This paper proposes bilateral contract networks as a new scalable market design for peer-to-peer energy trading. Coordinating small-scale distributed resources to shape overall demand could offer significant value power systems, by alleviating the need investments in upstream generation and transmission infrastructure, increasing network efficiency security. However, incentivising coordination between owners of large-scale at different levels system remains an unsolved challenge. introduces...

This paper proposes a peer-to-peer energy market platform based on the new concept of multiclass management, to coordinate trading between prosumers with heterogeneous (i.e., beyond purely financial) preferences. Power networks are undergoing fundamental transition, traditionally passive distribution network consumers becoming "prosumers"; proactive that actively manage their production and consumption energy. The introduces classes, allowing be treated as product, attributes its source,...

This paper presents an overview of the state art control strategies specifically designed to coordinate distributed energy storage (ES) systems in microgrids. Power networks are undergoing a transition from traditional model centralised generation towards smart decentralised network renewable sources and ES systems, organised into autonomous can provide range services, particularly when throughout power network. The introduction represents fundamental change for networks, increasing problem...

Peer-to-peer trading in energy networks is expected to be exclusively conducted by the prosumers of network with negligible influence from grid. This raises critical question: how can enough encouraged participate peer-to-peer so as make its operation sustainable and beneficial overall electricity network? To this end, paper proposes a motivational psychology framework used effectively design increase user participation. do so, first, state-of-the-art literature discussed following...

This paper proposes a peer-to-peer (P2P) energy trading scheme that can help centralized power system to reduce the total electricity demand of its customers at peak hour. To do so, cooperative Stackelberg game is formulated, in which acts as leader needs decide on price period incentivize prosumers not seek any from it. The prosumers, other hand, act followers and respond leader's decision by forming suitable coalitions with neighboring order participate P2P meet their demand. properties...

The advances in distributed renewable generation technologies recent years have started to cause load balancing issues power networks. Distributed energy storage (ES) systems, although seen as a tool mitigate the stress on local networks, tend be operated only minimize cost of their direct owner. In this paper, cooperative game theory is used construct an grand coalition, which ES system operations are optimized coalitional cost. Case studies then show that forming coalitions effective...

Accurate estimation of battery degradation cost is one the main barriers for participating on energy arbitrage market. This paper addresses this problem by using a model-free deep reinforcement learning (DRL) method to optimize considering an accurate model. Firstly, control formulated as Markov Decision Process (MDP). Then noisy network based approach proposed learn optimized policy storage charging/discharging strategy. To address uncertainty electricity price, hybrid Convolutional Neural...

This paper proposes the novel use of multi-agent sliding mode control for state charge balancing between distributed dc microgrid battery energy storage systems. Unlike existing strategies based on linear consensus protocols, proposed nonlinear strategy: 1) ensures systems are either all charging or discharging, thus eliminating circulating currents, increasing efficiency, and reducing lifetime degradation; 2) achieves faster balancing; 3) avoids overloading during periods high load; 4)...

This paper proposes a unified distributed control strategy for DC microgrid operating modes, without bus voltage signaling or mode detection mechanisms that are normally required decentralized strategies. The proposed is based on the novel integration of controllers energy balancing between storage systems with used to regulate average voltage, and new method controlling grid connected rectifier maintains structure. Under strategy, seamless transitions achieved qualitatively different...

This paper introduces a decentralized market design, which allows distribution system operator to manage local demand constraints by obtaining flexibility from competing aggregators, must in-turn incentivize prosumers provide this flexibility. The novel networked structure accounts for operator-to-aggregator and aggregator-to-prosumer ICT infrastructure contractual arrangements, may limit participants can negotiate transactions with one another. proposed is opt-in prosumers, continue obtain...

This paper proposes a new local energy market design for distribution systems, which integrates peer-to-peer (P2P) trading and probabilistic locational marginal pricing. Distribution pricing P2P have each been proposed as potential alternatives to traditional retail pricing, improve coordination between prosumers with distributed resources. Unidirectional provides scalable approach coordinating demand, considering constraints losses; while allows negotiate mutually beneficial bilateral...

This paper proposes dynamic energy level balancing between distributed storage devices as a strategy to improve frequency regulation and reliability in droop controlled microgrids. has been achieved with multi-agent cooperative control system which modifies the output power of so that they reach balanced state. As approach common are able contribute their full capacity deal generation demand fluctuations microgrid. The also provides secondary control, restoring microgrid reference frequency....

This paper proposes a multi-agent control strategy to coordinate power sharing between heterogeneous energy storage devices distributed throughout DC microgrid. Without requiring central controller, the proposed extends benefits offered by hybrid systems microgrids with batteries and ultracapacitors spatially at different levels of distribution hierarchy. The has following advantages. 1) high frequency microgrid load is provided ultracapacitors. 2) low used for bulk during islanded mode,...

This paper proposes a new convex model predictive control strategy for dynamic optimal power flow between battery energy storage systems distributed in an AC microgrid. The proposed uses problem formulation, based on linear d-q reference frame voltage-current and linearised approximations. allows the flows to be solved as optimisation problem, which fast robust solvers exist. method does not assume real reactive are decoupled, allowing line losses, voltage constraints converter current...

This paper presents a distributed control strategy for state-of-charge balancing between the battery modules of reconfigurable energy storage system. The autonomous share information with their neighbors over sparse communication network and cooperate to reach balanced state charge. proposed provides advantages in terms reduced requirements increased modularity, centralized management Steady-state analysis bounds on mean error mean-squared average estimates used control. enforces module...

This paper proposes a strategy for managing wildfire risks and preventing blackouts using microgrids. To demonstrate this approach, not seen in previous literature, we use the power network of Victoria, Australia, December 2019 as case study. The Fire Weather Index (FWI) is crucial indicator global fire behaviour both spatially temporally, proved with its robust analysis within many studies. FWI applied to Wildfire-Energy System first time, contributing higher spatial temporal resolution...

In light of a reliable and resilient power system under extreme weather natural disasters, networked microgrids integrating local renewable resources have been adopted extensively to supply demands when the main utility experiences blackouts. However, stochastic nature renewables unpredictable contingencies are difficult address with deterministic energy management framework. The paper proposes comprehensive distributionally robust joint chance-constrained (DR-JCC) framework that...

This paper proposes a novel scalable type of multi-agent reinforcement learning-based coordination for distributed residential energy. Cooperating agents learn to control the flexibility offered by electric vehicles, space heating and flexible loads in partially observable stochastic environment. In standard independent Q-learning approach, performance under partial observability drops at scale environments. Here, combination learning from off-line convex optimisations on historical data...

A decentralised control method that deals with current sharing issues in dc microgrids (MGs) is proposed this study. The formulated terms of ‘modified global indicator’ concept, which was originally to improve reactive power ac MGs. In work, the concept extended coordinate MGs, aims preserve main features offered by methods such as no need communication links, central controller or knowledge microgrid topology and parameters. This indicator inserted between voltage variables adopting a...