Combining System Dynamics Research Articles

Factors Influencing Consumer Willingness to Pay for Low‐Carbon Products: A Simulation Study in China

AbstractConsumer choice behavior is crucial to supporting cleaner production and plays an essential role in low‐carbon development and environmental policy‐making. Therefore, combining system dynamics with an agent‐based model (SD–AB), the present study explores influencing factors on both providers' and consumers' sides. Using empirical data from selected firms and a questionnaire survey of residents in China, the simulation results revealed that consumers' low‐carbon awareness and income have little effect on their willingness to pay for low‐carbon products. In contrast, some factors have an obvious effect on consumers' willingness to pay for low‐carbon products, including the delivery speed of low‐carbon products, consumers' patience and degree of satisfaction. Thus, companies that provide low‐carbon products should be more focused on customer expectations and should ensure timely and efficient delivery to consumers. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

Research of the combined extremum-seeking control system dynamics on mathematical and computer models

The article introduces the process of studying the dynamics of the combined extremum-seeking control system, which is used for grinding-mixing unit automatic balancing. The structure of the proposed system is shown and the algorithm of its operation is described. On the basis of the harmonic balance and Goldfarb’s methods, the values of quality factors of the extremum-seeking control system on the first cycle were obtained in the absence of static map drift and the stability of the system was established. The co-simulation model of the combined extremum-seeking control system implemented in the MATLAB / Simulink software is presented and described. MSC.Adams model of the grinding-mixing unit, which is a plant in the co-simulation model of the system, is presented. The results of co-simulation of the extremum-seeking control system dynamics are presented and analysed.

Integrating biophysical and socio-economic factors for land-use and land-cover change projection in agricultural economic regions

Land-use and land-cover change (LUCC) are shaped by society–nature interactions and processes. Therefore, a full study of LUCC dynamics needs explicitly to take account of both socio-economic and biophysical factors. Although some studies have addressed both these drivers, most are built as a package/black-box and consider individual types of land-use rather than land systems as a whole. Our research aims to develop a comprehensive and flexible framework that links socio-economic and biophysical driving factors to project LUCC. The framework combines System Dynamics and Geographic Information System (GIS) models, with System Dynamics used to examine the relationship between socio-economic driving factors of LUCC processes and land demand estimates. The GIS model is used to allocate land demand to the most suitable grid cells, according to the different biophysical characteristics of the cells. The study is based on the application of the framework in Dak Lak province, Vietnam, where economic development has resulted in rapid LUCC. The Kappa value of our study, compared with actual land-use in the province (2010), is 0.87. It proves that our model is reliable and can help land-use planners and policy makers develop sustainable land-use planning and management strategies. Working on the assumption that the trends indicated in Dak Lak’s 2020 land-use plan continue, we produced projected land-use/land-cover maps for 2020 and 2030.

A hybrid electric vehicle market penetration model to identify the best policy mix: A consumer ownership cycle approach

HEV market penetration exists in a circular loop of purchase, use, retirement, and repurchase, i.e., the consumer ownership cycle. Existing HEV market penetration models focus on a single linear process, such as purchasing, without considering other processes. Market penetration policies based on such models can facilitate a single process, but they cannot boost market penetration as planned. Combining system dynamics with consumer choice models, we propose a new HEV market penetration model to describe the dynamic circular market penetration process as well as its interaction with macroeconomic conditions and government policies. In this way, our model finds bottlenecks, estimates the future effects of different policies to solve bottlenecks, and identifies more effective combinations of policies to boost HEV market penetration. Our empirical analysis of Korean HEV market penetration reveals that combining a tax incentive and retirement subsidy will be more effective than offering either of those alone. Also, HEV market penetration becomes slower when the tax incentive is smaller than the retirement subsidy (or vice versa) because consumers escape the market penetration loop.

Modeling and dynamic assessment on sustainable development of drainage enterprise: Application of a coupled system dynamics- comprehensive assessment model

The operating efficiency, operating performance and service quality of a drainage enterprise are determined by its sustainable development level. Sustainable development is a dynamic process affected by many factors and their complicated interaction. Compared with regular assessment methods, which are usually static and discontinuous, this research applies the system dynamics (SD) method to study the dynamic process that controls the sustainable development of a drainage enterprise. This assessment can be achieved through building a dynamic feedback mechanism among operable factors, simulating the dynamic evolution process of each effect factor within a continuous time and combining a comprehensive assessment model. A case study is presented that can help drainage enterprise stakeholders to strategically understand the possible effects of policy implementation. In addition, three different sustainable development scenarios are presented, which were designed and simulated through the setting the key variables. These three variables are investment in environmental protection, wastewater treatment fees (yuan/m3) and the growth rate of wastewater treatment capacity. The assessment results show that long-term sustainable development of a drainage enterprise is best served by improving the growth rate of wastewater treatment capacity compared to the other variables. The SD method has proven to be reliable for the dynamic assessment of drainage enterprise. This work provides a model that combines system dynamics with comprehensive assessment for drainage enterprise sustainability evaluation and identification of the most significant factors. The results can offer critical information to stakeholders and provide a method to implement the best practices for the management of drainage enterprises.

The Effect of FRT Behavior of VSC-HVDC-Connected Offshore Wind Power Plants on AC/DC System Dynamics

Future power systems will contain more converter-based generation, among which are the voltage-source converter–high-voltage direct-current (VSC-HVDC)-connected offshore wind power plants (WPP). Their interaction with the onshore system influences power system dynamics in the transient stability timeframe. The respective protection and control methods which cause this interaction must be taken into account in grid-integration studies performed today. This paper gives insight into the effect of typically required fault ridethrough (FRT) and post-FRT measures of VSC-HVDC-connected offshore WPPs on the combined ac and HVDC system dynamics. Several important sensitivities are addressed, among which are: 1) FRT implementation, 2) the postfault active power-recovery rates, 3) the ac network dynamic characteristics, and 4) the HVDC topology. The analysis is first performed as a proof of concept on a small benchmark system, and subsequently generalized to a realistic dynamic model of the future Northwestern European power system. The results of this paper can be used as a reference for understanding the effects of large-scale VSC-HVDC-connected offshore WPPs on the stability of the onshore interconnected power systems.

Integrated decision-making about housing, energy and wellbeing: a qualitative system dynamics model.

BackgroundThe UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative “unintended consequences” across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system.This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process.MethodsWe used participatory system dynamics modelling to develop a qualitative causal theory linking housing, energy and wellbeing. Qualitative interviews were followed by two interactive workshops to develop the model, involving representatives from national and local government, housing industries, non-government organisations, communities and academia.ResultsMore than 50 stakeholders from 37 organisations participated. The process resulted in a shared understanding of wellbeing as it relates to housing; an agreed set of criteria against which to assess to future policy options; and a comprehensive set of causal loop diagrams describing the housing, energy and wellbeing system. The causal loop diagrams cover seven interconnected themes: community connection and quality of neighbourhoods; energy efficiency and climate change; fuel poverty and indoor temperature; household crowding; housing affordability; land ownership, value and development patterns; and ventilation and indoor air pollution.ConclusionsThe collaborative learning process and the model have been useful for shifting the thinking of a wide range of housing stakeholders towards a more integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing.Electronic supplementary materialThe online version of this article (doi:10.1186/s12940-016-0098-z) contains supplementary material, which is available to authorized users.

Combining system dynamics and multi-objective optimization with design space reduction

– The purpose of this paper is to introduce an effective methodology of obtaining Perot-optimal solutions when combining system dynamics (SD) and multi-objective optimization (MOO) for supply chain problems. , – This paper proposes a new approach that combines SD and MOO within a simulation-based optimization framework for generating the efficient frontier for supporting decision making in supply chain management (SCM). It also addresses the issue of the curse of dimensionality, commonly found in practical optimization problems, through design space reduction. , – The integrated MOO and SD approach has been shown to be very useful for revealing how the decision variables in the Beer Game (BG) affect the optimality of the three common SCM objectives, namely, the minimization of inventory, backlog, and the bullwhip effect (BWE). The results from the in-depth BG study clearly show that these three optimization objectives are in conflict with each other, in the sense that a supply chain manager cannot minimize the BWE without increasing the total inventory and total backlog levels. , – Having a methodology that enables effective generation of optimal trade-off solutions, in terms of computational cost, time as well as solution diversity and intensification, assist decision makers in not only making decision in time but also present a diverse and intense solution set to choose from. , – This paper presents a novel supply chain MOO methodology to assist in finding Pareto-optimal solutions in a more effective manner. In order to do so the methodology tackles the so-called curse of dimensionality by reducing the design space and focussing the search of the optimization to regions of inters. Together with design space reduction, it is believed that the integrated SD and MOO approach can provide an innovative and efficient approach for the design and analysis of manufacturing supply chain systems in general.

The combination of system dynamics and game theory in analyzing oligopoly markets

In this paper, we present a hybrid method of game theory and dynamic systems to study the behavior of firms in an oligopoly market. The aim of this study is to build a model for an oligopoly game on the basis of feedback loops and system dynamics approach and to solve the resulted problems under some special conditions where traditional game theory methods are unable to handle. The method includes a combination of qualitative methods including interviews with industry experts to prepare the model and quantitative methods of system dynamics, simulation methodologies and game theory. The results indicate that competitive behavior and the important parameters such as volume of demand, interest rates and price fluctuation will be stabilized after a transition period.

Supporting business model decisions: a scenario-based simulation approach

A key challenge for entrepreneurs is to find a robust and scalable business model. In complex environments, business model decisions often build on highly uncertain assumptions. The uncertainty increases when the entrepreneurial venture is confronted with unexpected changes in the environment. This paper proposes an approach to support entrepreneurs in understanding the future implications of their business model decisions. The approach combines system dynamics simulation modelling with formal scenario building. The paper presents a novel conceptual approach to modelling business models. It develops a business model simulation for a multi-sided platform such as the online marketplace eBay. The paper builds future scenarios to conduct simulation experiments that incorporate the uncertainty of developments external to the firm. Based on historic data of eBay, it demonstrates how the scenario-based simulation approach allows comparing the implications of different revenue model options on eBay's performance. Finally, the research discusses the general applicability of the scenario-based simulation approach as a tool for entrepreneurial decision making.

Combining system dynamics and agent-based modeling to analyze social-ecological interactions—an example from modeling restoration of a shallow lake

Modeling social-ecological interactions between humans and ecosystems to analyze their implications for sustainable management of social-ecological systems (SES) has multiple challenges. When integrating social and ecological dynamics, which are often studied separately, one has to deal with different modeling paradigms, levels of analysis, temporal and spatial scales and data availabilities in the social and ecological domains. A major challenge, for instance, is linking the emergent patterns from individual micro-level human decisions to system level processes such as reinforcing feedbacks determining the state of the ecosystem. We propose building a hybrid model that combines a system dynamics with an agent-based approach to address some of these challenges. In particular, we present a procedure for model development and analysis that successively builds up complexity and understanding of model dynamics, particular with respect to feedbacks between the social and ecological system components. The proposed steps allow for a systematic increase of the coupling between the submodels and building confidence in the model before deploying it to study the coupled dynamics. The procedure consists of steps for i) specifying the characteristics of the link between the social and ecological systems, ii) validating the decoupled submodels, iii) doing sensitivity analysis of the decoupled submodels with respect to the drivers from the respective other subsystem and, finally iii) analyzing the coupled model. We illustrate the procedure and discuss opportunities and limitations of hybrid models against the background of an archetypical SES case study, namely the restoration of a turbid lake. Our approach exemplifies how a hybrid model is used to unpack SES complexity and analyze interactions between ecological dynamics and micro-level human actions. We discuss the benefits and challenges of combining a system dynamics models as an aggregated view with an agent-based model as a disaggregated view to improve social-ecological system understanding.

A dynamic feasibility analysis of public investment projects: An integrated approach using system dynamics and agent-based modeling

Increasingly, public sector investment projects face a dynamic environment that incorporates both macroscopic system and microscopic individuals. Prior attempts to analyze the feasibility of those projects, however, have been subject to limitations in accommodating such environmental changes. As a remedial measure, the combination of system dynamics (SD) and agent-based modeling (ABM) is proposed due to their complementary strengths. Consequently, this paper suggests a new approach to dynamic feasibility analysis for public investment projects through an integrated simulation model using SD and ABM. The former SD part elucidates the relationships among system elements that constitute project's benefits and costs, while the latter ABM part depicts users’ emergent behavior with their heterogeneity. A bridge construction case study demonstrates the applicability of the proposed approach. The findings show that the proposed approach can provide a valuable and flexible framework for analyzing project feasibility in a dynamic environment.

Analysis on Inundation Impacts of Sea Level Rise Using System Dynamics-GIS Model

In order to analyze the impacts of climate change, a time and space integrated model was developed in this study using system dynamics and GIS. The model built was used to carry out a simulation on the inundation impact on A-gu of Busan Metropolitan city resulting from the sea level rise scenario of IPCC and storm surge, which is the worst case. Through this, the flooded area and population until 2100 were predicted. Also, the result and significance of each alternative was reviewed improving the model by establishing alternative scenarios of protection, accommodation and retreat as plans of reaction to sea level rise. The combination of system dynamics and GIS has advantages of how the diverse variables change until the target year can be traced and, accordingly, not only the results but also the processes of spatial change can be examined by calculating the value of change process at each time step. The synergy of this model presumed to be a foothold for solving problems which are becoming difficult to predict due to increase in uncertainty and complexity such as the support for decision making for urban resilience to natural disasters.

Combining system dynamics modelling and management control systems to support strategic learning processes in SMEs: a Dynamic Performance Management approach

Traditional management control systems, mainly centred on accounting-based measures, are widely recognized as useful tools to support Small and Medium Enterprises (SMEs) managers and entrepreneurs in steering business development. However, due to the increasing turbulence and dynamic complexity that characterize today’s competitive arenas, such systems need to be combined with simulation-based methodologies in order to improve entrepreneurial learning processes and, as a result, better detect possible crisis symptoms and weak signals of change—emerging from the business environment—to promptly react. Therefore, the aim of this paper is to show how a combination of traditional management control mechanisms with system dynamics modelling can effectively lead to better results in terms of SMEs’ performance measurement and management. As a result, a Dynamic Performance Management approach will be illustrated and discussed, also through an empirical application to a real small business.

Model-Based Analysis of Urban Energy Systems (on the Basis of a City's Energy Master Plan)

AbstractAs half of the world's population live in cities today, the topic of urbanization and urban energy systems shift continuously into society's focus. It has become a common challenge for local governments to provide a so called Plan, outlining a long term vision for the city's energy infrastructure, to which all planners and investors have to adhere. Being a top-down approach, these Master plans are first of all politically motivated documents, which focus on achieving given targets, such as CO2-emission reductions or higher shares of electric mobility. Originating from these targets, a set of milestones and measures is derived, e.g., the implementation of certain green technologies or refurbishments of buildings. The goal of this paper is to elaborate a model, which allows to analyze a Master Plan from a bottom-up perspective and thereby to be able to quantitatively assess the plan with regards to its feasibility, while identifying possible bottlenecks in their implementation. The results can then serve the city planners to adapt their planning in order to avoid unforeseen problems, when putting the plan's measures into practice. The approach pursued in this research is a combination of system dynamics and an agent-based simulation model of the city's energy system, having both a high spatial and temporal granularity. The model is developed with the multi-method modelling tool Anylogic and Geographic Information System (GIS). The city itself is implemented with its existing building and power infrastructure, which is then subject to the planned measures and developments. The core of the model implements on the one hand different energy generation technologies, both fossil fuels and renewables, reaching from big power plants to small local PV-installations on a private household's roof. On the other hand, the heat and electricity consumers are represented through the buildings. The aim of the model is, at first, to provide a support system to analyze the short and long term effects of the Master Plan. Since its measures are usually not planned in detail concerning exact location or timing of the realization, the simulation results can provide references on these specific details. Secondly, the findings are used to identify the impact of single planned measures and their combinations which answers the questions of how, when and where local electricity and heat producers and the energy efficiency measures influence one another and if they have synergetic or competitive effects. Finally, a set of recommendations is derived from the analyses, which can help the city planners to transfer the strategic measures of the Master Plan into operative business.IntroductionThe topic of urbanization and therewith also urban energy systems shift continuously into society's focus because half of the world's population lives in cities today1. Three quarters of the world energy consumption takes place in cities, being the case for 80% of greenhouse gas emissions. Estimations predict the share of population living in cities to rise to 70% in average and up to 85% in industrialized countries until 205O2. These numbers show clearly the growing importance of an urban energy system which is not only effective and efficient but at the same time also adaptable to new technologies.An urban energy system can be described as the combined process of supply and demand of energy services to cover the given needs of a city's population. This process includes the production, transport and storage of resources as well as the actual conversion into the final end use energy, usually heat and electricity. The cities are not only passive energy consumers with all the power plants outside the urban borders but can increasingly be regarded as an opportunity for many energy transformation units supplying energy locally right where it is needed. This distributed energy generations is becoming an important topic for sustainable use of energy. …

Dynamics of Photovoltaic-Generator-Interfacing Voltage-Controlled Buck Power Stage

This paper investigates the dynamic properties of the photovoltaic-generator-interfacing voltage-controlled buck power stage operating in both the maximum and limited power point tracking modes. The photovoltaic generator (PVG) is known to possess both current- and voltage-source properties with respect to its maximum power point. While voltage-fed operation is conventional, current-fed action is nontrivial and is thoroughly analyzed in this paper. The photovoltaic-generator-interfacing converter is formed by adding a capacitor at conventional voltage-fed converter input terminals, turning it into a current-fed power stage. During the maximum power point tracking phase, converter input voltage is regulated, possessing nontrivial dynamics. The situation is burdened further when output-voltage control should be alternatively realized to limit the voltage of the converter terminating the energy storage element. It is shown that both the photovoltaic generator and the terminating energy storage greatly affect the combined system dynamics. Parallel as well as cascaded control arrangements are proposed to support dual-mode system operation. Extended experimental results are shown to enforce presented theory and reveal nontrivial dynamics-related issues.

Optimal subsidy estimation method using system dynamics and the real option model: Photovoltaic technology case

In this paper, we propose a method of optimizing financial subsidies and public research and development investments for renewable energy technologies, rather than optimizing financial subsidy alone. By combining system dynamics with real option models, we capture dynamic complex interactions among investors, consumers, and policymakers, as well as future uncertainties of key energy, economic, and environmental factors. Our method thereby makes subsidy optimization more accurate and flexible. To evaluate our model, we apply it to the Korean photovoltaic subsidy and determine that the government can achieve the photovoltaic diffusion target, even if it reduces the total subsidy by $US 359.5million. The optimal approach is to increase research and development funding by $US 310.4million while reducing the financial subsidy by $US 669.9million. Our method helps policymakers optimize their subsidy allocation and therefore reduces subsidy inefficiencies.

A hybrid SD–DES simulation approach to model construction projects

Purpose– The purpose of this research is to propose a hybrid simulation framework which can take into account both the continuous and operational variables affecting the performance of construction projects.Design/methodology/approach– System dynamics (SD) simulation paradigm is implemented for the modelling of the complex inter-related structure of continuous variables and discrete event simulation (DES) is implemented for the modelling of operational influencing factors. A hybrid modelling framework is then proposed through combination of SD and DES to simulate the construction projects.Findings– This paper discusses the deficiencies of two traditional simulation methods – SD and DES – for simulation of construction projects which can be compensated by implementing hybrid SD–DES model. Different types of basic hybrid structures and synchronisation methods of SD and DES models are introduced.Practical implications– The proposed hybrid framework discussed in this research will be beneficial to modellers to simulate construction projects.Originality/value– The paper introduces a theoretical framework for a hybrid continuous- discrete simulation approach which can take into account the dynamics of project environment arising from the complex inter-related structure of various continuous influencing factors as well as the construction operations. Different steps required to develop the hybrid SD–DES model and synchronisation of SD and DES simulation methods are illustrated.

Complex Mode Analysis and Simulation Research of Automotive Driveline Based on Bending-torsional-axial Coupled Vibration Hybrid Model

The characteristics of torsional-bending-axial coupled vibration hybrid model for automotive driveline are introduced based on the combination of system dynamics and structural dynamics and the modelling methods of hybrid model for automotive driveline are also discussed from three aspects which are structural dynamic modelling of shaft, system dynamic modelling of helical gear pair, bearing and attaching mass(inertia), connections among components by coordinate transformation. Complex mode analysis of driveline is analyzed and it is found that the main vibration mode of first four order modal calculated by hybrid model are torsional vibration and they are similar to the first four order modal calculated by system dynamic branched torsional vibration model, the main vibration modes are two or three forms of coupled vibration after the fifth order modal. It is discovered that the shudder degree of hybrid model is slightly enhanced and the characteristic frequency is almost the same between hybrid model and branched torsional model from the simulation research of launch shudder. It is also concluded that bending and axial vibrations have little effect on launch shudder phenomenon.

Delayed resonator with acceleration feedback – Complete stability analysis by spectral methods and vibration absorber design

This paper deals with the problem of active vibration suppression using the concept of delayed resonator (DR) absorber with acceleration feedback. A complete dynamic analysis of DR and its coupling with a single degree of freedom mechanical system are performed. Due to the presence of a delay in the acceleration feedback, the dynamics of the resonator itself, as well as the dynamics of combined system are of ‘neutral’ character. On this system, spectral methods are applied to perform a complete stability analysis. Particularly, the method of cluster treatment of characteristic roots is used to determine stability boundaries in the space of the resonator parameters. Based on this analysis, a methodology to select the resonator parameters is proposed in order to guarantee desirable suppression characteristics and to provide safe stability margins. An example case study is included to demonstrate these analytical results.