann, Jutta"],["dc.contributor.author","Desideri, Umberto"],["dc.date.accessioned","2022-09-12T08:26:54Z"],["dc.date.available","2022-09-12T08:26:54Z"],["dc.date.issued","2019"],["dc.description.abstract","The expansion of intermittent renewable power poses new challenges: Balancing fluctuations in power supply and demand requires additional flexibility. In this work, we model a unit commitment optimization problem to investigate the economic feasibility of concepts for flexible power generation from biogas. Because the economics of flexible power generation also depend on the availability of other flexibility options, we compared flexible biogas plants in power markets with different characteristics, namely Germany, northern Italy, and the islands of Sardinia and Sicily.\r\n\r\nUsing an algorithm to optimize the constrained mixed-integer unit commitment of biogas plants, we determine hourly optimal production schedules in each region based on the prices from 2008 to 2017. The algorithm helps to assess whether the investment for equipment that required for flexible electricity production, such as a larger generator and storage facilities, would have been justified by the likely additional revenue in the investigated period.\r\n\r\nOur results show that the premium that flexible biogas plants can earn over non-flexible ones has decreased significantly between 2008 and 2017 in all investigated regions. Since 2015, additional incentives have been indispensable in all four investigated regions to make the concept of producing power from biogas flexibly economically viable."],["dc.identifier.doi","10.1016/j.enpol.2019.01.007"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114203"],["dc.language.iso","en"],["dc.relation.issn","0301-4215"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Estimating the revenue potential of flexible biogas plants in the power sector"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]