Smart Grid Deployment Research Articles

An Innovative Transport Layer Protocol for Smart Grid Communications

The communication technology for power systems a major focus in the development and deployment of smart grid, the SCTP protocol, which was initially designed for transporting signaling messages over IP networks, is now an established in different domain, and lately in Smart Grid communications. SCTP can provide high-performance transmission in both wired and wireless networks. This paper describes different components of smart grid and the smart grid communications layer then we propose a new approach to employ the Stream Control Transmission Protocol (SCTP) in a smart grid, by using the two very significant characteristics offered by SCTP multi-homing and multi-streaming respectively. The simulation results show the comparison between two protocols of the transport layer, TCP and SCTP in terms of the throughput and delay. The simulation works have been conducted in NS2 network simulator.

Grid tie inverter energy stabilizing in smart distribution grid with energy storage

With the growing deployment of smart distribution grid, it has become urgent to investigate the smart distribution grid behavior during transient faults and improve the system stability. The feasibility of segmenting large power grids and multiple smart distribution grids interconnections using energy storage technology for improving the system dynamic stability was studied. The segmentation validity of the large power grids and smart distribution grid inverter output interconnections power system using energy storage technology was proved in terms of theoretical analysis. Then, the influences of the energy storage device location and capacity on the proposed method were discussed in detail. The conclusion is obtained that the ESD optimal locations are allocated at the tie line terminal buses in the interconnected grid, respectively. The effectiveness of the proposed method was verified by simulations in an actual power system.

On Quality of Usage Provisioning for Electricity Scheduling in Microgrids

Microgrid is a promising component for future smart grid deployment. The balance of supply and demand of electricity is one of the most important requirements of microgrid management. In this paper, we investigate the grid stability problem from an admission control perspective, while guaranteeing the quality of usage (QoU) of local residents in a microgrid under both random electricity supply and demand. In particular, a QoU request is generated when the electricity demand exceeds the microgrid supply. The microgrid control center aims to maintain the QoU blocking probability around a target value by serving (i.e., switching to the macrogrid for extra electricity supply) or blocking QoU requests. The problem is formulated as a queue stability problem by introducing the concept of a QoU blocking virtual queue. Lyapunov optimization is then applied to derive an adaptive QoU scheduling algorithm with low complexity ${\cal O}(1)$ . Furthermore, it is an online algorithm since it does not require any future knowledge of the electricity supply and demand processes. The stability of the algorithm is proven, and its performance is evaluated with trace-driven simulations under random or nonstationary QoU requests. The simulation results demonstrate the efficacy and robustness of the proposed QoU scheduling algorithm.

Achieving Accountability in Smart Grid

Smart grid is a promising power infrastructure that is integrated with communication and information technologies. Nevertheless, privacy and security concerns arise simultaneously. Failure to address these issues will hinder the modernization of the existing power system. After critically reviewing the current status of smart grid deployment and its key cyber security concerns, the authors argue that accountability mechanisms should be involved in smart grid designs. We design two separate accountable communication protocols using the proposed architecture with certain reasonable assumptions under both home area network and neighborhood area network. Analysis and simulation results indicate that the design works well, and it may cause all power loads to become accountable.

The impact of scalable routing on lifetime of smart grid communication networks

The paradigm of sensors organized in a multi-hop wireless network has been recognized as a cost effective way to satisfy the real-time sensing and communication needs of a smart grid. For wireless sensor networks, one of the most important design goals is the maximization of network lifetime. Scalability, on the other hand, is also of utmost importance for any given network design problem and especially in a wide area smart grid deployment scenario. Improving scalability requires the network flows to be more localized, however, localizing network operations works against the utilization of some optimal paths required for load balancing and lifetime prolonging. Therefore, lifetime maximization and scalability are two design criteria acting against each other. In this study, a characterization of achievable network lifetime as a function of level of localization of the routing operations under optimal conditions is performed using three localized routing approaches. We build a novel Mixed Integer Programming (MIP) framework with a special emphasis on the details of energy dissipation terms in sensor nodes to model the network behavior correctly. Numerical analysis performed using the developed MIP framework enables us to quantify the impact of different levels of route localization on network lifetime.

Criteria for smart grid deployment in Brazil by applying the Delphi method

The deployment of smart grids has become a global trend in the most diverse electrical systems. This strategy aims to increase the control and efficiency of electrical systems. However, this deployment requires major changes to systems, for example, the information of a telecommunications infrastructure and the provision of adequate equipment, human resources and financial resources. In Brazil, which is territorially large and contains a power distribution system with centralised generation, the deployment of smart grids tends to be time-consuming and could require decades to complete, as well as a large monetary investment. Therefore, the elaboration and implementation of well-defined criteria are necessary for the planning steps of this deployment to minimise the investment cost.This article aims to develop a methodology for selecting electrical systems that will be implemented in smart grids in Brazil by applying the Delphi method based on technical, financial and human resources and environmental applications. This methodology will be used to evaluate electrical systems in their current operating conditions. The results obtained in this research are the creation of a priority factor to determine the order of Smart grid deployment to achieve the best cost benefit in electrical systems evaluated.

Role of residential demand response in modern electricity markets

Electricity generation must match the demand at each instant, following seasonal patterns and instantaneous fluctuations. Thus, one of the biggest drivers of costs and capacity requirements is the electricity demand that occurs during peak periods. This paper reviews market-related problems of modern electric grids and possible solutions to address them. In particular, one techno-economical solution, namely residential demand response programs enabled by a smart grid, is analyzed and modeled in detail. The implications of this solution from both economic and policy perspectives are discussed. The analysis results in several insights: first a local optimum does not generally lead to a global optimum, especially for complex markets; second, in this approach, there exists a disconnection between the locus of the problem (electric utilities) and the locus of the solution (change of demand); third, any techno-economic solution must be carefully designed and global impact should be evaluated to ensure that the final objective is achieved; and fourth, two-way communication is an essential requirement for the successful deployment of smart grids.

Development of a Smart Grid Roadmap for Kentucky

Thanks to the various benefits promised by the smart grid, many utilities are considering deployment of smart grid technologies. For such cross-organizational projects to be successful, a concerted effort is needed, requiring a careful roadmap to be developed. However, there is a lack of methodical process in the current literature for describing the development of smart grid deployment roadmaps. This article presents the results of a recently completed project aimed at developing a comprehensive smart grid roadmap for the state of Kentucky, including the methods and processes utilized and the achieved roadmap plan. The project results may benefit roadmap development and smart grid deployment efforts in other states.

The “Smart Paradox”: Stimulate the deployment of smart grids with effective regulatory instruments

The concept of SG (Smart Grids) encompasses a set of technologies that raise the intelligence of the electrical networks, such as smart meters or instruments of communication, sensing and auto-correction of networks. Nevertheless, the cost is still an important obstacle for the transformation of the current electricity system into a smarter one. Regulation can have an important role in setting up a favorable framework that fosters investments. However, the novelty with SG is the disembodied character of the technology, which may change the incentives of the regulated network companies to invest, affecting the effectiveness of the regulatory instruments (“cost plus” or “price cap”). This paper demonstrates that the solution to this “Smart” paradox requires strong incentive regulation mechanisms able to stimulate the adoption of SG technologies. Moreover, the regulation should not jeopardize conventional investments that are unable to be substituted by SG. Thus, a combination of performance regulation and efficiency obligations may be necessary.

Predictive Electricity Cost Minimization Through Energy Buffering in Data Centers

More and more cloud computing services are handled by different Internet operators in distributed Internet data centers (IDCs), which incurs massive electricity costs. Today, the power usage of data centers contributes to more than 1.5% market share of electricity consumption across the United States. Minimization of these costs benefits cloud computing operators, and attracts increasing attentions from many research groups and industrial sectors. Along with the deployment of smart grid, the electrical real-time pricing policy promotes power consumers to adaptively schedule their electricity utilization for lower operational costs. This paper proposes a novel approach to enable electrical energy buffering in batteries to predictively minimize IDC electricity costs in smart grid. Batteries are charged when electricity price is low and discharged to power servers when electricity price is high. A power management controller is used per battery to arbitrate the charging and discharging actions of the battery. The controller is designed as a MPC-based (model predictive control) controller. To this end, an MPC power minimization problem is formulated based on a discrete state-space model with states of battery power level and cost. Extensive simulation results demonstrate the effectiveness of our approach based on real-life electricity prices in smart grid.

Adaptive Electricity Scheduling in Microgrids

Microgrid (MG) is a promising component for future smart grid (SG) deployment. The balance of supply and demand of electric energy is one of the most important requirements of MG management. In this paper, we present a novel framework for smart energy management based on the concept of quality-of-service in electricity (QoSE). Specifically, the resident electricity demand is classified into basic usage and quality usage. The basic usage is always guaranteed by the MG, while the quality usage is controlled based on the MG state. The microgrid control center (MGCC) aims to minimize the MG operation cost and maintain the outage probability of quality usage, i.e., QoSE, below a target value, by scheduling electricity among renewable energy resources, energy storage systems, and macrogrid. The problem is formulated as a constrained stochastic programming problem. The Lyapunov optimization technique is then applied to derive an adaptive electricity scheduling algorithm by introducing the QoSE virtual queues and energy storage virtual queues. The proposed algorithm is an online algorithm. We derive several “hard” performance bounds for the proposed algorithm, and evaluate its performance with trace-driven simulations. The simulation results demonstrate the efficacy of the proposed electricity scheduling algorithm.

Experimental and data collection methods for a large-scale smart grid deployment: Methods and first results

This paper has two objectives: 1) to describe the experimental and data collection methods for a large-scale smart grid deployment in Austin, Texas, and 2) to provide results based on those data. As of October 2012, the test bed was comprised of 1) 250 homes concentrated in a single neighborhood all built after 2007, and 2) 160 homes distributed throughout Austin with ages ranging from 10 to 92 years old. This experiment includes 200 electric monitoring systems (15-s resolution), 211 electric monitoring systems (1-min), 182 gas meters (2-cubic foot), and 51 water meters (1 gallon) and many of the monitored homes also have energy audits and homeowner surveys. The test bed also includes 185 rooftop PV (photovoltaic) installations and 50 electric vehicles in the same neighborhood. Data streams were automated and gathered at a supercomputing facility at UT-Austin yielding 250 GB (2.95 × 109 records) of data in the first year. This paper describes the baseline study and monitoring methods, characterizes the study participants, and provides some first results about residential energy use. These results include a negative correlation between energy use and knowledge about energy as well as a possible positive correlation between energy use and some rebates.

A device-level service-oriented middleware platform for self-manageable DC microgrid applications utilizing semantic-enabled distributed energy resources

Dynamic and adaptable integration of Distributed Energy Resources (DERs) into novel power system assets, such as microgrids, is one of the key prerequisites for accelerated Smart Grid deployment. By using standardized network interfaces and semantic descriptions for remotely controllable DERs, it is possible to develop intelligent microgrid applications capable of dealing with dynamic loads and intermittent DER power production. IEC 61850 standard has been accepted as one of the prime movers of successful and interoperable Smart Grid communication and integration. Although primarily being applied to the substation automation, IEC 61850 now provides semantic definitions for DER devices allowing it to be applied to expert microgrid application development. The current IEC 61850 middleware definition cannot cope with certain Smart Grid requirements such as support for autonomous microgrid applications with DER plug-and-play capability. These issues could be solved by integrating the device-level Service Oriented Architecture (SOA) paradigm into IEC 61850 applications. Developing a device-level SOA middleware platform based on IEC 61850 principles could significantly facilitate standards-compliant DER integration and accelerate microgrid deployment. A new middleware platform for microgrid applications is proposed. It is based on integrating device-level SOA design principles into IEC 61850 applications in order to fulfil dynamic microgrid management requirements.

The role of the state in sustainable energy transitions: A case study of large smart grid demonstration projects in Japan

Smart grids represent one of the most significant evolutionary changes in energy management systems as they enable decentralised energy systems, the use of large-scale renewable energy as well as major improvements in demand-side-management. Japan is one of the pioneers in smart grid deployment. The Japanese model is characterised by a government-led, community-oriented, and business-driven approach with the launch of four large-scale smart-community demonstration projects. Our case study of large smart grid demonstration projects in Japan found that the Japanese government has demonstrated its high governing capacity in terms of leadership, recombinative capacity, institutional capacity, enabling capacity, and inducement capacity. However, the major limitations of the government in introducing some critical regulatory changes have constrained the smart grid deployment from advancing to a higher-order form of smart grid developments. This paper calls for more attention to be given to the importance of regulatory changes that are essential to overcome the technological lock-in, and the complementary roles of non-state actors such as the business sector and consumers to strengthen the governing capacity of the state.

Worldwide Smart Grid Progress and Trends of China

The development of smart grid is essential to achieve goals for energy security, economic development and climate change mitigation, and is treated as emphasis of national strategy in major countries. In this paper, we described the concept of smart grid first, then analyzed the worldwide progress in strategic planning, R&D and deployment of smart grid. Combining with Chinese situation, the future smart grid R&D will focus on: intelligent power electronics equipments, intelligent sensing technologies, renewable integration technologies, energy storage technologies and distributed energy technologies.

Candidate solutions to improve Wireless Mesh Networks WMNs performance to meet the needs of Smart Grid applications - Survey paper

market share of existing Smart Grid network installations is wireless mesh networks ( 1). The paper starts by justifying the selection of WMNs as opposed to any other communication techn ology based on quantifying the bandwidth/latency/QoS constraints of a number of Smart Grid applications. The main objective of this paper, however, is to discuss some optimization techniques that found in the literature and can be implemented to overcomesome of the challenges currently being faced by WM Ns deployment in Smart Grid's NANs. Hybrid WMN (HWMN) is proposed as an optimization on the topology level to leverage WMNs convergence. Distributed Autonomous Data Routing DADR, multigate and diversity routing are optimizations on the protocol level to minimize the down time of WMNs. Cognitive Radio is investigated as an optimization on the physical level . The paper also explores the feasibility of using Wireless Software DefinedNetworks WSDN to improve the overall visibility and manageability of WMNs.

Potential carbon impacts of smart grid development in six European countries

This paper examines reports on work carried out for the European Commission to devise a methodology for estimating the potential impact of smart grids on carbon emissions. It first identifies functionalities that enable carbon benefits to be realised. Each functionality on the demand side is assumed to be mirrored on the supply side, as when dynamic peak shifting ‘replaces’ flexible peak generation. Metrics are developed to describe the state of markets and to estimate customer response to demand response initiatives. Quantitative analysis identifies where the greatest scope for emissions reduction lies, while qualitative assessment indicates where to expect more or less impact from smart grid deployment. The impact of smart grid functionalities by 2020 is then modelled for six representative EU markets (Austria, France, Germany, Great Britain, Portugal and Spain), using a detailed pan-European market model and also a high-level ancillary services model. Three scenarios are developed: baseline, in which no smart grid rollout is assumed; feasible, based on what could be achievable in the light of technology developments and with supportive legislation; and an intermediate expected scenario, in which new technologies are introduced but nothing else changes. The findings indicate the potential for emissions reductions by 2020. They also show that the potential is very unlikely to be reached without regulatory support for user engagement in demand response and demand reduction, along with enabling technology and programmes. Development of regulatory frameworks that allow full advantage to be taken of the new technologies emerges as a challenge for smart grid development.

Towards Implementation of Smart Grid: An Updated Review on Electrical Energy Storage Systems

A smart grid will require, to greater or lesser degrees, advanced tools for planning and operation, broadly accepted communications platforms, smart sensors and controls, and real-time pricing. The smart grid has been described as something of an ecosystem with constantly communication, proactive, and virtually self-aware. The use of smart grid has a lot of economical and environmental advantages; however it has a downside of instability and unpredictability introduced by distributed generation (DG) from renewable energy into the public electric systems. Variable energies such as solar and wind power have a lack of stability and to avoid short-term fluctuations in power supplied to the grid, a local storage subsystem could be used to provide higher quality and stability in the fed energy. Energy storage systems (ESSs) would be a facilitator of smart grid deployment and a “small amount” of storage would have a “great impact” on the future power grid. The smart grid, with its various superior communications and control features, would make it possible to integrate the potential application of widely dispersed battery storage systems as well other ESSs. This work deals with a detailed updated review on available ESSs applications in future smart power grids. It also highlights latest projects carried out on different ESSs throughout all around the world.

Privacy-enhanced architecture for smart metering

The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values.

A survey on security issues in smart grids

AbstractA key feature of the smart grid is the introduction of two‐way data communications into the power grid. This brings many security challenges, because of the large‐scale, difficult‐to‐secure environment, complexity of smart grid systems, and resource limitations of the smart grid deployments. In this paper, we focus on security and privacy concerns in the context of the smart grid. Existing security mechanisms developed for traditional information technology systems can be used as a basis for designing security measures for the smart grid. However, new methods that meet the special requirements and characteristics of the smart grid are also required. In spite of the obstacles against developing detailed security solutions for the future smart grid, such as uncertainty of the architecture and lack of practical experiences with security attacks, some research has been performed in this area over the last few years. We survey the existing literature on different security aspects of the smart grid and provide directions for further research. Copyright © 2012 John Wiley & Sons, Ltd.