Distributed Adaptive Primal Algorithm for P2P-ETS over Unreliable Communication Links

Abstract

Algorithms for distributed coordination and control are increasingly being used in smart grid applications including peer-to-peer energy trading and sharing to improve reliability and efficiency of the power system. However, for realistic deployment of these algorithms, their designs should take into account the suboptimal conditions of the communication network, in particular the communication links that connect the energy trading entities in the energy network. This study proposes a distributed adaptive primal (DAP) routing algorithm to facilitate communication and coordination among proactive prosumers in an energy network over imperfect communication links. The proposed technique employs a multi-commodity flow optimization scheme in its formulation with the objective to minimize both the communication delay and loss of energy transactional messages due to suboptimal network conditions. Taking into account realistic constraints relating to network delay and communication link capacity between the peers, the DAP routing algorithm is used to evaluate network performance using various figures of merit such as probability of signal loss, message delay, congestion and different network topologies. Further, we address the link communication delay problem by redirecting traffic from congested links to less utilized ones. The results show that the proposed routing algorithm is robust to packet loss on the communication links with a 20% reduction in delay compared with hop-by-hop adaptive link state routing algorithm.

Energy Peer-to-Peer Trading in Virtual Microgrids in Smart Grids: A Game-Theoretic Approach

“…P2P energy trading scheme has recently gained traction with diverse motivations [3], [4], [6], [7], [10]- [14]. The motivations include modelling the psychological behaviour of the traders, the problems of feed-in tariff (FiT), the imposition of energy dispatch limits on distributed energy generators (DEG) by some local governments [13], [15] and incentives [16], [17].…”

“…Supposing a strictly RES trading system and considering that RES is unschedulable, we can as well discuss both (7) and (10) with respect to load uncertainty demand quantity, ii . In that case, we rewrite (7) as follows…”

“…These datasets are generated as uniformly distributed random variables using MATLAB tool. Using (16) and (17) in (7), we evaluate the optimal energy trading costs for RES and nRES. We adopt the energy pricing parameter, namely P (g) j = 16p for each unit of energy produced [3] and P (b) ji = 12p.…”

“…When these prosumers are coordinated using communication systems [3], [4], significant power network values could be achieved including reduced pollution and, increased energy network efficiency and security [5].Reliable communication systems play vital roles in smart grids [3], [6]. For example, communication infrastructure can be leveraged to regroup prosumers into logical clusters called virtual microgrids (VMGs) in order to improve performance and aid network management cost reduction [3], [4], [7].…”

“…Reliable communication systems play vital roles in smart grids [3], [6]. For example, communication infrastructure can be leveraged to regroup prosumers into logical clusters called virtual microgrids (VMGs) in order to improve performance and aid network management cost reduction [3], [4], [7].…”