RS
R.M. Stikkelman
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1
Self-organized industrial symbiosis (IS) starts with one actor's decision to invest in a waste recovery plant and the other actors' decision to buy the recovered flow. Technical and institutional conditions of the cluster influence actors' decisions. This paper explores the emergence of IS collaborations in industrial clusters under different techno-economic conditions in the long term. We propose a mixed-integer linear programming model that incorporates costs and constraints associated with waste recovery and exchange to study actors' investment decisions and investigate shaped symbiotic exchanges under rising energy prices and limited electricity supply. The approach is implemented in Iran's Persian Gulf Mining and Metals Special Economic Zone as a case study. The results revealed that changes in internal or external condition simultaneously influence the industrial and waste recovery plants. For instance, increasing energy prices without raising product prices significantly decreased the production level of industrial plants and, consequently, heat recovery potential. Furthermore, the waste heat recovery plants' contribution to improving the cluster's economic and environmental performance was not the same. Electricity recovery from a power plant's waste heat can result in 55 PJ grid electricity intake reduction and 720 M€ cluster cash flow increase. Recovered cooling or electricity from the steelmaking plant waste heat was consumed internally rather than shaping IS. These model outcomes show its capability to study IS within the socio-technical structure of the cluster, not a standalone phenomenon. Implemented conceptualization offers a novel system-level approach, which could be adjusted to assess other industrial development strategies.
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Self-organized industrial symbiosis (IS) starts with one actor's decision to invest in a waste recovery plant and the other actors' decision to buy the recovered flow. Technical and institutional conditions of the cluster influence actors' decisions. This paper explores the emergence of IS collaborations in industrial clusters under different techno-economic conditions in the long term. We propose a mixed-integer linear programming model that incorporates costs and constraints associated with waste recovery and exchange to study actors' investment decisions and investigate shaped symbiotic exchanges under rising energy prices and limited electricity supply. The approach is implemented in Iran's Persian Gulf Mining and Metals Special Economic Zone as a case study. The results revealed that changes in internal or external condition simultaneously influence the industrial and waste recovery plants. For instance, increasing energy prices without raising product prices significantly decreased the production level of industrial plants and, consequently, heat recovery potential. Furthermore, the waste heat recovery plants' contribution to improving the cluster's economic and environmental performance was not the same. Electricity recovery from a power plant's waste heat can result in 55 PJ grid electricity intake reduction and 720 M€ cluster cash flow increase. Recovered cooling or electricity from the steelmaking plant waste heat was consumed internally rather than shaping IS. These model outcomes show its capability to study IS within the socio-technical structure of the cluster, not a standalone phenomenon. Implemented conceptualization offers a novel system-level approach, which could be adjusted to assess other industrial development strategies.
The Netherlands is known for its high penetration of natural gas use in households and industry, but the threat of climate change and earthquakes in the province of Groningen, caused by natural gas production, stimulate the search for alternatives, such as hydrogen gas. Various ways of producing and supplying hydrogen have the attention of scientists, companies and policy makers. This study compares the following three ways of green hydrogen production: 1) a photovoltaic system in Africa is used to produce hydrogen from sea water, followed by pipeline transport to Rotterdam, Netherlands, 2) electricity generated by the offshore Borssele 1&2 wind farm in the Netherlands is used for the offshore production of hydrogen from sea water followed by pipeline transport to Rotterdam, or 3) the electricity generated by this offshore wind farm is transmitted to Rotterdam where it is used for onshore production of hydrogen from sea water. The sustainability of the three systems is assessed from a life cycle point of view. The environmental LCA resulted in ReCiPe 2016 endpoint indicators and the midpoint indicators GWP, land use and water consumption. The exergetic sustainability assessment applied the Total Cumulative Exergy Loss (TCExL) method. The preferred system according to the results of the environmental LCA and the exergetic sustainability assessment is the wind energy system including offshore hydrogen production. The results are not unanimous as to which system is the second-best. The three systems need to be investigated in more detail before firm conclusions can be drawn. It is recommended that attention also be paid to the economic and social pillars of sustainability, and to the exergetic sustainability of technological systems in general, as exergetic assessment results are independent of changing and subjective models, weighting factors and other variables.
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The Netherlands is known for its high penetration of natural gas use in households and industry, but the threat of climate change and earthquakes in the province of Groningen, caused by natural gas production, stimulate the search for alternatives, such as hydrogen gas. Various ways of producing and supplying hydrogen have the attention of scientists, companies and policy makers. This study compares the following three ways of green hydrogen production: 1) a photovoltaic system in Africa is used to produce hydrogen from sea water, followed by pipeline transport to Rotterdam, Netherlands, 2) electricity generated by the offshore Borssele 1&2 wind farm in the Netherlands is used for the offshore production of hydrogen from sea water followed by pipeline transport to Rotterdam, or 3) the electricity generated by this offshore wind farm is transmitted to Rotterdam where it is used for onshore production of hydrogen from sea water. The sustainability of the three systems is assessed from a life cycle point of view. The environmental LCA resulted in ReCiPe 2016 endpoint indicators and the midpoint indicators GWP, land use and water consumption. The exergetic sustainability assessment applied the Total Cumulative Exergy Loss (TCExL) method. The preferred system according to the results of the environmental LCA and the exergetic sustainability assessment is the wind energy system including offshore hydrogen production. The results are not unanimous as to which system is the second-best. The three systems need to be investigated in more detail before firm conclusions can be drawn. It is recommended that attention also be paid to the economic and social pillars of sustainability, and to the exergetic sustainability of technological systems in general, as exergetic assessment results are independent of changing and subjective models, weighting factors and other variables.
Renewable energy sources are currently presented as an economically viable and environmentally safe option in the near future. A major constraint to the incorporation of wind and solar generation at large scale is the increase of variability in the power system. To assure the perpetual balance between power production and gross consumption a significant improvement on power systems flexibility is required. Such flexibility in the power system can be achieved by two options on the demand side through demand response obtained through industrial processes: Storage and Substitution. The power system model in study contemplates the purchase of electricity from the Dutch Balancing Market. The electricity prices of the Balancing Market are considered unpredictable. The storage system is characterized by the size of the storage tank and by ramp up/down rates, reflecting the changing speed of the production levels. The substitution system is characterized by the ramp rate of substitution between electricity and an alternative energy carrier as input. The impact of the parameters on the Power System Flexibility when connected to the balancing market under several scenarios was analyzed by Linny-R, a software tool that applies Linear Programming optimization. For the storage system a bigger tank size, a higher ramp rate and a high level of predictability will increase the flexibility of the system. As the actual predictability of the balancing market is limited, the flexibility is limited too, which makes the storage system a questionable option. For the substitution system flexibility is increased by a higher ramp. The effect of the predictability is less dominant, which makes substitution a suitable flexibility enabler for the current Dutch market system. In this context, a restructure of the energy markets, considering the prices predictability, is suggested, as a way of easing the penetration of renewable energy sources.
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Renewable energy sources are currently presented as an economically viable and environmentally safe option in the near future. A major constraint to the incorporation of wind and solar generation at large scale is the increase of variability in the power system. To assure the perpetual balance between power production and gross consumption a significant improvement on power systems flexibility is required. Such flexibility in the power system can be achieved by two options on the demand side through demand response obtained through industrial processes: Storage and Substitution. The power system model in study contemplates the purchase of electricity from the Dutch Balancing Market. The electricity prices of the Balancing Market are considered unpredictable. The storage system is characterized by the size of the storage tank and by ramp up/down rates, reflecting the changing speed of the production levels. The substitution system is characterized by the ramp rate of substitution between electricity and an alternative energy carrier as input. The impact of the parameters on the Power System Flexibility when connected to the balancing market under several scenarios was analyzed by Linny-R, a software tool that applies Linear Programming optimization. For the storage system a bigger tank size, a higher ramp rate and a high level of predictability will increase the flexibility of the system. As the actual predictability of the balancing market is limited, the flexibility is limited too, which makes the storage system a questionable option. For the substitution system flexibility is increased by a higher ramp. The effect of the predictability is less dominant, which makes substitution a suitable flexibility enabler for the current Dutch market system. In this context, a restructure of the energy markets, considering the prices predictability, is suggested, as a way of easing the penetration of renewable energy sources.
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.
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.
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.
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.
This research project gives an integrated technical and institutional design to outline how wind energy peaks can be converted into value-added products by making optimal use of the synergies that may exist in the Rotterdam Harbor area. As the number of hours that power prices are very low is limited, the existing industrial infrastructure and (local) market for steam and intermediate or final products is vital for reducing the (additional) investment cost for the power-to-value options, which improves their economic feasibility, in particular compared to other sites that lack such industrial clusters and local market(s). Consequently, the implementation of such “power-to-value” options in the Port of Rotterdam can contribute to the greening of the industrial processes in that area.
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This research project gives an integrated technical and institutional design to outline how wind energy peaks can be converted into value-added products by making optimal use of the synergies that may exist in the Rotterdam Harbor area. As the number of hours that power prices are very low is limited, the existing industrial infrastructure and (local) market for steam and intermediate or final products is vital for reducing the (additional) investment cost for the power-to-value options, which improves their economic feasibility, in particular compared to other sites that lack such industrial clusters and local market(s). Consequently, the implementation of such “power-to-value” options in the Port of Rotterdam can contribute to the greening of the industrial processes in that area.