The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

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Smart Grid — The New and Improved Power Grid: A Survey

Smart Grid - The New and Improved Power Grid:

This paper presents a comprehensive review and assessment of the latest research and advancement of electric vehicles (EVs) interaction with smart grid portraying the future electric power system model. The concept goal of the smart grid along with the future deployment of the EVs puts forward various challenges in terms of electric grid infrastructure, communication and control. Following an intensive review on advanced smart metering and communication infrastructures, the strategy for integrating the EVs into the electric grid is presented. Various EV smart charging technologies are also extensively examined with the perspective of their potential, impacts and limitations under the vehicle-to-grid (V2G) phenomenon. Moreover, the high penetration of renewable energy sources (wind and photovoltaic solar) is soaring up into the power system. However, their intermittent power output poses different challenges on the planning, operation and control of the power system networks. On the other hand, the deployment of EVs in the energy market can compensate for the fluctuations of the electric grid. In this context, a literature review on the integration of the renewable energy and the latest feasible solution using EVs with the insight of the promising research gap to be covered up are investigated. Furthermore, the feasibility of the smart V2G system is thoroughly discussed. In this paper, the EVs interactions with the smart grid as the future energy system model are extensively discussed and research gap is revealed for the possible solutions.

Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration

The integration of distributed generation (DG) units in power distribution networks has become increasingly important in recent years. The aim of the optimal DG placement (ODGP) is to provide the best locations and sizes of DGs to optimize electrical distribution network operation and planning taking into account DG capacity constraints. Several models and methods have been suggested for the solution of the ODGP problem. This paper presents an overview of the state of the art models and methods applied to the ODGP problem, analyzing and classifying current and future research trends in this field.

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Optimal Distributed Generation Placement in Power Distribution Networks: Models, Methods, and Future Research

This paper investigates the problem of multiple distributed generator (DG units) placement to achieve a high loss reduction in large-scale primary distribution networks. An improved analytical (IA) method is proposed in this paper. This method is based on IA expressions to calculate the optimal size of four different DG types and a methodology to identify the best location for DG allocation. A technique to get the optimal power factor is presented for DG capable of delivering real and reactive power. Moreover, loss sensitivity factor (LSF) and exhaustive load flow (ELF) methods are also introduced. IA method was tested and validated on three distribution test systems with varying sizes and complexity. Results show that IA method is effective as compared with LSF and ELF solutions. Some interesting results are also discussed in this paper.

Multiple Distributed Generator Placement in Primary Distribution Networks for Loss Reduction

It is widely accepted that renewable energy sources are the key to a sustainable energy supply infrastructure since they are both inexhaustible and nonpolluting. A number of renewable energy technologies are now commercially available, the most notable being wind power, photovoltaic, solar thermal systems, biomass, and various forms of hydraulic power. In this paper, a methodology has been proposed for optimally allocating different types of renewable distributed generation (DG) units in the distribution system so as to minimize annual energy loss. The methodology is based on generating a probabilistic generation-load model that combines all possible operating conditions of the renewable DG units with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer nonlinear programming (MINLP), with an objective function for minimizing the system's annual energy losses. The constraints include the voltage limits, the feeders' capacity, the maximum penetration limit, and the discrete size of the available DG units. This proposed technique has been applied to a typical rural distribution system with different scenarios, including all possible combinations of the renewable DG units. The results show that a significant reduction in annual energy losses is achieved for all the proposed scenarios.

Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization

Recently, integration of distributed generation (DG) in distribution systems has increased to high penetration levels. The impact of DG units on the voltage stability margins has become significant. Optimization techniques are tools which can be used to locate and size the DG units in the system, so as to utilize these units optimally within certain limits and constraints. Thus, the impacts of DG units issues, such as voltage stability and voltage profile, can be analyzed effectively. The ultimate goal of this paper is to propose a method of locating and sizing DG units so as to improve the voltage stability margin. The load and renewable DG generation probabilistic nature are considered in this study. The proposed method starts by selecting candidate buses into which to install the DG units on the system, prioritizing buses which are sensitive to voltage profile and thus improve the voltage stability margin. The DG units' placement and sizing is formulated using mixed-integer nonlinear programming, with an objective function of improving the stability margin; the constraints are the system voltage limits, feeders' capacity, and the DG penetration level.

Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation

Environmental concerns and fuel cost uncertainties associated with the use of conventional energy sources have resulted in rapid growth in the amount of wind energy connected to distribution grids. However, based on Ontario's standard offer program (SOP), the utility has the right to curtail (spill) wind energy in order to avoid any violation of the system constraints. This means that any increase in wind energy production over a specific limit might be met with an increase in the wind energy curtailed. In spite of their cost, energy storage systems (ESSs) are considered to be a viable solution to this problem. This paper proposes a methodology for allocating an ESS in a distribution system with a high penetration of wind energy. The ultimate goal is to maximize the benefits for both the DG owner and the utility by sizing the ESS to accommodate all amounts of spilled wind energy and by then allocating it within the system in order to minimize the annual cost of the electricity. In addition, a cost/benefit analysis has been conducted in order to verify the feasibility of installing an ESS from the perspective of both the utility and the DG owner.

Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy

Recent development in small renewable/clean generation technologies such as wind turbines, photovoltaic, fuel cells, microturbines and so on has drawn distribution utilities' attention to possible changes in the distribution system infrastructure and policy by deploying distributed generation (DG) in distribution systems. In this study, a methodology has been proposed for optimally allocating wind-based DG units in the distribution system so as to minimise annual energy loss. The methodology is based on generating a probabilistic generation–load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer non-linear programming (MINLP), with an objective function for the system's annual energy losses minimise. The constraints include voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units. This proposed technique is applied to a typical rural distribution system and compared to the traditional planning technique (constant output power of DG units and constant peak load profile).

Probabilistic approach for optimal allocation of wind-based distributed generation in distribution systems

This paper proposes a method to evaluate the worth of installing renewable distributed generation (DG) in distribution networks. Moreover, the work optimally allocates these DG units in the distribution network to maximize the worth of the connection to the local distribution company (LDC), as well as the customers connected to the system. The proposed methodology helps the LDC to better assess the benefits of the renewable DG units' proposed connections and to identify the optimal buses on which to connect these DG units. The benefits considered in this paper are deferral of upgrade investments, reduction of the cost of energy losses, and reliability improvement, which is represented by the interruption cost reduction. The proposed methodology takes into consideration the uncertainty and variability associated with the output power of renewable DG as well as the load variability. The planning problem of determining the optimal location and sizes of DG units is defined as multi-objective mixed integer programming.

Y.M. Atwa

Papers

Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization

Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation

Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy

Probabilistic approach for optimal allocation of wind-based distributed generation in distribution systems

DG allocation for benefit maximization in distribution networks