Agent-based Modeling and Simulation of Competitive Wholesale Electricity Markets

Guerci, Éric; Rastegar, Mohammad Ali; Cincotti, Silvano

doi:10.1007/978-3-642-12686-4_9

Cited by 49 publications

(40 citation statements)

References 66 publications

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“…ABMs are now ubiquitous when modelling the electricity sector [84][85][86] because of their higher explanatory power in general [87,88] and better ability to explore the effects of increasing amounts of renewable energy in the mix [89][90][91]. Multiagent systems can also be used to actually run a decentralized power grid [92,93].…”

Section: Specific Problems With Energy Modelsmentioning

confidence: 99%

“…The price reductions will also continue since we have many, many doublings to go and renewable energy uses much less raw material than fossil energy. For example, wind needs between 2 grams (airborne wind energy [85]) and 10 grams of material per kWh [86,87] while a coal fired power plant burns about 300 grams per kWh [88,89]. And electric vehicles running on this renewable energy use only 400 kg of battery (falling to 100-200 kg) to replace over 15 tons of crude oil over the lifetime of the car [91,92].…”

Section: Disruptive Technological Innovationmentioning

confidence: 99%

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Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

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Section: Specific Problems With Energy Modelsmentioning

confidence: 99%

Section: Disruptive Technological Innovationmentioning

confidence: 99%

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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“…ABMs have gained an increasing interest in different fields of economic research also thanks to the possibility of an extensive and fast simulation analysis for different effects and parameter settings (for a literature review see, e.g., Tesfatsion and Judd, 2006). In the last years, ABMs have become popular to model transitory processes (see, e.g., Nannen and van den Bergh, 2010, Lopolito et al, 2013and Safarzynska and van den Bergh, 2013 and electricity markets (see, e.g., Sensfußet al, 2007, Weidlich and Veit, 2008and Guerci et al, 2010or Ringler et al, 2016 for a recent overview on smart electricity grids). In addition, there is a large body of literature utilizing this approach to investigate the problem of diffusion of eco-innovations (see Cantono and Silverberg, 2009, Bleda and Valente, 2009and Windrum et al, 2009.…”

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confidence: 99%

Optimal policy identification: Insights from the German electricity market

Herrmann

Savin

2017

Technological Forecasting and Social Change

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The diffusion of renewable electricity generating technologies is widely considered as crucial for establishing a sustainable energy system in the future. However, the required transition is unlikely to be achieved by market forces alone. For this reason, many countries implement various policy instruments to support this process, also by re-distributing related costs among all electricity consumers. This paper presents a novel history-friendly agent-based study aiming to explore the efficiency of different mixes of policy instruments by means of a Differential Evolution algorithm. Special emphasis of the model is devoted to the possibility of small scale renewable electricity generation, but also to the storage of this electricity using small scale facilities being actively developed over the last decade. Both combined pose an important instrument for electricity consumers to achieve partial or full autarky from the electricity grid, particularly after accounting for decreasing costs and increasing efficiency of both due to continuous innovation. Among other things, we find that the historical policy mix of Germany introduced too strong and inflexible demand-side instruments (like feed-in tariff) too early, thereby creating strong path-dependency for future policy makers and reducing their ability to react to technological but also economic shocks without further increases of the budget.

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“…Due to the rising needs, several electricity market simulators have been developed, as can be consulted in [5,[121][122][123][124], which provide interesting reviews on electricity market simulators. In fact, a total of 2454 documents related to electricity market simulation can be found in the SCOPUS database, until the end of 2017.…”

Section: Complex Large-scale Simulation Inmentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

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Agent-based Modeling and Simulation of Competitive Wholesale Electricity Markets

Cited by 49 publications

References 66 publications

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Optimal policy identification: Insights from the German electricity market

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

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