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Y.G. Melese
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Systems engineering is the dominant approach for designing flexibility in infrastructure systems. However, the approach merely focuses on physical elements of the system as 'objects of design', whereas hardly any attention is given to the institutional structures (e.g. contracts) required to realize the system. In this paper, the conceptual gaps of systems engineering approach when it comes to infrastructure systems design is discussed. As a way to address these conceptual gaps a theoretical framework that integrates the technical/engineering perspective and the actor/institutional perspective is proposed. The framework promotes design procedures for integrating flexibility, not only in the technical elements of the system but also in the institutional structures.
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Systems engineering is the dominant approach for designing flexibility in infrastructure systems. However, the approach merely focuses on physical elements of the system as 'objects of design', whereas hardly any attention is given to the institutional structures (e.g. contracts) required to realize the system. In this paper, the conceptual gaps of systems engineering approach when it comes to infrastructure systems design is discussed. As a way to address these conceptual gaps a theoretical framework that integrates the technical/engineering perspective and the actor/institutional perspective is proposed. The framework promotes design procedures for integrating flexibility, not only in the technical elements of the system but also in the institutional structures.
This paper presents a systematic design analysis method based on the flexible design approach and the concept of real options to support decision-makers during conceptual design of infrastructure public–private partnership projects under uncertainty. It employs probabilistic and simulation methods to model uncertainty and flexible design concept to generate flexible design strategies within the physical layout and the contractual structure. Monte Carlo simulation is used to compare the value effects of design strategies. Illustrated on a stylized public–private partnership to develop a carbon capture and storage infrastructure, it was found that partners could
find design solutions that not only reduce risk exposure but also enable value-creation. For example, by designing the physical network with flexibility options such as extra capacity and length coupled with flexible revenue guarantee contract, partners can be able to reduce risk and enhance their respective value in the face of capacity demand uncertainty. Such a design strategy can be a promising way to realize multi-user carbon capture and storage investments. ...
find design solutions that not only reduce risk exposure but also enable value-creation. For example, by designing the physical network with flexibility options such as extra capacity and length coupled with flexible revenue guarantee contract, partners can be able to reduce risk and enhance their respective value in the face of capacity demand uncertainty. Such a design strategy can be a promising way to realize multi-user carbon capture and storage investments. ...
This paper presents a systematic design analysis method based on the flexible design approach and the concept of real options to support decision-makers during conceptual design of infrastructure public–private partnership projects under uncertainty. It employs probabilistic and simulation methods to model uncertainty and flexible design concept to generate flexible design strategies within the physical layout and the contractual structure. Monte Carlo simulation is used to compare the value effects of design strategies. Illustrated on a stylized public–private partnership to develop a carbon capture and storage infrastructure, it was found that partners could
find design solutions that not only reduce risk exposure but also enable value-creation. For example, by designing the physical network with flexibility options such as extra capacity and length coupled with flexible revenue guarantee contract, partners can be able to reduce risk and enhance their respective value in the face of capacity demand uncertainty. Such a design strategy can be a promising way to realize multi-user carbon capture and storage investments.
find design solutions that not only reduce risk exposure but also enable value-creation. For example, by designing the physical network with flexibility options such as extra capacity and length coupled with flexible revenue guarantee contract, partners can be able to reduce risk and enhance their respective value in the face of capacity demand uncertainty. Such a design strategy can be a promising way to realize multi-user carbon capture and storage investments.
This thesis focuses on the design of nascent energy and industrial infrastructure networks: networks that still needed to be built and for which neither scope, size, nor participants were certain. It develops systematic design analysis approaches to help improve design under uncertainty by means of flexibility. There are four parts to the thesis. The first part focuses on understanding the concept of flexible design and its application to the design of engineering systems and energy infrastructure networks. The second part focuses on flexibility analysis with the objective of improving their lifetime performance in the face of uncertain design requirements. A systematic engineering design approach combining graph theory network modelling, exploratory modelling and real options is proposed to explore candidate designs, identify valuable flexibility enablers and appreciate the value of flexible design strategies. The third part considers the role of risk sharing when actors co-invest in infrastructure networks under uncertain environment. Contractual arrangements are modelled between actors as a cooperative game and analyses the effects of uncertainty. The fourth part focuses on how private and public actors may enhance desired performances when developing new energy and industrial infrastructure networks under uncertainty.
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This thesis focuses on the design of nascent energy and industrial infrastructure networks: networks that still needed to be built and for which neither scope, size, nor participants were certain. It develops systematic design analysis approaches to help improve design under uncertainty by means of flexibility. There are four parts to the thesis. The first part focuses on understanding the concept of flexible design and its application to the design of engineering systems and energy infrastructure networks. The second part focuses on flexibility analysis with the objective of improving their lifetime performance in the face of uncertain design requirements. A systematic engineering design approach combining graph theory network modelling, exploratory modelling and real options is proposed to explore candidate designs, identify valuable flexibility enablers and appreciate the value of flexible design strategies. The third part considers the role of risk sharing when actors co-invest in infrastructure networks under uncertain environment. Contractual arrangements are modelled between actors as a cooperative game and analyses the effects of uncertainty. The fourth part focuses on how private and public actors may enhance desired performances when developing new energy and industrial infrastructure networks under uncertainty.
Energy and industrial networks such as pipeline-based carbon capture and storage infrastructures and (bio)gas infrastructures are designed and developed in the presence of major uncertainties. Conventional design methods are based on deterministic forecasts of most likely scenarios and produce networks that are optimal under those scenarios. However, future design requirements and operational environments are uncertain and networks designed based on deterministic forecasts provide sub-optimal performance. This study introduces a method based on the flexible design approach and the concept of real options to deal with uncertainties during conceptual design of networks. The proposed method uses a graph theoretical network model and Monte Carlo simulations to explore candidate designs, and identify and integrate flexibility enablers to pro-actively deal with uncertainties. Applying the method on a hypothetical network, it is found that integrating flexibility enablers (real options) such as redundant capacity and length can help to enhance the long term performance of networks. When compared to deterministic rigid designs, the flexible design enables cost effective expansions as uncertainty unfolds in the future.
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Energy and industrial networks such as pipeline-based carbon capture and storage infrastructures and (bio)gas infrastructures are designed and developed in the presence of major uncertainties. Conventional design methods are based on deterministic forecasts of most likely scenarios and produce networks that are optimal under those scenarios. However, future design requirements and operational environments are uncertain and networks designed based on deterministic forecasts provide sub-optimal performance. This study introduces a method based on the flexible design approach and the concept of real options to deal with uncertainties during conceptual design of networks. The proposed method uses a graph theoretical network model and Monte Carlo simulations to explore candidate designs, and identify and integrate flexibility enablers to pro-actively deal with uncertainties. Applying the method on a hypothetical network, it is found that integrating flexibility enablers (real options) such as redundant capacity and length can help to enhance the long term performance of networks. When compared to deterministic rigid designs, the flexible design enables cost effective expansions as uncertainty unfolds in the future.
The allocation of risk among the cooperating parties in a shared project is an important decision. This is especially true in the case of large infrastructure investments. Existing risk allocation methods are either simplistic or do not consider the effect of the agents' pre-existing businesses. In this paper, we model and analyse the effect of risk sharing when two agents want to co-develop an energy infrastructure project in an uncertain environment. The cooperating agents have a pre-existing risky business, and the new common project has a deterministic initial cost but random revenue potential. Our analysis shows that the optimal risk-sharing rule depends not only on the agents' risk aversions but also on the volatility of the common project profit, the volatilities of the agents' pre-existing businesses and the correlation of each agent's pre-existing business with the common project. An illustrative example based on energy infrastructure is used to show the implications of the sharing rule for partners.
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The allocation of risk among the cooperating parties in a shared project is an important decision. This is especially true in the case of large infrastructure investments. Existing risk allocation methods are either simplistic or do not consider the effect of the agents' pre-existing businesses. In this paper, we model and analyse the effect of risk sharing when two agents want to co-develop an energy infrastructure project in an uncertain environment. The cooperating agents have a pre-existing risky business, and the new common project has a deterministic initial cost but random revenue potential. Our analysis shows that the optimal risk-sharing rule depends not only on the agents' risk aversions but also on the volatility of the common project profit, the volatilities of the agents' pre-existing businesses and the correlation of each agent's pre-existing business with the common project. An illustrative example based on energy infrastructure is used to show the implications of the sharing rule for partners.