Generation from distributed renewable energy sources is constantly increasing. Due to its volatility, the integration of this non-controllable generation poses severe challenges to the current energy system. Thus, ensuring a reliable balance of energy generation and consumption becomes increasingly demanding. In our approach to tackle these challenges, we suggest that consumers and prosumers can trade self-produced energy in a peer-to-peer fashion on microgrid energy markets. Thus, consumers and prosumers can keep profits from energy trading within their community. This provides incentives for investments in renewable generation plants and for locally balancing supply and demand. Hence, both financial as well as socio-economic incentives for the integration and expansion of locally produced renewable energy are provided. The efficient operation of these microgrid energy markets requires innovative information systems for integrating the market participants in a user-friendly and comprehensive way. To this end, we present the concept of a blockchain-based microgrid energy market without the need for central intermediaries. We derive seven market components as a framework for building efficient microgrid energy markets. Then, we evaluate the Brooklyn Microgrid project as a case study of such a market according to the required components. We show that the Brooklyn Microgrid fully satisfies three and partially fulfills an additional three of the seven components. Furthermore, the case study demonstrates that blockchains are an eligible technology to operate decentralized microgrid energy markets. However, current regulation does not allow to run local peer-to-peer energy markets in most countries and, hence, the seventh component cannot be satisfied yet.
This paper summarizes the main problems and solutions of power quality in microgrids, distributed-energy-storage systems, and ac/dc hybrid microgrids. First, the power quality enhancement of grid-interactive microgrids is presented. Then, the cooperative control for enhance voltage harmonics and unbalances in microgrids is reviewed. Afterward, the use of static synchronous compensator (STATCOM) in grid-connected microgrids is introduced in order to improve voltage sags/swells and unbalances. Finally, the coordinated control of distributed storage systems and ac/dc hybrid microgrids is explained.
The proliferation of distributed energy resources is setting the stage for modern distribution systems to operate as microgrids, which can avoid power disruptions and serve as resources for fast recovery during macrogrid disturbances. Microgrids are, therefore, major assets to improve the grid resilience. However, the offered resilience is seriously undermined if microgrids are not properly protected in the event of faults within their own boundaries. Distribution protective devices cannot reliably protect microgrids due to the variable and often limited short-circuit capacities of microgrids. Moreover, the research on microgrid protection has not led to a commercially available microgrid relay to date and has little prospect of reaching that level in the near future. As a result, the existing options for reliable microgrid protection remain effectively the subtransmission and transmission system protective devices, e.g., directional overcurrent, distance, and differential relays. Although years of operation in macrogrids support these relays, their performance for microgrids is yet to be analyzed. This paper presents such analysis for different relay types by considering various fault and generation conditions in a microgrid. Time-domain simulations are used to identify the scenarios where the relays function correctly as well as the problematic conditions, on which future research should focus. This paper also presents a short review on direct current (dc) microgrids and their protection requirements.
The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.
This article outlines the ongoing research, development, and demonstrates the microgrid operation currently in progress in Europe, the United States, Japan, and Canada. The penetration of distributed generation (DG) at medium and low voltages is increasing in developed countries worldwide. Microgrids are entities that coordinate DERs (distributed energy resources) in a consistently more decentralized way, thereby reducing the control burden on the grid and permitting them to provide their full benefits. In the context of this article, a microgrid comprises a LV locally-controlled cluster of DERs that behaves, from the grid's perspective, as a single producer or both electrically and in energy markets. A microgrid operates safely and efficiently within its local distribution network, but it is also capable of islanding.
This paper presents a model for the microgrid planning problem with uncertain physical and financial information. The microgrid planning problem investigates the economic viability of microgrid deployment and determines the optimal generation mix of distributed energy resources (DERs) for installation. Net metering is considered for exchanging power with the main grid and lowering the cost of unserved energy and DER investments. A robust optimization approach is adopted for considering forecast errors in load, variable renewable generation, and market prices. The microgrid islanding is further treated as a source of uncertainty. The microgrid planning problem is decomposed into an investment master problem and an operation subproblem. The optimal planning decisions determined in the master problem are employed in the subproblem to examine the optimality of the master solution by calculating the worst-case optimal operation under uncertain conditions. Optimality cuts sent to the master problem will govern subsequent iterations. Numerical simulations exhibit the effectiveness of the proposed model and further analyze the sensitivity of microgrid planning results on variety levels of uncertainty.
The increasing integration of the distributed renewable energy sources highlights the requirement to design various control strategies for microgrids (MGs) and microgrid clusters (MGCs). The multiagent system (MAS)-based distributed coordinated control strategies show the benefits to balance the power and energy, stabilize voltage and frequency, achieve economic and coordinated operation among the MGs and MGCs. However, the complex and diverse combinations of distributed generations (DGs) in MAS increase the complexity of system control and operation. In order to design the optimized configuration and control strategy using MAS, the topology models and mathematic models such as the graph topology model, noncooperative game model, the genetic algorithm, and particle swarm optimization algorithm are summarized. The merits and drawbacks of these control methods are compared. Moreover, since the consensus is a vital problem in the complex dynamical systems, the distributed MAS-based consensus protocols are systematically reviewed. On the other hand, the communication delay issue, which is inevitable no matter in the lowor high-bandwidth communication networks, is crucial to maintain the stability of the MGs and MGCs with fixed and random delays. Various control strategies to compensate the effect of communication delays have been reviewed, such as the neural network-based predictive control, the weighted average predictive control, the gain scheduling scheme, and synchronization schemes based on the multitimer model for the case of fixed communication delay, and the generalized predictive control, networked predictive control, model predictive control, Smith predictor, H∞-based control, sliding mode control for the random communication delay scenarios. Furthermore, various control methods have been summarized to describe switching topologies in MAS with different objectives, such as the plug-in or plug-out of DGs in an MG, and the plug-in or plug-out of MGs in an MGC, and multiagentbased energy coordination and the economic dispatch of the MGC. Finally, the future research directions of the multiagent-based distributed coordinated control and optimization in MGs and MGCs are also presented.
A microgrid (MG) is a local energy system consisting of a number of energy sources (e.g., wind turbine or solar panels among others), energy storage units, and loads that operate connected to the main electrical grid or autonomously. MGs provide flexibility, reduce the main electricity grid dependence, and contribute to changing large centralized production paradigm to local and distributed generation. However, such energy systems require complex management, advanced control, and optimization. Moreover, the power electronics converters have to be used to correct energy conversion and be interconnected through common control structure is necessary. Classical droop control system is often implemented in MG. It allows correct operation of parallel voltage source converters in grid connection, as well as islanded mode of operation. However, it requires complex power management algorithms, especially in islanded MGs, which balance the system and improves reliability. The novel reactive power sharing algorithm is developed, which takes into account the converters parameters as apparent power limit and maximum active power. The developed solution is verified in simulation and compared with other known reactive power control methods.
A new class of microgrids, called provisional microgrids, is introduced in this paper. Provisional microgrids hold similar characteristics as microgrids; however, do not possess the islanding capability and are dependent on one or more electrically connected microgrids for islanding purposes. Removing the islanding requirements and relying on the available unused capacity of existing microgrids characterizes provisional microgrids as enablers of rapidly deploying variable generation renewable energy resources in distribution networks and further preventing underutilization of capital-intensive distributed energy resources in microgrids. Provisional microgrids are defined and an uncertainty-constrained optimal scheduling model is developed, which considers prevailing uncertainties associated with loads, nondispatchable generation, and market price forecasts, as well as islanding incidents and the available unused capacity from coupled microgrids. The optimal scheduling problem is decomposed using Benders decomposition and solved via the robust optimization method. Numerical simulations study a test provisional microgrid for exploring its economic, reliability, and environmental merits.
Microgrids are envisioned as one of the most suitable alternatives for the integration of distributed generation units in the utility grid, as they efficiently combine generation, energy storage and loads in the same distribution network. In this context, hybrid ac/dc microgrids are arising as an interesting approach as they combine the advantages of ac and dc networks and do not require excessive modifications in the distribution network. However, they require more complex control strategies as they need to control the ac and dc networks and the interface power converter simultaneously. This paper identifies and analyses the control strategies that can be implemented in hybrid microgrids for an adequate power management in grid-tied and islanded modes of operation. The review is focused on hierarchical controls as they are the most extended approach in the literature. A classification has been elaborated, which covers the three main levels of hierarchical control strategies (primary, secondary and tertiary). Each of the levels has been independently studied in order to provide a comprehensive analysis of the alternatives found in the literature. The future trends related to this topic show that a higher research effort is required regarding the control of the interface device and the ancillary services that the management strategy must provide—e.g. blackstart, transition between islanded and grid-connected modes of operation, interconnection of microgrids, etc.