Simulating Business Models for Electricity Storage

Electricity storage systems (ESS) are hailed by many scholars and practitioners as a key element of the future electricity systems and a key step towards the transition to a renewable energy system. However, the global speed of ESS implementation is relatively slow. There are several reasons for the slow rate of ESS deployment, one of them is the lack of viable business models.This dissertation suggests a way to study the design of business models for ESS from different actors’ perspectives in the Dutch electricity sector given several complexities and deep uncertainties. We follow a step-by-step design framework, and adopt literature review and data analysis methods in order to set goals, objectives, and constraints; and we develop a design space. Then, we combine agent-based modelling (ABM) and exploratory modelling analysis (EMA) approaches to test ESS business models incorporating several complexities and uncertainties. Our experiments focus mostly on extreme conditions .Our results show that ESS is not profitable in most scenarios. The results also show that generally a “wholesale arbitrage” business model leads to more profit than “reserve capacity”. In addition, we found that in the scenarios with extremely high share electricity generation from renewable sources, ESS is not necessarily profitable. Besides, we found that more implementation of ESS does not necessarily reduce the average profit for ESS projects. Finally, we explain that improving technologies is expected to improve the desirability of ESS more than government intervention

Exploring the dynamics of the world energy system : an agent-based - system dynamics model

Due to limitation of some energy resources, there are concerns whether the world energy system (WES) can supply sufficient energy for societies in the future. Scientists develop models to gain insights into the system. GEMBA is a system dynamics model developed by Dale to explore the global energy supply using biophysical economics approach. Biophysical economics theory analyzes the economy based on the physical properties and structures of real economic systems and it considers natural resources and their impacts on the economic processes. GEMBA like other system dynamics models adopt a top-down view on the WES. The top-down view assumes that all elements of a system have global knowledge about the system. Many of such models do not capture some characteristics of a WES such as geographical resource distribution and demand diversity. In addition, it is often not possible to analyze the emergent effects from variations in low-level elements on the system behavior in top-down analysis. We developed an exploratory agent-based model, by taking a biophysical economics lens, for bottom-up analysis of a WES and relevant natural resources. We decomposed the world into a number of geographical regions to capture resource distribution and demand diversity in the WES. Our Multi-Region World Energy Model (MRWEM) combines the GEMBA with the concept of energy-return-on-investment (EROI) for imported energy. So, in MRWEM the internal behaviors of the world regions are modeled with GEMBA and the system dynamics approach while the inter-regions behaviors are modeled with agent-based modeling approach. MRWEM exhibits a number of advantages over GEMBA. First, it provides insights on the inter-regions energy movements and trade which is impossible in GEMBA. Second, MRWEM provides flexibility in analysis as changes in the model can be done at the level of regions not the whole world. Also, MRWEM facilitates analysts to analyze the WES using different geographical decompositions. Moreover, it shows that the hybrid adoption of agent-based modeling and system dynamics is possible and insightful when the level of abstraction is very high

Is electricity storage systems in the Netherlands indispensable or doable? Testing electricity storage business models with exploratory agent-based modeling

Electricity storage systems (ESS) are hailed by many scholars and practitioners as a key element of the future electricity systems and a key step toward the transition to renewables . Nonetheless, the global speed of ESS implementation is relatively slow, and among possible reasons is the lack of viable business models. We developed an agent-based model to simulate the behavior of ESS within the Dutch electricity market. We adopted an exploratory modeling analysis (EMA) approach to investigate the effects of two specific business models on the value of ESS from the perspective of both investors and the government under uncertainties in the ESS technical and economics characteristics, and uncertainties in market conditions and regulations. Our results show ESS is not profitable in most scenarios, and generally wholesale arbitrage business model leads to more profit than reserve capacity. In addition, ESS economic and technical characteristics play more important roles in the value of ESS than market conditions, and carbon pricing.Comment: 39 Pages, 6 Figures, 2 tables, article under revie

An Exploratory Model to Investigate the Dynamics of the World Energy System: A Biophysical Economics Perspective

Energy is inherent part of our current life. No one can imagine living without it. It has changed the lifestyle of people and it will continue to do so in future. About 80% of current global total primary energy supply belongs to non-renewable resources. It is also expected that non-renewable resources dominate in total primary energy supply in next decades. The world is moving towards scarcity in non-renewable energy resources. Most studies about the world energy-economy system use standard economic theories. These theories do not include limitations of natural resources and the environment. Biophysical economics theory considers the relation between economy and natural resources. It has been used as the basis of various energy-economy models. However, those models have a global view on this system. They do not sufficiently provide insights into the properties and international trading behaviors of energy suppliers and consumers. So, they do not provide insight on the effects of these interactions on the emergent behavior of the global energy system. Biophysical economics has high potential for providing insights into the world energy system. However, the current biophysical models are not capable of representing the world energy system considering trade and other interactions among regions. Considering this problem the main research question in this thesis is stated as follow: What can be learnt from biophysical economics theory when it is used for the modeling of the world energy system considering energy trade? In order to answer this question, the objective of this research is set to develop a model for exploring the behaviors of the world energy system with multiple interacting regions. The theory of complex adaptive systems (CAS) is used to enable biophysical economics theory to consider trade and other interactions among regions. In order to model and analyze the world energy system from both biophysical economics and CAS perspective, agent-based modeling is identified as the most appropriate paradigm. This thesis provides an analysis of the world energy system from both technical and actor perspectives. The technical analysis aims at describing the main characteristics of and activities in the world energy system. It also identifies the main uncertainties within this system. Actor analysis aims at providing a regional decomposition for the world energy system. To achieve this goal, a number of current regional decompositions are identified. One of those is selected on the basis of a number of criteria. This research uses the 11-region decomposition of (IIASA, 2012b) To develop the objective model, a two-step approach is used. In the first step, the aggregated world energy model is developed without considering energy trade. In the second step, the multi-region world energy model is developed considering energy trade. The aggregated world energy model is the implementation of the most recent biophysical economics model in the literature, GEMBA by (M. A. J. Dale, 2010), in NetLogo. The multi-region model inherits all characteristics of the first model. However, it considers each world region as a world and facilitates the energy trade among them. The models are evaluated by comparison with historical data and literature. The multi-region model shows that the energy trade can be modeled and explored using the biophysical economics perspective. Since it includes energy price as a parameter, it also shows that energy trade can be an interface between biophysical economics and standard economics as well. In addition, exploratory experiments show that size of energy trade for regions is low in comparison to their total production/consumption. Moreover, they show that the size of total energy trade will peak and decline. It is because energy trade mostly belongs to non-renewable energy and the production of non-renewables will peak and decline in the future. In addition, it shows that lower energy trade can increase the share of production of energy.System Engineering, Policy Analysis and ManagementInfrastructure Systems & ServicesTechnology, Policy and Managemen

Exploring the dynamics of the world energy system : an agent-based - system dynamics model

Due to limitation of some energy resources, there are concerns whether the world energy system (WES) can supply sufficient energy for societies in the future. Scientists develop models to gain insights into the system. GEMBA is a system dynamics model developed by Dale to explore the global energy supply using biophysical economics approach. Biophysical economics theory analyzes the economy based on the physical properties and structures of real economic systems and it considers natural resources and their impacts on the economic processes. GEMBA like other system dynamics models adopt a top-down view on the WES. The top-down view assumes that all elements of a system have global knowledge about the system. Many of such models do not capture some characteristics of a WES such as geographical resource distribution and demand diversity. In addition, it is often not possible to analyze the emergent effects from variations in low-level elements on the system behavior in top-down analysis. We developed an exploratory agent-based model, by taking a biophysical economics lens, for bottom-up analysis of a WES and relevant natural resources. We decomposed the world into a number of geographical regions to capture resource distribution and demand diversity in the WES. Our Multi-Region World Energy Model (MRWEM) combines the GEMBA with the concept of energy-return-on-investment (EROI) for imported energy. So, in MRWEM the internal behaviors of the world regions are modeled with GEMBA and the system dynamics approach while the inter-regions behaviors are modeled with agent-based modeling approach. MRWEM exhibits a number of advantages over GEMBA. First, it provides insights on the inter-regions energy movements and trade which is impossible in GEMBA. Second, MRWEM provides flexibility in analysis as changes in the model can be done at the level of regions not the whole world. Also, MRWEM facilitates analysts to analyze the WES using different geographical decompositions. Moreover, it shows that the hybrid adoption of agent-based modeling and system dynamics is possible and insightful when the level of abstraction is very high

Are electricity storage systems in the Netherlands indispensable or doable? Testing single-application electricity storage business models with exploratory agent-based modeling

Electricity storage systems (ESS) are hailed by many scholars and practitioners as a key element of the future electricity systems and a key step toward the transition to renewables. Nonetheless, the global speed of ESS implementation is relatively slow, and among possible reasons is the lack of viable business models. We developed an agent-based model to simulate the behavior of ESS within the Dutch electricity market. We adopted an exploratory modeling analysis (EMA) approach to investigate the effects of two single-application business models over a period of twenty years on the value of ESS from the perspective of both investors and the government under uncertainties in the ESS technical and economics characteristics, and uncertainties in market conditions and regulations. Our results show ESS is not profitable in most scenarios, and generally “wholesale arbitrage” business model leads to more profit than “reserve capacity”. In addition, ESS economic and technical characteristics play more important roles in the value of ESS than market conditions, and carbon pricing

Business models design space for electricity storage systems:Case study of the Netherlands

Because of weather uncertainty and dynamics, power generation from some renewable energy technologies is variable. Electricity storage is recognized as a solution to better integrate variable renewable generation into the electricity system. Despite considerable growth in the research on the electricity storage, implementation of electricity storage systems (ESS) is globally negligible because of technical, institutional, and business model challenges. We use literature review and data analysis to provide a conceptual framework and a design space for ESS business models in the case of Dutch electricity sector by taking technological, institutional, and business model considerations into account. We provide a map of single-application business models for ESS in the Netherlands which can be used as a basis for making ESS application portfolios and evaluating ESS business models in other parts of the world as well. Furthermore, this research can be used to inform models that explore the evolution of ESS