1,720,978 research outputs found
An optimization approach to biorefinery setup planning
No full textAs the production of first generation biofuels from corn or rape seed is facing severe criticism due to the perceived competition with food production, second generation biofuels made from non-food biomass are being developed to fill the gap. These can be made from lignocellulosic residues instead of agricultural products, which is commonly considered to make competition for soils and land-use change less severe. Economic competitiveness for this kind of biofuels could however not be established so far for various reasons, such as complex and expensive plant technology and the need of biomass transportation to the plant. In contrast to large fossil plants, economies of scale are overcompensated by increasing specific biomass transportation cost for large biorefineries. In order to suitably approximate these effects, a nonlinear optimization model is presented in this paper to simultaneously identify optimal plant setups and capacities. In this model, the co-production of other hydrocarbon products in addition to fuels in biorefineries through different combinations of FischereTropsch product upgrading processes is considered. As the optimal plant capacity also depends on the economic value of the plant's products, several biorefinery process setups and their corresponding process-specific economies of scale are compared with regard to their economic viability. (C) 2014 Elsevier Ltd. All rights reserved.University of Gottingen, German
Determinants of economically optimal cassava-to-ethanol plant capacities with consideration of GHG emissions
No full textThe 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
Simultaneously optimizing the capacity and configuration of biorefineries
No full textAdvanced 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.
Here, 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
Improving biorefinery planning: Integration of spatial data using exact optimization nested in an evolutionary strategy
No full textBiorefineries 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
Estimating the revenue potential of flexible biogas plants in the power sector
No full textThe 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. Using 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. Our 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
Two-Stage Unit Commitment Modeling for Virtual Power Plants
No full textThe development of an increasingly decentralized, renewable power supply requires adequate planning approaches. Compared to unit commitment planning in regulated markets with a dominant share of dispatchable power generation, power systems with large shares of intermittent renewable power sources such as wind or photovoltaics are subject to uncertain supply as well as uncertain load forecasts and prices.
Virtual Power Plants have been developed to aggregate intermittent renewables with so-called flexibility options, which include dispatchable power plants, storage systems and flexible power consumers. Dispatchable power plants, such as biogas plants, include all that can actively be committed to supply power in a time interval. Storage systems, such as pumped-storage hydroelectricity, can store power in times of low prices and resell it when prices rise. Flexible power consumers, such as operators of electric vehicles, can attempt to use these time windows to load the batteries, lowering their power purchasing costs.
In the current German power market, power can be traded either in auctions on the day before physical delivery or in continuous intraday trading on the day itself. To determine optimal schedules for flexibility options in the context of day-ahead or intraday markets, a two-stage unit commitment model is presented to deal with the uncertainty of market prices resulting from the interplay of power generation in wind turbines and photovoltaic cells one the one hand with power demand on the other
Demand side integration for electric transport vehicles
No full textPurpose – The purpose of this study is to examine both the technical feasibility and the commercial viability of several demand-side integration (DSI) programs to utilize the charging flexibility of electric transport vehicles in a logistic facility. DSI is important for improving system reliability and assisting in integrating renewables into the energy system. Design/methodology/approach – A pre-assessment of several DSI programs is performed by considering effort for implementation, costs and economic potential. Afterward, the most promising programs are compared economically on the basis of optimization methods and economic analysis. The analysis is based on a comprehensive electric mobility project dealing with electric transport vehicles operating in container terminals. Findings – The pre-assessment of several potential DSI programs revealed that many of these programs are unsuitable, largely due to regulatory requirements. Although using DSI to optimize the company’s load is feasible, controlled charging based on variable prices is particularly advantageous because the implementation requires modest effort while identifying significant cost-saving potentials. Practical implications – Based on the analysis, other companies using electric transport vehicles have a foundation for identifying the most promising demand-side management program. Originality/value – While most research has focused on individually used electric vehicles, here commercial electric transport vehicles operating in closed systems were investigated as this area of application was found to be particularly suitable for participation in DSI programs
Strategic planning of a multi-product wood-biorefinery production system
No full textProducts 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
Using PROMETHEE to assess bioenergy pathways
No full textInvestment 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
Decision Support for the Planning of Production Systems for Renewable Resources
Full text linkFor the substitution of fossil fuels with renewables, the use of biomass in production processes is often considered ambivalent regarding economic viability and other sustainability criteria. To address the sustainability and efficiency concerns associated with biomass conversion, concepts for multi-input and multi-output biorefineries have been discussed and tested. However, lacking economic viability, none have been realized on an industrial scale until today. Instead, biogas plants, mostly used for combined heat and power generation, have become the most prevalent biomass conversion process in Germany. Incentivized by feed-in tariffs and other subsidies, almost 10,000 biogas plants operate in Germany in 2019. These and other biomass-fueled plants can produce power flexibly, but at higher cost than most other renewable and fossil power plants.
In order to make sound decisions for production systems for renewable resources, comprehensive decision support is needed. The choices of capacity, configuration and location are among the major challenges for the planning of such production systems. This habilitation elaborates decision support by considering relevant strategic and operational aspects of production systems for renewable resources. The covered strategic aspects concentrate on the interdependent choices of plant capacity, configuration and location, which are addressed with nonlinear programming and geographic information systems. For plants for the conversion of biomass, large plant capacities lead to both economies of scale and rising specific transportation cost, which plays a major role for their economic viability. The operational aspect of scheduling flexible and programmable power generation and consumption is investigated as well because of its rising importance due to the increasing share of intermittent power generation from photovoltaic cells and wind turbines. Optimization models, application programming interfaces and available data sources are combined to offer the aspired decision support.2022-10-0
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