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MASTER THESIS Nr. 610 INTELLIGENT TRADING AGENT FOR POWER TRADING BASED ON THE REPAST TOOLKIT. Ivana Pranjić. Overview. Introduction Agent based modeling Electricity market Smart grid Agent-based modeling of electricity markets Powertac Repast toolkit
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MASTER THESIS Nr. 610INTELLIGENT TRADING AGENT FOR POWER TRADING BASED ON THE REPAST TOOLKIT Ivana Pranjić
Overview • Introduction • Agent based modeling • Electricity market • Smart grid • Agent-based modeling of electricity markets • Powertac • Repast toolkit • Implementing PowerTAC broker using Repast • Conclusion
Introduction • Most systems show signs of complex behavior • Complex adaptive systems – many interacting components • Adaptation and self-organization • Emergence • Non-linearity • Co-evolution • Simulation using agent-based models
Agent-based modeling • Suitable for imitating non-linear characteristics of complex adaptive systems • Agents – behaviors based on sets of rules • Autonomous • Able to learn and adapt • Interactive • Goal-oriented • ABM are flexible, provide natural description of complex systems and capture emergent phenomena
Electricity market • One of the most complex markets in the world • Centralized topology • transmission losses, power outages • Restructuring, liberalization • Distributed electricity generation - reliability, environmental and economical reasons • Introduction of the smart grid • Two-way flow of information and electricity • Integration of numerous new producers and encouraging use of renewable sources • Balancing power supply and demand in real-time
Agent-based modeling of electricity markets • Testing new market designs before implementing them in real life • ABM is commonly used for modeling electricity markets • Agents represent market participants who interact, make decisions, take actions and learn from their experience • There are numerous models of electricity markets • Power Trading Agent Competition (PowerTAC) – agents act as brokers and compete with each other
Repast toolkit • Repast Simphony – a toolkit for agent-based modeling written in Java • Model agents using Java, Groovy, ReLogo or flowcharts • Graphical user interface – control the simulation, modify parameters, use external tools (Pajek, Weka) • Display data through charts and graphs • Libraries for neural networks, genetic algorithms, etc.
Implementing PowerTAC broker using Repast • “Sample broker” – agent template written in Java • Implementing the sample broker using Repast • Configure simulation parameters using the GUI • ClassNotFound and NoClassDefFound errors • Start the simulation without using the GUI • User is not able to control the simulation • Incompatibility between Repast development libraries and libraries used by sample broker
Implementing PowerTAC broker using Repast • Control the simulation execution manually • Give user the opportunity to manually create tariffs and wholesale offers and submit them to the market • PowerTAC simulation is managed by the simulator, not the agent
Conclusion • Agent-based models are often used to model electricity markets • Repast is not appropriate for implementing PowerTAC agent • Incompatible technologies • In Repast the user controls the simulation, in PowerTAC it is done by the simulator • Lack of documentation