5.2.1 The Framing of Preferential Choice -- 5.2.2 Framing Effects, Construal Levels, and Individual Differences -- 5.2.3 The Present Study -- 5.3 Data and Methods -- 5.4 Results -- 5.4.1 Basic Differences Between Tariff Evaluations -- 5.5 Discussion and Conclusion -- References -- 6 AgentUDE: A Smart Broker Agent for Autonomous PowerTrading -- 6.1 Introduction -- 6.2 Related Work -- 6.2.1 Electricity Demand and Price Forecasting -- 6.2.2 Strategic Bidding in Wholesale Markets -- 6.2.3 Tariff Forming in Retail Markets -- 6.3 Experimental Setup and Resources -- 6.3.1 Power TAC Tournament Manager -- 6.3.2 Power TAC Log Analysis Tool -- 6.4 AgentUDE14: A Champion Agent -- 6.4.1 Wholesale Market -- 6.4.2 Retail Market -- 6.5 AgentUDE15: Utilizing Storage Capacities -- 6.5.1 Experimental Setup -- 6.5.2 Results -- 6.6 AgentUDE17: A State-of-the-Art Broker -- 6.6.1 AgentUDE17: Smart Bidding in Wholesale Markets -- 6.6.2 AgentUDE17: Evolutionary Trading in Retail Markets -- 6.7 Conclusion and Future Work -- 6.8 AgentUDE Executables and Resources -- References -- 7 Upgrading a Winning Agent to Not Winning: The Case of Agent Mertacor in Power TAC -- 7.1 Introduction -- 7.2 Related Work -- 7.2.1 The Power TAC Environment -- 7.2.2 Pivotal Broker Designs -- 7.3 Mertacor: A Winning Power TAC Agent -- 7.3.1 The Wholesale Market Module -- 7.3.2 The Retail Market Module -- 7.3.3 Mertacor Prediction Strategy -- 7.4 Competition Results (2019, 2020, 2021) and Discussion -- 7.5 Conclusions -- References -- 8 SPOT: Strategies for Power Trading in Wholesale Electricity Markets -- 8.1 Introduction -- 8.2 Background -- 8.2.1 PowerTAC and Related Agent Strategies -- 8.2.2 Periodic Double Auctions (PDAs) -- 8.2.3 Monte Carlo Tree Search (MCTS) -- 8.3 Learning Prices in Dynamic Wholesale Market -- 8.3.1 Supervised Price Predictors -- 8.3.2 Dynamic MDP Price Predictor. |