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Identification of Manipulation in Receding Horizon Electricity Markets

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Future distribution network markets will need to be flexible enough to enable the participation of small-scale customers with distributed energy resources. We propose using a receding horizon market that can manage the state-dependent decisions and large uncertainties of these participants. Unfortunately, this added flexibility creates new opportunities for agents to manipulate the actions of others by misrepresenting their true preferences for energy. This paper investigates this form of market manipulation in detail by first formalizing the notions of receding horizon inconsistency and manipulation. We present a method for experimentally calculating the impact of a manipulative agent, and run it on two market settings, one based on a wholesale market and the other on a market providing distribution network support. We develop simple privacy-preserving indicators to identify inconsistency and manipulation, and demonstrate a difference in the behavior of uncertain and manipulative agents. When using these indicators in a test for receding horizon manipulation, we correctly identify more than 95% of the days in which the greedy agents undertake the most harmful form of manipulation. Market operators can use these tools to run the system closer to its social optimum by restricting or penalizing manipulative actions.

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IEEE Transactions on Smart Grid

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