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.

Trends in Microgrid Control

The significant benefits associated with microgrids have led to vast efforts to expand their penetration in electric power systems. Although their deployment is rapidly growing, there are still many challenges to efficiently design, control, and operate microgrids when connected to the grid, and also when in islanded mode, where extensive research activities are underway to tackle these issues. It is necessary to have an across-the-board view of the microgrid integration in power systems. This paper presents a review of issues concerning microgrids and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, microgrid operation and control, microgrid clusters, and protection and communications issues.

State of the Art in Research on Microgrids: A Review

The distributed energy resources (DER) comprise several technologies, such as diesel engines, micro turbines, fuel cells, photovoltaic, small wind turbines, etc. The coordinated operation and control of DER together with controllable loads and storage devices, such as flywheels, energy capacitors and batteries are central to the concept of MicroGrid (MG). MG can operate interconnected to the main distribution grid, or in an islanded mode. This paper reviews the researches and studies on MG technology. The operation of MG and the MG in the market environment are also described in the paper.

A review on distributed energy resources and MicroGrid

Dealing with Renewable Energy Resources (RERs) requires sophisticated planning and operation scheduling along with state of art technologies. Among many possible ways for handling RERs, Demand Response (DR) is investigated in the current review. Because of every other year modifications in DR definition and classification announced by Federal Energy Regulatory Commission (FERC), the latest DR definition and classification are scrutinized in the present work. Moreover, a complete benefit and cost assessment of DR is added in the paper. Measurement and evolution methods along with the effects of DR in electricity prices are discussed. Next comes DR literature review of the recent papers majorly published after 2008. Eventually, successful DR implementations, around the world, are analyzed.

Demand response in smart electricity grids equipped with renewable energy sources: A review

In this paper, a generalized formulation for intelligent energy management of a microgrid is proposed using artificial intelligence techniques jointly with linear-programming-based multiobjective optimization. The proposed multiobjective intelligent energy management aims to minimize the operation cost and the environmental impact of a microgrid, taking into account its preoperational variables as future availability of renewable energies and load demand (LD). An artificial neural network ensemble is developed to predict 24-h-ahead photovoltaic generation and 1-h-ahead wind power generation and LD. The proposed machine learning is characterized by enhanced learning model and generalization capability. The efficiency of the microgrid operation strongly depends on the battery scheduling process, which cannot be achieved through conventional optimization formulation. In this paper, a fuzzy logic expert system is used for battery scheduling. The proposed approach can handle uncertainties regarding to the fuzzy environment of the overall microgrid operation and the uncertainty related to the forecasted parameters. The results show considerable minimization on operation cost and emission level compared to literature microgrid energy management approaches based on opportunity charging and Heuristic Flowchart (HF) battery management.

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Multiobjective Intelligent Energy Management for a Microgrid

This paper presents an algorithm to be implemented in a distribution management system (DMS) that is capable of managing an active distribution network (ADN). This goal is achieved by minimizing the cost of system operation, which is expressed in terms of cost of energy losses, cost of curtailed energy, cost of reactive support, and cost of shed energy. Furthermore, the exploitation of network reconfiguration in ADNs is investigated. This paper shows that the coordination of flexible network topology with the continuous active management of energy resources allows improving the efficiency of power delivery. The proposed DMS algorithm allows reducing the risk of energy loss rise, caused by the bigger generation capacity and the deferment of network upgrade that may be a follow-up of ADNs. The proposed method has been applied on a test network to verify the validity of the approach.

Optimal Coordination of Energy Resources With a Two-Stage Online Active Management

Until now, distribution networks are regarded as a passive termination of the transmission network, with a radial structure, unidirectional power flows, and a simple and efficient protection scheme. In presence of a large amount of distributed generation (DG), distribution networks will gradually, but ineluctably, change towards a new kind of active networks. The most revolutionary change, needed to efficiently allocate so much DG, could be represented by the adoption of a meshed network architecture. For this reason, in the paper new possible arrangements for distribution networks have been deeply investigated and compared with the radial scheme. Steady state and dynamic simulations have been performed, considering a portion of the real Italian distribution network, and voltage profile, power losses, short circuit currents and grid reliability have been analyzed.

Meshed vs. radial MV distribution network in presence of large amount of DG

Energy management systems for the operation of distributed energy resources, distribution storage devices, and responsive loads will be embedded in distribution management systems (DMSs) as advanced functions that rely on accurate input data and fast communication signals. For a proper DMS design, the impact of the state estimation uncertainties and of the communication system delays should be evaluated. The paper presents an integrated software package for the cyber-physical simulation of DMS taking into account the accuracy of state estimation and measurements. The effectiveness of a wireless Wi-Max communication system has been tested on the rural Italian representative network produced by the research project ATLANTIDE. Results proved the need of cosimulation packages in modern distribution systems.

DMS Cyber-Physical Simulation for Assessing the Impact of State Estimation and Communication Media in Smart Grid Operation

The interconnection of large amounts of nontraditional generation causes problems in a network designed for 'conventional' operation. A microgrid consists of a combination of generation sources, loads and energy storage interfaced through fast acting power electronics. The aim of operating microgrid sub-systems is to move away from considering DG as badly behaved system components, of which a limited amount can be tolerated in an area, to 'good citizens'. The paper is focused on the development of a novel energy management system (EMS) based on the application of neural networks (NN). The EMS is able to autonomously make decisions and determine hour by hour the correct dispatch of generators with the final goal of minimising the global energy costs. The application of the EMS to a small test case has showed significant saves in the global energy bill by using typical Italian energy and fuel price data

Optimal participation of a microgrid to the energy market with an intelligent EMS

This paper proposes an optimization algorithm that is suitable for choosing the optimal number and position of the measurement devices in distribution state estimation (DSE) procedures used in modern electric distribution networks. The algorithm is based on the techniques of dynamic programming, and its goal is to guarantee both the minimum cost and the accuracy required for the measured data needed to operate management and control issues, such as energy dispatch and protection coordination. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. The aggregation of the quantities to be measured in a few measurement points has been favored to reduce the overall cost of the measurement system. Random changes in the loads are considered to establish adequate reference conditions for the tests. Tests relevant to real distribution networks are presented to show the validity of the proposed approach. The results emphasize how both the influence of the tolerance on the network parameters and the cost of the measurement system can dramatically be minimized by suitably choosing the algorithm to be implemented to solve the DSE problem.

Giuditta Pisano

Papers

Optimal Coordination of Energy Resources With a Two-Stage Online Active Management

Meshed vs. radial MV distribution network in presence of large amount of DG

DMS Cyber-Physical Simulation for Assessing the Impact of State Estimation and Communication Media in Smart Grid Operation

Optimal participation of a microgrid to the energy market with an intelligent EMS

Optimal Allocation of Multichannel Measurement Devices for Distribution State Estimation