Dr. Zhiwei Shen

Profil

• Die Minderung der Datenknappheit bei der Bewertung von Ernteversicherungen anhand räumlicher Informationen: Ein Propagation-Separations-Ansatz

  Quelle ↗

  Förderer: DFG Eigene Stelle (Sachbeihilfe) Zeitraum: 08/2017 - 10/2018 Projektleitung: Dr. Zhiwei Shen

• Agroscope

  PT

  16 Treffer55.1%
  • CowData (Verbesserung des Betriebsmanagements durch Kombination von Stall- und Weidedaten)
    P

    55.1%

• Landesamt für Verbraucherschutz, Landwirtschaft und Flurneuordnung Brandenburg

  P

  14 Treffer55.0%
  • Sortenstrategien bei landwirtschaftlichen Nutzpflanzen zur Anpassung an den Klimawandel
    P

    55.0%

• Landesbauernverband Brandenburg e.V.

  P

  14 Treffer55.0%
  • Sortenstrategien bei landwirtschaftlichen Nutzpflanzen zur Anpassung an den Klimawandel
    P

    55.0%

• Märkischer Saatgutverband Brandenburg e.V.

  P

  14 Treffer55.0%
  • Sortenstrategien bei landwirtschaftlichen Nutzpflanzen zur Anpassung an den Klimawandel
    P

    55.0%

• Science & Startups Berlin

  T

  1 Treffer53.5%
  • Zuwendung im Rahmen des Programms „exist – Existenzgründungen aus der Wissenschaft“ aus dem Bundeshaushalt, Einzelplan 09, Kapitel 02, Titel 68607, Haushaltsjahr 2026, sowie aus Mitteln des Europäischen Strukturfonds (hier Euro-päischer Sozialfonds Plus – ESF Plus) Förderperiode 2021-2027 – Kofinanzierung für das Vorhaben: „exist Women“
    T

    53.5%

• Abiomics Europe KFT

  P

  4 Treffer52.9%
  • Validating C. Elegans Healthspan Model for Better Understanding Factors Causing Health and Disease, to Develop Evidence Based Prevention, Diagnostic, Therapeutic and Other Strategies
    P

    52.9%

• Biopolis S.L.

  P

  6 Treffer52.9%
  • Validating C. Elegans Healthspan Model for Better Understanding Factors Causing Health and Disease, to Develop Evidence Based Prevention, Diagnostic, Therapeutic and Other Strategies
    P

    52.9%
  • Climate-smart rewilding: ecological restoration for climate change mitigation, adaptation and biodiversity support in Europe
    P

    49.9%

• AnalytiCon Discovery GmbH

  P

  4 Treffer52.9%
  • Validating C. Elegans Healthspan Model for Better Understanding Factors Causing Health and Disease, to Develop Evidence Based Prevention, Diagnostic, Therapeutic and Other Strategies
    P

    52.9%

• International Business Machines Corporation Research GmbH

  P

  28 Treffer52.8%
  • EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)
    P

    52.8%
  • EU: Simulation in Multiscale Physical and Biological Systems (STIMULATE)
    P

    52.6%

• Graphenea S.A.

  P

  19 Treffer52.8%
  • EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)
    P

    52.8%

• Challenges and Mitigation Measures in Power Systems with High Share of Renewables—The Australian Experience

  2022

  Energies · 90 Zitationen · DOI

  Australia is one of the leading countries in energy transition, and its largest power system is intended to securely operate with up to 75% of variable renewable generation by 2025. High-inertia synchronous condensers, battery energy storage systems, and grid-forming converters are some of the technologies supporting this transformation while facilitating the secure operation of the grid. Synchronous condensers have enabled 2500 MW of solar and wind generation in the state of South Australia, reaching minimum operational demands of ≈100 MW. Grid-scale battery energy storage systems have demonstrated not only market benefits by cutting costs to consumers but also essential grid services during contingencies. Fast frequency response, synthetic inertia, and high fault currents are some of the grid-supporting capabilities provided by new developments that strengthen the grid while facilitating the integration of new renewable energy hubs. This manuscript provides a comprehensive overview, based on the Australian experience, of how power systems are overcoming expected challenges while continuing to integrate secure, low cost, and clean energy.

• Forecasting volatility of wind power production

  2016

  Applied Energy · 65 Zitationen · DOI

• Challenges of insuring weather risk in agriculture

  2014

  Agricultural Finance Review · 62 Zitationen · DOI

  Purpose – The purpose of this paper is to review some challenges of insuring weather risk in agriculture and to discuss potential remedies for these problems. Design/methodology/approach – The paper is developed as a narrative on weather insurance based largely on existing literature. Findings – Weather risks show characteristics that often violate classical requirements for insurability. First, some weather risks, particularly slowly emerging weather perils like drought, are spatially correlated and cause systemic risks. Second, climatic change may increase the volatility of weather variables and lead to non-stationary loss distributions, which causes difficulties in actuarial ratemaking. Third, limited availability of yield and weather data hinders the estimation of reliable loss distributions. Practical implications – Some of the approaches discussed in this review, such as time diversification, local test procedures and the augmentation of observational data by expert knowledge, can be useful for crop insurance companies to improve their risk management and product design. Originality/value – This study provides background and development information regarding weather insurance and also presents statistical tools and actuarial methods that support the assessment of weather risks as well as the design of weather and yield insurance products.

• Designing an index for assessing wind energy potential

  2015

  Renewable Energy · 45 Zitationen · DOI

• Coping with systemic risk in index‐based crop insurance

  2012

  Agricultural Economics · 36 Zitationen · DOI

  Abstract The implementation of index‐based crop insurance is often impeded by the existence of systemic risk of insured losses. We assess the effectiveness of two strategies for coping with systemic risk: regional diversification and securitization with catastrophe (CAT) bonds. The analysis is conducted in an equilibrium pricing framework which allows the optimal price of the insurance and the number of traded contracts to be determined. We also explore the role of basis risk and risk aversion of market agents. The model is applied to a hypothetical area yield insurance for rice producers in northeast China. If yields in two regions are positively correlated, we find that enlarging the insured area leads to higher insurance premiums. Unless capital market investors are very risk averse, a CAT bond written on an area yield index outperforms regional diversification in terms of certainty equivalents of both farmers and insurers.

• Artificial intelligence and digital twins in power systems: Trends, synergies and opportunities

  2023

  Digital Twin · 33 Zitationen · DOI

  Artificial Intelligence (AI) promises solutions to the challenges raised by the digitalization of power grids and their assets. Decision-making, forecasting and even operational optimization of grids and assets are just some of the solutions that AI algorithms can provide to operators, utilities and vendors. Nevertheless, barriers such as access to quality datasets, interpretability, repeatability, and availability of computational resources currently limit the extent of practical AI implementations. At the same time, Digital Twins (DTs) are foreseen as platforms that can overcome these barriers, and also provide a new environment for the development of enhanced and more intelligent applications. In this manuscript, we review the published literature to determine the existing capabilities and implementation challenges of AI algorithms in power systems, and classify AI-based applications based on their time scale to reveal their temporal sensitivity. Furthermore, DT-based technologies are discussed, identifying the potentials to tackle current limitations of real-world AI applications as well as exploring the synergies between DTs and AI. By combining AI and DT, we outline multiple prospective use cases for AI-enhanced power grid and power asset DTs. Our review also identifies that the combination of AI-based solutions and DTs leverages new applications with the potential to fundamentally change multiple aspects of the power industry.

• Numerical simulation of crack formation process in clays during drying and wetting

  2006

  Geomechanics and Geoengineering · 31 Zitationen · DOI

  Clays generally crack upon drying and the cracks gradually close up because of expansion of the clays induced by rainfall infiltration. Based on the concept of air drainage ratio, we introduce an improved simplified consolidation theory for unsaturated soils and apply it to solve the crack formation problem. We present initial conditions, special consideration, and finite-element (FEM) formulations for simulation of cracks under axisymmetric conditions. Similar to finding solutions for sand-well consolidation problems, a prism of clays surrounded by polygonal distributed cracks is simplified as a cylinder. Numerical simulations using the FEM formulations are performed on the processes of crack occurrence, propagation, and closure during drying and wetting. To investigate the influence of air drainage ratio distribution, three different schemes are adopted for computation. It is found that the behaviour of cracks in clays during drying and wetting can be well represented using the approach proposed in the paper. The simplified consolidation theory used in the paper for unsaturated soils is more suitable for crack analysis than the general consolidation theory currently applied.

• Can expert knowledge compensate for data scarcity in crop insurance pricing?

  2015

  European Review of Agricultural Economics · 26 Zitationen · DOI

  Although there is an increasing interest in area yield insurance in many developing countries, crop data scarcity hinders its implementation by imposing higher premiums. Expert knowledge has been considered a valuable information source to augment limited data in insurance pricing. This article investigates whether the use of expert knowledge can mitigate model risk arising from insufficient statistical data. We adopt a Bayesian framework that allows for the combination of scarce crop data, expert knowledge and weather information, to estimate the loss distribution. We find that expert knowledge reduces the parameter uncertainty and changes the insurance premium in the correct direction.

• Virtual testbed for development and evaluation of power system digital twins and their applications

  2024

  Sustainable Energy Grids and Networks · 20 Zitationen · DOI

  Digital twins (DTs) show considerable promise for development of applications and solutions across a diverse range of power system services. Ensuring these applications function as intended without causing disruptions or unexpected issues requires comprehensive testing prior to practical deployment. However, current approaches to power system digital twin (PSDT) application development and testing experience significant obstacles, including limitations and risks associated with accessing real-world power systems, models and data. This article introduces a virtual testbed based on the concept of a virtual physical twin (VPT), that replaces the need for access to a physical twin (PT), as a platform designed to remove the heavy reliance on online data flows and provide a close to real-world environment. A testbed enables simultaneous development and testing of DTs and their related applications in a realistic, interactive, and safe setting without impact on the operation of the actual power system. A complete workflow for PSDT testbed implementations is proposed, with all necessary steps from concept to the eventual connection to the physical system. To validate the practical implementation steps, utility, and value of the testbed, a real-time transient stability analysis with two artificial intelligence algorithms is provided. The proposed testbed is expandable and adaptable, promoting the development of advanced and intelligent PSDTs. The key benefit of the testbed is that it enables the development of DT and its application closely in a realistic environment without affecting the operation of PT.

• Development of Power System Models for Distributed Real-Time Simulations

  2022

  IEEE Access · 16 Zitationen · DOI

  This paper proposes a general methodology for the development of power system models suitable for distributed real-time simulations (D-RTS) based on topology, simulator interfaces and data exchange. D-RTS have risen as functional alternatives that can combine remote and multi-vendor resources for large-scale power system simulations via a virtual connection. However, previous work focused on combination of separate models and not the performance of D-RTS when splitting a single monolithic model, failing to study the behaviors of D-RTS, including, synchronization and accuracy. The proposed methodology is used to develop distributed models of two widely used testbed large power systems, the IEEE Australian Benchmark model and the IEEE 300-Bus system. These testbeds are selected as they can be simulated as both monolithic and distributed models in available simulators in order to validate both the methodology and resulting model performance. The obtained results and comparison between monolithic and distributed models support the proposed approach and demonstrate the performance of D-RTS under both steady-state and transient operations in multiple scenarios.

• Adaptive local parametric estimation of crop yields: implications for crop insurance rate making

  2017

  European Review of Agricultural Economics · 16 Zitationen · DOI

  The estimation model of crop yields is a prerequisite for deriving actuarially sound insurance premiums. A major challenge in estimating crop yield models arises from the non-stationarity of the data generating process due to technological change and climate change. In this paper, we introduce an adaptive local parametric approach to deal with the non-stationarity of crop yields. An empirical application to major crops in the USA indicates that yield risks for corn and cotton are decreasing, but are increasing for winter wheat. A rating analysis suggests that the proposed model shows potential to obtain more accurate rates than commonly used methodology.

• How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin

  2021

  Energies · 12 Zitationen · DOI

  In light of the global effort to limit the temperature rise, many cities have undertaken initiatives to become climate-neutral, making decentralized urban energy production more relevant. This paper addresses the potential of urban wind energy production with small wind turbines, using Berlin as an example. A complete framework from data selection to economic feasibility is constructed to enable the empirical assessment of wind energy for individual buildings and Berlin as a whole. Based on a detailed dataset of all buildings and hourly wind speed on a 1 km2 grid, the results show that multiple turbines on suitable buildings can significantly contribute to households’ energy consumption but fall short of covering the full demand. For individual households, our economic evaluation strongly recommends the self-consumption of the produced electricity. The findings suggest that while the use of small wind turbines should be continuously encouraged, exploring other renewable resources or combination of wind and photovoltaic energy in the urban environment remains important.

• Estimating Location Values of Agricultural Land

  2017

  German Journal of Agricultural Economics · 12 Zitationen · DOI

  “Bodenrichtwerte” reflect the average location value of land plots within a specific area. They constitute an important source of information that contributes to price transparency on land markets. In Germany, “Bodenrichtwerte” are provided by publicly appointed expert groups (Gutachterausschüsse). Using empirical data from Mecklenburg-Western Pomerania between 2013 and 2015, this article examines the relation between “Bodenrichtwerten” and statistically determined location values. It turns out that “Bodenrichtwerte” tend to underestimate location values of arable land by 11.5% on average. This underestimation can be traced back to the pronounced increase of land prices in the observation period. As an alternative to the expert-based determination of location values, we suggest a nonparametric smoothing procedure that rests on the Propagation-Separation Approach. The application of this data-driven procedure achieves an accuracy comparable to that of official “Bodenrichtwerte” at the one-year ahead prediction of location values without the requirement of expert knowledge.

• A New Approach to Assess Wind Energy Potential

  2015

  Energy Procedia · 10 Zitationen · DOI

  To meet the increasing global demand for renewable energy, such as wind energy, an increasing number of wind parks are being constructed worldwide. Finding a suitable location requires a detailed and often costly analysis of local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. We suggest a novel, globally feasible approach to assess the local wind energy potential: First, meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at specific turbine locations and hub heights. Second, the relation between wind data and energy production is for the first time determined via a five parameter logistic function using actual high-frequency energy production data. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of the wind power potential for Germany exemplifies our approach.

• Artificial intelligence and digital twins in power systems: Trends, synergies and opportunities

  2022

  Digital Twin · 9 Zitationen · DOI

  <ns4:p>Artificial Intelligence (AI) promises solutions to the challenges raised by the digitalization of power grids and their assets. Decision-making, forecasting and even operational optimization of grids and assets are just some of the solutions that AI algorithms can provide to operators, utilities and vendors. Nevertheless, barriers such as access to quality datasets, interpretability, repeatability, and availability of computational resources currently limit the extent of practical AI implementations. At the same time, Digital Twins (DTs) are foreseen as platforms that can overcome these barriers, and also provide a new environment for the development of enhanced and more intelligent applications. In this manuscript, we review the published literature to determine the existing capabilities and implementation challenges of AI algorithms in power systems, and classify AI-based applications based on their time scale to reveal their temporal sensitivity. By combining AI and DT, we outline multiple prospective use cases for AI-enhanced power grid and power asset DTs. Our review also identifies that the combination of AI-based solutions and DTs leverages new applications with the potential to fundamentally change multiple aspects of the power industry.</ns4:p>

• Is there a demand for multi-year crop insurance?

  2015

  Agricultural Finance Review · 8 Zitationen · DOI

  Purpose – The purpose of this paper is to examine the aggregate demand for single- and multi-year crop insurance contracts and to discuss market potential for multi-year crop insurances. Design/methodology/approach – In this paper the authors develop a dynamic discrete choice model of insurance alternatives, in which single- and multi-year insurance contracts are offered to heterogeneous risk averse farmers. The farmers determine their insurances choices based on inter-temporal utilities. Findings – The results show that in a competitive insurance market with heterogeneous risk averse farmers, there is simultaneous demand for both insurance contracts. Moreover, the introduction of multi-year contracts enhances the market penetration of insurance products. Research limitations/implications – The effect of introducing multi-year crop insurance is moderate when applying the model to US corn production. In practice, however, the increase of insurance demand could be more pronounced because we did not consider marketing and administrative costs and thus ignore this cost reduction potential of multi-year insurance. Originality/value – This study adds to the literature analyzing the feasibility of multi-year crop insurance and also shows that there is market potential for multi-year crop insurance.

• What-if Scenario Testing Through Power System Digital Twins

  2024

  7 Zitationen · DOI

  Power system digital twins (PSDTs) promise ad-vanced solutions to reshape power system applications by op-erating in parallel with their physical counterparts to generate valuable operational insights. Digital twins (DT) enable what-if scenario testing, which can evaluate the outcomes of hypothetical situations or events without disrupting the normal operation of actual power systems. The lack of a framework supporting different applications while simultaneously managing real-time and historical data hinders the execution of multiple simultaneous PSDT instances. The parallel execution of DT instances has the potential to improve the efficiency of performing and analysing the outcomes of multiple tests. This paper proposes a workflow for what-if scenario testing by using DT instances to evaluate different tests under actual operating scenarios or conditions in parallel. A case study adopts real-time simulators as a virtual physical twin (VPT) and two parallel DTs in a laboratory environ-ment, respectively. Real-time simulation-based DT instances are simultaneously executed for different tests under actual operating points as the current state of VPT. It demonstrates the use and deployment of DT-enabled what-if scenario testing to reinforce power system operation. The proposed workflow is expandable and flexible, providing a practical approach that enhances DT- based applications.

• Development of adaptive model-based digital twins for evolving power systems

  2025

  Computers & Electrical Engineering · 6 Zitationen · DOI

  Adaptation is a critical function that guarantees a digital twin (DT) remains accurate and provides reliable and trustworthy information about its behaviour. Lack of a suitable adaptation function compromises the efficiency and reliability of DT-based applications. Data-driven DTs that rely on machine learning (ML) adapt to new datasets acquired from the physical twin (PT) by employing transfer learning techniques or by undergoing complete reconstruction. However, these approaches cannot be implemented on model-based DTs that are based on known laws and principles of physics, since their accuracy is dependent on specific parameters that may be neither estimated from the measurements nor derived from existing datasets. This paper proposes a generic workflow to adapt model-based DTs to minimise their deviation and introduced errors from their corresponding PTs. The two-step method uses ML to first identify the deviating components within an interval of confidence and then estimate new parameters based on information from the PT. A relational database is adopted for flexible and efficient data access and storage. To verify the effectiveness and feasibility of the proposed method, a DT testbed is used for a power system digital twin (PSDT) based on real-time simulations. The PSDT can be successfully adapted for specific changes, including system configurations and component parameters. The proposed adaptation workflow provides an opportunity to adapt system-level model-based PSDTs across wider scenarios and/or conditions. • A generic and applicable method for adapting model-based DTs to changing conditions. • Initialisation ensures alignment between the PT and its DT. • Synchronisation maintains real-time alignment between PT and DT. • Tuning minimises errors and discrepancies in component parameters within the DT. • Demonstration of model-based PSDT adaptation validates the proposed approach.

• Sequential power flow algorithm and post-event steady-state power distribution analysis in hybrid AC/MT-MVDC systems

  2024

  International Journal of Electrical Power & Energy Systems · 3 Zitationen · DOI

  In hybrid ac/multi-terminal medium-voltage dc (AC/MT-MVDC) systems with multiple voltage source converters (VSCs) and dc/dc converters, it is essential to attain accurate initial power flow (PF) and post-event power distribution solutions efficiently. This paper proposes: (i) a novel sequential PF algorithm for hybrid AC/MT-MVDC systems by a Fibonacci search-based Newton–Raphson (FSNR) approach with uniform MVDC bus type definition, while considering power losses and varied control schemes of different converters; (ii) a zero error steady-state post-event power distribution calculation method under droop control by the introduction of dynamic I/V droop coefficients based on the FS algorithm. The FSNR approach simplifies the MVDC PF derivation by only requiring the definition of the dc current bus type, effectively eliminating the need to solve multiple sub-Jacobian matrices. Furthermore, the post-event power distribution analysis offers precise power redistribution calculation approach following disturbances by considering both open- and closed-loop operation in an MT-MVDC distribution system. The computational efficiency and validity of the proposed PF algorithm, along with the accuracy of presented post-event power distribution calculation method are verified through Python and RTDS real-time simulators in an extended MT-MVDC distribution network incorporated with the IEEE 14/33/69 bus transmission/distribution systems.

• Estimating Location Values of Agricultural Land

  2017

  AgEcon Search (University of Minnesota, USA) · 3 Zitationen · DOI

  “Bodenrichtwerte” reflect the average location value of land plots within a specific area. They constitute an important source of information that contributes to price transparency on land markets. In Germany, “Bodenrichtwerte” are provided by publicly appointed expert groups (Gutachterausschüsse). Using empirical data from Mecklenburg-Western Pomerania between 2013 and 2015, this article examines the relation between “Bodenrichtwerten” and statistically determined location values. It turns out that “Bodenrichtwerte” tend to underestimate location values of arable land by 11.5% on average. This underestimation can be traced back to the pronounced increase of land prices in the observation period. As an alternative to the expert-based determination of location values, we suggest a nonparametric smoothing procedure that rests on the Propagation-Separation Approach. The application of this data-driven procedure achieves an accuracy comparable to that of official “Bodenrichtwerte” at the one-year ahead prediction of location values without the requirement of expert knowledge.

• The Impact of Overlap Period on the Stability of Current-Controlled Alternate Arm Converter Based on dq Frame Impedance Analysis

  2022

  Electronics · 2 Zitationen · DOI

  As a variant modular converter configuration, the alternate arm converter (AAC) is well-suited for high-voltage power transmission and large-scale integration of renewables. In contrast to conventional multilevel converters, the director switches in the arms of AAC lead to the introduction of an overlap period, during which circuiting current can flow through the two arms in the same phase. Thus, fixed or variable overlap period control can be implemented in AAC systems so as to dynamically balance stored arm energy. However, the control of overlap period is linked to instability issues that might impede the safe operation of AAC systems, which are yet to be reported. In this paper, the stability of an AAC system is demonstrated based on measured grid and converter impedance, in conjunction with impedance-based stability criterion in the dq frame. The interaction between harmonic sources at AC and DC sides of the AAC system is analyzed to determine resonant frequencies in the AC current when any potential resonance is identified in the dq frame. Novel results with respect to the impact of overlap period on the system stability are obtained by depicting and comparing the Eigenloci in the polar plot, which are validated by real-time simulations.

• Validation of Distributed Real-Time Simulations for Decoupled Power System Models

  2022

  2022 IEEE 20th International Conference on Industrial Informatics (INDIN) · 2 Zitationen · DOI

  Distributed real-time simulation (D-RTS) has been proposed as an alternative solution for the simulation of large-scale power systems. D-RTS interconnects heterogeneous and remote real-time resources virtually in order to combine and extend their simulation capabilities. A reliable D-RTS framework is necessary to virtually interconnect subsystems and manage simulation data in real time. D-RTS has mainly been implemented to combine standalone models, which only shows the feasibility and increased computing capability. However, the behavior of D-RTS has not been appropriately assessed nor investigated for decoupling models. On this basis, this paper investigates power system model decoupling and verifies its implementation for the purposes of D-RTS. The IEEE Australian Benchmark model is used as a case study. The implementation, operation, and performance of the distributed model are benchmarked against its monolithic counterpart. Results validate the simulation of the distributed model under both steady-state and transient operation, demonstrating that power system models can be decoupled in order to perform real-time simulations in a distributed manner under certain conditions.

• A numerical study on a Cartesian-based body-fitted adaptive grid method

  2018

  International journal of computational fluid dynamics · 2 Zitationen · DOI

  A hybrid Cartesian-based body-fitted adaptive grid method for compressible Navier–Stokes equations is implemented and investigated. In this method, the body-fitted structured grids are generated around the geometries, and the left regions are filled with Cartesian grids. To transfer the data between the different grids, the donor cell searching technique is adopted. An unstructured data-based finite volume update procedure is used, and least squares method is suggested to retain the second order in the overlap region. The moving shock waves with different speeds and vortex passing through the interfaces of the hybrid Cartesian grid are used to explore the accuracy and conservation. A new technique is presented to deal with the non-physical stagnation of slowly moving shock wave around the interface of grid. Numerical examples are presented to demonstrate the results. The three-dimensional extension has also been shown by a benchmark problem.

• Design of RFID-based sliding sleeve control system

  2017

  Zhongguo shiyou kantan · 2 Zitationen · DOI

• Research on Business Model Based on the Classical Grounded Theory

  2011

  Beijing Youdian Xueyuan xuebao · 2 Zitationen

  The rapid development of information technology and environment had a profound impact on the study of business model and its innovations.However,a lot of research results of business model still didn't reach a consensus on this fundamental concept.Aiming at this complex concept,this paper uses the classical grounded theory to systematically analyze a great number of business model materials,and discusses the relationship among different factors of business model,especially between business model and strategy and the reform and innovation types of business model,etc.Finally this paper achieves the definition of the business model with the value proposition as the core logic and constructs business model theory system,which will provide a theoretical basis for the further theoretical research and business practice.

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Name

Dr. Zhiwei Shen

Titel

Dr.

Fakultät

Lebenswissenschaftliche Fakultät

Institut

Albrecht Daniel Thaer-Institut für Agrar- und Gartenbauwissenschaften

Arbeitsgruppe

Quantitative Agrarökonomik insbesondere angewandte Ökonometrie (J)

Telefon

+49 30 2093-46834

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26.4.2026, 01:12:31