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In light of a reliable and resilient power system under extreme weather and natural disasters, networked microgrids integrating local renewable resources have been adopted extensively to supply demands when the main utility experiences blackouts. However, the stochastic nature of renewables and unpredictable contingencies are difficult to address with the deterministic energy management framework. The paper proposes a comprehensive distributionally robust joint chance-constrained (DR-JCC) framework that incorporates microgrid island, power flow, distributed batteries and voltage control constraints. All chance constraints are solved jointly and each one is assigned to an optimized violation rate. To highlight, the JCC problem with the optimized violation rates has been recognized as NP-hard and challenging to solve. This paper proposes a novel evolutionary algorithm that successfully solves this problem and reduces the solution conservativeness (i.e., operation cost) by around 50% compared with the baseline Bonferroni Approximation. We construct three data-driven ambiguity sets to model uncertain solar forecast error distributions. The solution is thus robust for any distribution in sets with the shared moments and shape assumptions. The proposed method is validated by robustness tests based on these sets and firmly secures the solution robustness. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed coordination control strategy for load sharing and energy balancing between heterogeneous energy storages. These control objectives are satisfied through a two-level control structure. At the primary level, the decentralized virtual impedance control, without the requirement of communication links, allocates the low frequency component of the loads to batteries, while the high frequency component is allocated to ultracapacitors. Distributed control strategy, introduced at the secondary level over a sparse communication network, achieves battery state of charge balancing and regulation of the local bus voltages. Two sets of data are exchanged via the communication links, the local bus voltages, and state of charges of batteries. The distributed controller for the restoration of local bus voltages implements an average consensus protocol, while the controller for energy balancing uses a cooperative protocol. In addition, the ultracapacitor voltages are locally restored at a slower time-scale. The proposed control strategy is resilient to communication link failures and features plug-and-play capability. Presented results demonstrate performance of the proposed control strategy for an islanded 380 VDC datacenter with variable loads. Different operating conditions are verified through the RTDS Technologies real-time digital power system simulator using switching converter models and nonlinear battery models. [ABSTRACT FROM AUTHOR]

This paper proposes bilateral contract networks as a new scalable market design for peer-to-peer energy trading. Coordinating small-scale distributed energy resources to shape overall demand could offer significant value to power systems, by alleviating the need for investments in upstream generation and transmission infrastructure, increasing network efficiency and increasing energy security. However, incentivising coordination between the owners of large-scale and small-scale energy resources at different levels of the power system remains an unsolved challenge. This paper introduces real-time and forward markets, consisting of energy contracts offered between generators with fuel-based sources, suppliers acting as intermediaries and consumers with inflexible loads, time-coupled flexible loads and/or renewable sources. For each type of agent, utility-maximising preferences for real-time contracts and forward contracts are derived. It is shown that these preferences satisfy full substitutability conditions essential for establishing the existence of a stable outcome—an agreed network of contracts specifying energy trades and prices, which agents do not wish to mutually deviate from. Important characteristics of energy trading are incorporated, including upstream–downstream energy balance and forward market uncertainty. Full substitutability ensures a distributed price-adjustment process can be used, which only requires local agent decisions and agent-to-agent communication between trading partners. [ABSTRACT FROM AUTHOR]

The advances in distributed renewable generation technologies in recent years have started to cause load balancing issues in power networks. Distributed energy storage (ES) systems, although seen as a tool to mitigate the stress on local networks, tend to be operated only to minimize the energy cost of their direct owner. In this paper, cooperative game theory is used to construct an energy grand coalition, in which ES system operations are optimized to minimize the coalitional energy cost. Case studies then show that forming energy coalitions is effective in reducing the variability of a local network load profile. The resulting cooperative game is mathematically proven to be balanced, which means the energy cost savings from the cooperative ES operation can be allocated to the players within the energy grand coalition in a manner that disincentivizes them from exiting from the grand coalition to form smaller coalitions. [ABSTRACT FROM AUTHOR]

This paper proposes the novel use of multi-agent sliding mode control for state of charge balancing between distributed dc microgrid battery energy storage systems. Unlike existing control strategies based on linear multi-agent consensus protocols, the proposed nonlinear state of charge balancing strategy: 1) ensures the battery energy storage systems are either all charging or all discharging, thus eliminating circulating currents, increasing efficiency, and reducing battery lifetime degradation; 2) achieves faster state of charge balancing; 3) avoids overloading the battery energy storage systems during periods of high load; and 4) provides plug and play capability. The proposed control strategy can be readily integrated with existing multi-agent controllers for secondary voltage regulation and accurate current sharing. The performance of the proposed control strategy was verified with an RTDS Technologies real-time digital simulator, using switching converter models and nonlinear lead-acid battery models. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the state of the art control strategies specifically designed to coordinate distributed energy storage (ES) systems in microgrids. Power networks are undergoing a transition from the traditional model of centralised generation towards a smart decentralised network of renewable sources and ES systems, organised into autonomous microgrids. ES systems can provide a range of services, particularly when distributed throughout the power network. The introduction of distributed ES represents a fundamental change for power networks, increasing the network control problem dimensionality and adding long time-scale dynamics associated with the storage systems’ state of charge levels. Managing microgrids with many small distributed ES systems requires new scalable control strategies that are robust to power network and communication network disturbances. This paper reviews the range of services distributed ES systems can provide, and the control challenges they introduce. The focus of this paper is a presentation of the latest decentralised, centralised and distributed multi-agent control strategies designed to coordinate distributed microgrid ES systems. Finally, multi-agent control with agents satisfying Wooldridge’s definition of intelligence is proposed as a promising direction for future research. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-agent dynamic optimal power flow (DOPF) strategy for microgrids with distributed energy storage systems. The proposed control strategy uses a convex formulation of the ac DOPF problem developed from a d-q reference frame voltage–current model and linear power flow approximations. The convex DOPF problem is divided between autonomous agents and solved based on local information and neighbour-to-neighbour communication over a sparse communication network, using a distributed primal subgradient algorithm. Each agent is only required to solve convex quadratic sub-problems, for which robust and efficient solvers exist, making the control strategy suitable for receding horizon model predictive control. Also, the agent sub-problems require limited power network information and include only a subset of the centralised optimisation problem decision variables and constraints, providing scalability and data privacy. Unlike existing distributed optimal power flow methods, such as alternating direction method of multipliers, under the proposed control strategy the information required by each agent is independent of the communication network topology, providing increased flexibility and robustness. The performance of the proposed control strategy was verified for an ac microgrid with distributed lead-acid batteries and intermittent photovoltaic generation, using an RTDS Technologies real-time digital simulator. [ABSTRACT FROM AUTHOR]

This brief proposes a new convex model predictive control (MPC) strategy for dynamic optimal power flow between battery energy storage (ES) systems distributed in an ac microgrid. The proposed control strategy uses a new problem formulation, based on a linear $d$ – $q$ reference frame voltage-current model and linearized power flow approximations. This allows the optimal power flows to be solved as a convex optimization problem, for which fast and robust solvers exist. The proposed method does not assume that real and reactive power flows are decoupled, allowing line losses, voltage constraints, and converter current constraints to be addressed. In addition, nonlinear variations in the charge and discharge efficiencies of lithium ion batteries are analyzed and included in the control strategy. Real-time digital simulations were carried out for an islanded microgrid based on the IEEE 13 bus prototypical feeder, with distributed battery ES systems and intermittent photovoltaic generation. It is shown that the proposed control strategy approaches the performance of a strategy based on nonconvex optimization, while reducing the required computation time by a factor of 1000, making it suitable for a real-time MPC implementation. [ABSTRACT FROM PUBLISHER]

This paper proposes multi-agent energy storage system aggregation as a means of scaling energy management to low voltage microgrids with distributed energy storage systems. Based on this concept, a hierarchical control strategy is developed for an AC microgrid with distributed battery and ultracapacitor energy storage systems. On the tertiary control level, the energy management problem is made scalable by considering each type of energy storage system in aggregate. This addresses the “curse of dimensionality,” since additional energy storage systems do not increase the optimization problem dimension, and allows nonlinear energy storage models to be used for optimization, accounting for variable efficiency, self-discharge, and lifetime degradation. On the secondary control level, multi-agent state of charge balancing, reactive power sharing, frequency restoration, and voltage restoration are combined, to aggregate energy storage systems for the tertiary control. This includes the novel use of multi-agent sliding mode control for state of charge balancing between AC microgrid energy storage systems. Unlike a linear state of charge balancing strategy, circulating currents are prevented, increasing efficiency and reducing lifetime degradation. An RTDS Technologies real-time digital simulator was used to verify the performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

A decentralised control method that deals with current sharing issues in dc microgrids (MGs) is proposed in this study. The proposed method is formulated in terms of 'modified global indicator' concept, which was originally proposed to improve reactive power sharing in ac MGs. In this work, the 'modified global indicator' concept is extended to coordinate dc MGs, which aims to preserve the main features offered by decentralised control methods such as no need of communication links, central controller or knowledge of the microgrid topology and parameters. This global indicator is inserted between current and voltage variables by adopting a virtual capacitor, which directly produces an output current sharing performance that is less relied on mismatches of the multi-bus network. Meanwhile, a voltage stabiliser is complementary developed to maintain output voltage magnitude at steady state through a shunt virtual resistance. The operation under multiple dc-buses is also included in order to enhance the applicability of the proposed controller. A detailed mathematical model including the effect of network mismatches is derived for analysis of the stability of the proposed controller. The feasibility and effectiveness of the proposed control strategy are validated by simulation and experimental results. [ABSTRACT FROM AUTHOR]

With the decreasing cost of green technologies and the increasing ambitions to reach the net-zero carbon emissions target, more communities are engaged in renewable deployment and energy-intensive technologies such as heat pumps and electric vehicles will be intensively adopted in the near future. The integration of these appliances in lower grid levels will likely require grid reinforcements. However, some of these appliances are flexible and there is an opportunity to explore their flexibility potential to optimise the investment costs further. This paper proposes an optimal design strategy for a grid-connected site that returns the renewable generation and storage's optimal sizing capacities and the required network reinforcement capacity. The novelty of the work is integrating network upgrade costs and considering flexibility from distributed flexible resources across planning and operation. The problem is formulated as a mixed integer piecewise linear problem, with the capacities of generation, storage and network upgrade as decision variables. The piecewise linear cost function related to the upgrade costs figuring in the objective function is then recast as a mixed-integer problem, and the flexible resources are modelled through an approximation method as a single virtual flexible asset. The application of the strategy on the Perth West smart city project as a case study demonstrates the importance of considering flexibility in the planning phase. The costs related to the storage system can decrease by up to 76%, and the overall costs by up to 35%, with the highest levels of savings, reached for the highest rates of electric vehicle adoption. [Display omitted] • An optimal sizing strategy for grid-connected microgrids is proposed. • Both flexibility from distributed assets and network upgrade costs are incorporated. • The problem is formulated as MINLP and recast into an MILP. • The value of the methods are demonstrated for the Perth West Smart City project. • Considering flexibility from EVs, the overall costs can decrease by up to 35 %. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-agent control strategy to coordinate power sharing between heterogeneous energy storage devices distributed throughout a DC microgrid. Without requiring a central controller, the proposed control strategy extends the benefits offered by hybrid energy storage systems to DC microgrids with batteries and ultracapacitors spatially distributed at different levels of the power distribution hierarchy. The proposed control strategy has the following advantages. 1) The high frequency microgrid load is provided by the ultracapacitors. 2) The low frequency load is provided by batteries used for bulk energy storage during islanded mode, and the main grid during grid connected operation. 3) The ultracapacitor voltages are regulated at a desired reference. 4) State of charge balancing is provided between the batteries. 5) The energy storage systems cooperate based on neighbor-to-neighbor output feedback over a sparse communication network. The only communication requirement is a spanning tree from the ultracapacitor leaders and battery leaders to their respective followers. Simulations are presented demonstrating the performance of the proposed control strategy for a 380 VDC datacenter during grid connected and islanded operation. [ABSTRACT FROM PUBLISHER]

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 for decentralized control strategies. The proposed control strategy is based on the novel integration of distributed controllers for energy balancing between DC microgrid energy storage systems with distributed controllers used to regulate the average DC microgrid bus voltage, and a new method for controlling the grid connected rectifier that maintains the distributed control structure. Under the proposed control strategy, seamless mode transitions are achieved between qualitatively different operating modes, namely, 1) grid connected operation with the rectifier providing load balancing, 2) grid connected operation with the rectifier charging the energy storage systems, and 3) islanded operation. In all operating modes, the average DC microgrid bus voltage is regulated to the microgrid voltage reference, and the energy storage systems are controlled independently of the operating mode to achieve and maintain a balanced energy level. Simulations are presented demonstrating the performance of the proposed control strategy for a 380 VDC datacenter with intermittent photovoltaic generation and communication delays expected from a WiFi control network implementation. [ABSTRACT FROM AUTHOR]

This paper proposes dynamic energy level balancing between distributed storage devices as a strategy to improve frequency regulation and reliability in droop controlled microgrids. This has been achieved with a distributed multi-agent cooperative control system which modifies the output power of droop controlled storage devices so that they reach a balanced energy state. As the storage devices approach a common energy level they are able to contribute their full power capacity to deal with generation and demand fluctuations in the microgrid. The cooperative control system also provides secondary frequency control, restoring the microgrid to the reference frequency. Simulations have been completed showing that the cooperative control system improves frequency regulation compared to traditional droop control strategies when the storage devices begin at different energy levels and the microgrid experiences generation or demand variability. A control input saturation constraint has been developed which ensures that the cooperative control system will not overload the storage devices. [ABSTRACT FROM AUTHOR]

• A novel strategy for managing wildfires and blackouts using microgrids is proposed. • The Fire Weather Index is used to describe the fire risk distribution in a grid. • The Grid and Wildfire Index are linked by line locations and fire risk distribution. • Set Victoria Australia as a case study, 68% of the overall system cost can be saved. 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, in December 2019 as a case study. The Fire Weather Index (FWI) is a crucial indicator of global fire behaviour both spatially and temporally, as proved with its robust analysis within many previous studies. The FWI is applied to a Wildfire-Energy System for the first time, contributing to a higher spatial and temporal resolution to position the wildfire risk in a grid. A novel method is proposed to automatically correlate the wildfire risk index and the power network model using geographical information of the transmission lines. The optimal power flow and grid performances are obtained from a grid model which incorporates wildfire risk distributions. It is shown that a system with installed microgrids can maintain operation under severe fire-related conditions without scheduled or unplanned outages. Finally, a cost-benefit analysis is conducted, which demonstrates that 68% of system costs can be recuperated by implementing networked microgrid solutions. [ABSTRACT FROM AUTHOR]