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We consider a game in which one player (the principal) seeks to incentivize another player (the agent) to exert effort that is costly to the agent. Any effort exerted leads to an outcome that is a stochastic function of the effort. The amount of effort exerted by the agent is private information for the agent and the principal observes only the outcome; thus, the agent can misreport his effort to gain higher payment. Further, the cost function of the agent is also unknown to the principal and the agent can also misreport a higher cost function to gain higher payment for the same effort. We pose the problem as one of contract design when both adverse selection and moral hazard are present. We show that if the principal and agent interact only finitely many times, it is always possible for the agent to lie due to the asymmetric information pattern and claim a higher payment than if he were unable to lie. However, if the principal and agent interact infinitely many times, then the principal can utilize the observed outcomes to update the contract in a manner that reveals the private cost function of the agent and hence leads to the agent not being able to derive any rent. The result can also be interpreted as saying that the agent is unable to keep his information private if he interacts with the principal sufficiently often. 

This paper considers optimization problems of energy demand networks including aggregators and investigates strategic behavior of the aggregators. The participants of the network are a utility company, who plays a role of energy supply source, aggregators and a large number of consumers. We suppose that the network will be optimized by price response based or, in other words, market based optimization processes. We also suppose that the aggregator has a strategic parameter in its cost function and, by choosing the parameter strategically, the aggregator will try to pursue its own benefit. This general problem formulation will apply to a specific problem setting, where the aggregator possess battery storage with different specifications: The one is high-performance and expensive and the other is low-performance and cheap. The aggregator will choose total capacity of storage to be installed and a ratio of high-performance storage to low-performance storage as the strategic parameters and try to increase its own benefit. By using numerical examples, we show that the strategic decision making by the aggregator could provide useful insights in qualitative analysis of energy demand networks.