Consensus-Based Approach to Peer-to-Peer Electricity Markets With Product Differentiation

Abstract

With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peerto-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peerto-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.

Peer-to-peer electricity market analysis: From variational to Generalized Nash Equilibrium

“…Similar approaches relying on dual decomposition, which iteratively solves the problem in a distributed manner with limited information exchange, were implemented for energy trading between islanded microgrids in [9,18]. Two main drawbacks of these algorithmic approaches are listed in [31]: first, they do not take into account the strategic behaviors of the prosumers; second, they are computationally limited, which might constitute a blocking point when studying large-scale peer-to-peer networks. The latter issue is overcome in [19] with an improved consensus algorithm.…”

“…In practice, the radial structure of the distribution grid calls for hierarchical market designs, involving transmission and distribution network operators [14]. Nevertheless, various degrees of coordination can be envisaged: full coordination organized by a global market operator (transmission network operator), bilateral contract networks [21], fully decentralized market designs allowing peer-to-peer energy trading between the prosumers in a distributed fashion [19,31] or, still, within and between coalitions of prosumers, called community or hybrid peer-to-peer [20]. A community-based organization involves a community manager which organizes trades among the community and is in charge of the interactions with the rest of the market.…”

A coalition formation game framework for peer-to-peer energy trading

“…To this end, by equating (15) to (16) and replacing the value of p c (t) with p d (t) from (17), the trading prices p c (t) and p d (t)…”

“…Trading mechanisms that focus on empowering prosumers in the market are proposed in [11] and [12]. In the literature, integration of P2P trading in the energy market is also discussed via double-auction based [13], fairness based [14], consensus-based [15], negotiation-based [16], generalized Nash equilibrium [17], and orchestrator based [18] approaches respectively.…”

A P2P-Dominant Distribution System Architecture

“…The system-centric matching resembles pool-structured wholesale electricity markets with the single supervisory entity that collects and matches the bids and offers submitted by market participants in a centralized manner. On the other hand, the peer-centric approach is decentralized, which offers more flexibility for accommodating their preferences, [11], and allows for distributed decision-making protocols that preserve privacy of peers, [19], [20]. Regardless of the matching mechanism chosen, the large-scale implementation of P2P interactions is expected to affect the ability of the utility to operate the distribution network efficiently and reliably.…”