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 smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.

A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms

This paper proposes a novel control strategy for coordinated operation of networked microgrids (MGs) in a distribution system. The distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize the operation costs. It is assumed that both the dispatchable and nondispatchable distributed generators (DGs) exist in the networked MGs. In order to achieve the equilibrium among all entities and take into account the uncertainties of DG outputs, we formulate the problem as a stochastic bi-level problem with the DNO in the upper level and MGs in the lower level. Each level consists of two stages. The first stage is to determine base generation setpoints based on the load and nondispatchable DG output forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. A scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Case studies of a distribution system with multiple MGs of different types demonstrate the effectiveness of the proposed methodology. The centralized control, deterministic formulation, and stochastic formulation are also compared.

Coordinated Energy Management of Networked Microgrids in Distribution Systems

This paper proposes a transformative architecture for the normal operation and self-healing of networked microgrids (MGs). MGs can support and interchange electricity with each other in the proposed infrastructure. The networked MGs are connected by a physical common bus and a designed two-layer cyber communication network. The lower layer is within each MG where the energy management system (EMS) schedules the MG operation; the upper layer links a number of EMSs for global optimization and communication. In the normal operation mode, the objective is to schedule dispatchable distributed generators (DGs), energy storage systems (ESs), and controllable loads to minimize the operation costs and maximize the supply adequacy of each MG. When a generation deficiency or fault happens in an MG, the model switches to the self-healing mode and the local generation capacities of other MGs can be used to support the on-emergency portion of the system. A consensus algorithm is used to distribute portions of the desired power support to each individual MG in a decentralized way. The allocated portion corresponds to each MG’s local power exchange target, which is used by its EMS to perform the optimal schedule. The resultant aggregated power output of networked MGs will be used to provide the requested power support. Test cases demonstrate the effectiveness of the proposed methodology.

Networked Microgrids for Self-Healing Power Systems

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Power management and power flow control with back-to-back converters in a utility connected microgrid

Smart grid initiatives are becoming more and more achievable through the use of information infrastructures that feature peer-to-peer communication, monitoring, protection and automated control. The analysis of smart grid operation requires considering the reliability of the cyber network as it is neither invulnerable nor failure free. This paper quantitatively evaluates the reliability of modern power systems, which incorporates the impact of cyber network failures on the reliability of the power network. In this paper, four types of interdependencies are defined and a new concept of state mapping is proposed to map the failures in the cyber network to the failures of the power network. Furthermore, in order to evaluate the impact of direct cyber-power interdependencies on the reliability indices, two optimization models are introduced to maximize the data connection in the cyber network and minimize the load shedding in the power network. The effectiveness of proposed reliability evaluation method is shown by a smart microgrid application. The methodology presented in this paper is a start point to optimize the future power grid which has increasingly interdependencies between cyber and power networks.

Reliability Assessment of Smart Grid Considering Direct Cyber-Power Interdependencies

The operation of power systems now relies on extensive applications of digital communication systems, known as cyber networks. These applications are categorized as having either direct or indirect interactions between cyber and power networks. We previously studied direct interdependencies inside cyber-power networks and proposed the state mapping based model to evaluate its impact on the power system reliability. This paper focuses on indirect interdependencies between cyber and power networks. Certain applications of indirect interdependencies in modern power systems are discussed, and a state updating-based model is proposed to quantitatively evaluate the reliability of cyber-power networks under indirect interdependencies. Two optimization models are used to maximize the data connectivity in the cyber network and minimize the load curtailment in the power network. A high-voltage substation equipped with both monitoring and protection systems is studied to show the effectiveness of the proposed solution model.

Reliability Assessment of Smart Grids Considering Indirect Cyber-Power Interdependencies

Demand response (DR) is a market driven and sometimes semi-emergency action performed at the utility level or at the Demand Response Service Provider (aggregator) with the objective of reducing the overall demand of the system during peak load hours. If implemented successfully, DR helps postpone the capacity expansion projects related to the distribution network, and provides a collaborative framework for the liberalized energy market of the Smart Grid. Customers subscribed to the DR program are requested to reduce their demand or turn off one or more energy consuming appliances in exchange for financial incentives such as extra payments or discounted electricity rates. This would change the concept of distribution system reliability as is traditionally known. From one hand, DR could lead to a higher amount of unserved energy; on the other hand, it does not qualify as an unwanted lost load. This paper tries to provide a qualitative analysis on the impact of demand response on distribution system reliability.

Impact of demand response on distribution system reliability

Smart grid technologies leveraging advancements in sensors, communications, and computing offer new avenues for reliability enhancements of complex power grids by increasing the up-times and reducing the down times. This paper discusses various aspects of smart grid monitoring and proposes a mathematical model to assess its impact on power grid reliability. Based on a multiple-state Markov chain model, the failure and repair rates of power components with and without monitoring provisions are determined and compared. The proposed formulation incorporates the failure rates of the monitoring systems themselves and the impact on system/component reliability.

Reliability Modeling and Evaluation of Power Systems With Smart Monitoring

This paper presents a decentralized solution algorithm for network-constrained unit commitment (NCUC) in multiregional power systems. The proposed algorithm is based on our previous work in which a local NCUC was formulated for each control entity (i.e., region) and an analytical target cascading (ATC) based distributed but partially parallelized algorithm requiring a central coordinator was presented. The primary objective of this paper is to present a decentralized approach that relaxes the need for any form of central coordinator in ATC and allows fully parallelized solutions of the local NCUCs. To achieve this objective, we formulate a bilevel optimization problem for each control entity. While the upper level solves the NCUC problem of the control entity, the lower level seeks to coordinate the control entity with its neighboring regions. The lower level is a convex optimization, which can be further replaced in the upper level problem by the Karush–Kuhn–Tucker conditions. The control entities communicate directly with each other and synchronously solve their local NCUCs. Having no need for any form of central coordinator, the proposed algorithm is potentially less vulnerable to cyber-attacks and communication failures than the distributed methods utilizing a coordinator.

Bamdad Falahati

Papers

Reliability Assessment of Smart Grid Considering Direct Cyber-Power Interdependencies

Reliability Assessment of Smart Grids Considering Indirect Cyber-Power Interdependencies

Impact of demand response on distribution system reliability

Reliability Modeling and Evaluation of Power Systems With Smart Monitoring

Decentralized Implementation of Unit Commitment With Analytical Target Cascading: A Parallel Approach