Designing coalition-based fair and stable pricing mechanisms under private information on consumers’ reservation prices

Abstract

We model the relation between an aggregator and consumers joining a coalition to reduce the risk resulting from the unpredictability of their base load demand, as a Stackelberg game formulated as a mathematical bilevel program with private information on the consumers' reservation prices. At the upper-level of the Stackelberg game, the aggregator optimizes his daily price profile so as to reach a net targeted profit which is the maximum value guaranteeing that no consumer will leave the coalition -to contract with a conventional retailer considered here as a fixed alternative -while meeting fairness criterion imposed by the cost-sharing mechanism. At the lower-level, the consumers are asked to provide in day ahead an estimate of their base load hourly demand profile and to schedule their shiftable loads depending on the price signal sent by the aggregator. We provide algorithms that determine the unique price profile and consumer shiftable load schedules as functions of the reservation price estimates. The Stackelberg game between the aggregator and the consumers being repeated for a period of time, the aggregator has the possibility to update his estimates of the reservation prices relying on a feedback function which depends on the percentage of activated loads. A randomized algorithm for consumers' reservation price learning based on regret minimization is provided. For four cost-sharing mechanisms such as uniform allocation, stand-alone cost, Shapley value, separable and non-separable costs, we determine the closed form of the aggregator's optimal net targeted profit guaranteeing the stability of the coalition. We also determine conditions guaranteeing the core non-emptiness and prove that for a profit-maximizing aggregator, the stand-alone cost is always preferable to the Shapley value, which coincides with the uniform allocation. Furthermore, the optimal size of the coalition -in terms of the aggregator's profit -can be determined analytically when the Shapley value is implemented as cost-sharing mechanism. The results are illustrated on a case study where we show that there exists an optimal net targeted profit below which the consumers energy bill is lower when joining the aggregator than with the conventional retailer. Coalition dynamics is also analyzed numerically depending on the consumer inertia in their energy supplier choice process, for each cost-sharing mechanism.

Peer to peer electricity markets

“…In order for them to remain marginal, the design of market mechanisms [52] and the redistribution of possible taxes -see section 6.2 -must ensure their fairness [53]. When it is a question of a service rendered by an agent to preserve a common infrastructure, the contribution of each one should be evaluated from collaborative games approaches [54].…”

Local energy trading for microgrids : modeling human behavior, uncertainty and grid constraints

“…The second group of settings uses Stackelberg games to model the relation between the prosumers and their MGO or DSO. This setting is considered in [9,10,55,142,143,162,209,253,282]. In [55,143,162], the leader of the game is the MGO, while the prosumers are the followers.…”

“…This setting is considered in [9,10,55,142,143,162,209,253,282]. In [55,143,162], the leader of the game is the MGO, while the prosumers are the followers. The goal of the leader is to maximize its profit and it starts by submitting initial internal buying and selling prices to the prosumers.…”