This paper models and analyzes Nega-Watt markets. In the proposed setting a utility operator wants to curtail some amount of demanded load during peak hours in order to save energy generation costs. The problem for the operator is twofold: (i) select the consumers, and (ii) determine the amounts of load to be curtailed by each one of them. The major novelty in this setup stems from the arising uncertainty due to consumer nonengagement. Even if an a priori agreement is reached between the operator and a consumer about the load to be curtailed, the consumer may not succeed to curtail the load. The second element that makes our problem formulation different from other markets is the incentive design per se. We argue that the operator needs to employ a two-branch incentive, that is, provide consumers with a reward if they actually curtail the load and charge them a fine if they do not. We employ this dualmode incentive into various game-theoretic market mechanisms such as bilateral negotiation and different types of Stackelberg mechanisms that result in selecting the consumers and the amounts of load to curtail. We define equilibrium points for the mechanisms and compute the resulting contractual agreements between the operator and each selected consumer for load curtailment. Our results reveal interesting insights about the impact of the competition arising among consumers and the consumer-operator interaction on the expected benefits for the operator and the consumers. 1
We model and analyze a peer-to-peer (p2p) energy trading market under uncertainty in the traded energy, in a setting with multiple sellers and buyers. A set of prosumers sell in the market their energy surplus units, which are subject to uncertainty for being actually available, while other prosumers buy energy to cover their deficit units, which are subject to uncertainty for being actually needed. Given the different levels of uncertainty of different prosumers and different energy units, the p2p trading problem is to match energy demand and supply and to specify the payments of buyers and compensations to sellers.We propose an innovative variant of the Vickrey-Clarke-Groves (VCG) auction customized to our setting, motivated by the properties of the standard form of the VCG auction, namely maximizing social welfare while ensuring participants' truthfulness. We determine the bidding profiles of players by considering the uncertainty in the declared amounts of energy surplus or deficit. Moreover, we develop a low-complexity allocation rule, that provably leads to maximization of the expected social welfare, where the expectation is with respect to uncertainties of energy units. We also derive closed-form expressions for winners' payments. We compare our mechanism to a double auction, which is currently used as a p2p trading mechanism. The results reveal that our mechanism outperforms the double auction one, and lead to interesting intuitions and guidelines that shed light into p2p energy market design.
CCS CONCEPTS• Theory of computation → Computational pricing and auctions.
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