“IEEE Vision for Smart Grid Communications: 2030 and Beyond,” S. Goel, S. F. Bush and D. E. Bakken (Editors), IEEE Press, May 2013, E-ISBN: 978-0-7381-8460-9.

S. F. Bush, S. Goel and G. Simard, “IEEE Vision for Smart Grid Communications: 2030 and Beyond Reference Model,” IEEE Press,September 2013, E-ISBN: 978-0-7381-8833-1.

S. F. Bush, S. Goel and G. Simard, “IEEE Vision for Smart Grid Communications: 2030 and Beyond Roadmap,”IEEE Press, March 2013, September 2013, E-ISBN: 978-0-7381-8646-7.

These are three interconnected documents that formpart of the same project covering the future of the smart grid. They provide a vision of the future and indicate a path to reach the goals of the smart grid. The first document is a book by a team of well-known experts from around the globe who are working on different technologies that are integral to the success of the smart grid. The two other documents, reference model and roadmap, are accompanying documents. The IEEE Vision for Smart Grid Communications: 2030 and Beyond Reference Model directly overlays events in the power grid with communication performance on the same mathematical space-time model ensuring a perspective that verifies whether any of the myriad of communication technologies chosen will provide the required support for the smart grid. The IEEE Vision for Smart Grid Communications: 2030 and Beyond Roadmap derives basic communication principles for the power grid and then utilizes these to drive a vision for the future power grid that extends beyond 2030. The fundamental research required to achieve the vision is broken down into specific time periods so that funding agencies and industry can use the roadmap to help determine a research strategy for the next several decades.

”Electric Power Substations Engineering,”John D. McDonald (Editor). Series: Electrical Engineering Handbook, CRC Press, May 2012, ISBN 978-1-4398-5638-3.

Modern electric power systems have been dubbed “the largest machine made by mankind” because they are both physically large and operate in precise synchronism. Keeping such a large machine from breaking apart is not trivial. Substation communication plays a vital role in power system operation. This bookprovides a brief historical overview of substation communication followed by sections that review functional and communication requirements; examines components of both traditional and emerging supervisory control and data acquisition systems; reviews the characteristics of past, present, and future substation communication protocols; reviews the role of standards for substation communication; discusses the electromagnetic environment which substation communication devices must withstand; discusses security aspects of substation communications; and discusses communication media options for substation communications.

M. Adamiak and M. A. Redfern, “Relay Communications,”Chapter 9 of the IEEE Tutorial Course “Advancements in Microprocessor Based Protection and Communications,” IEEE publication 97TP120-0, January 1997.

Communication has been used for decades to enhance the performance of power system protection schemes. In normal power system operation a variety of communication links are used to provide data transfer. Digital relays and other intelligent electronic devices communicate and providewarning of failure and malfunction, such that these conditions can be detected and fixed before there is failure to operate. This tutorial explores the basics of digital communication as applied to digital relays, including the standard communication model, communication media, modulation techniques, asynchronous and synchronous communications, protocols, error detection, and concludes with a glimpse of the future of relay communications.

K. Tomsovic, D. Bakken, V. Venkatasubramanian and A. Bose, ”Designing the Next Generation of Real-Time Control, Communication and Computations for Large Power Systems,” Proceedings of the IEEE, Vol. 93, No. 5, May 2005, pp. 965-979.

This paper provides a comprehensive introduction tothe major aspects of control, communication, and computation of the smart grid. The major principles of design as well as typical practical systems are explained.

D.Yergin, ”The Quest: Energy, Security, and the Remaking of the Modern World,” Penguin Books, September 2012, ISBN 978-0-1431-2194-7.

This book by Pulitzer Prize-winning author Daniel Yerginprovides an overview of the geopolitical landscape of energy in our modern world, which is useful in understanding the needs and motivation for the smart grid.

S. Galli, A. Scaglione and Z. Wang, ”For the Grid and Through the Grid: The Role of Power Line Communications in the Smart Grid,” Proceedings of the IEEE, vol. 99, no. 6, June 2011, pp. 998-1027.

This paper is the most comprehensive and readable survey on the subject matter. It contains a wealth of historical information on the evolution of PLC since its early days and describes the most recent technological advances in the area. It addresses smart grid applications as instances of sensor networking and network control and critically analyzes the application scenario of PLC within the smart grid. The paper is appealing to a broad range of readers, from the reader generally interested in the promise of PLC for the future of the smart grid to the technology expert. It is a thorough reference of what is known about modeling the power line channel today and a must-read for anybody who would like to know about, or is working on, PLC for the smart grid.

W. Meng, R. Ma and H.-H. Chen, ”Smart Grid Neighborhood Area Networks: A Survey,” IEEE Network, vol. 28, no. 1, January/February 2014, pp. 24-32. 

The paper presents a review of a neighborhood area-network (NAN) design and discusses the last mile communication problems in a smart grid environment. The focus is on the use of wireless networking standards in NANs, particularly IEEE 802.15.4g and IEEE 802.11s, dealing with the implementation issues of network topology, gateway deployment, routing algorithms, and security. The paper also provides an overview of RPL (Routing Protocol for Low-Power and Lossy Networks) techniques for smart grid applications.

Y. Ye, Q. Yi, H. Sharif, and D. Tipper, ”A Survey on Smart Grid Communication Infrastructures: Motivations, Requirements and Challenges,” IEEE Communications Surveys & Tutorials, vol. 15, no. 1, First Quarter 2013, pp. 5-20. 

This recent survey starts with a presentation of the background and motivation for implementation of communication infrastructure within the power grid. Smart grid services and applications such as smart metering, distributed energy resources, as well as monitoring and control are assessed from the perspective of the communication network architecture, identifying challenges, requirements and benefits of their deployment. The survey also presents several relevant industrial trials ofsmart grid with communication infrastructures.

H. Liang, B. J. Choi, A. Abdrabou, W. Zhuang, and X. Shen, ”Decentralized Economic Dispatch in Microgrids via Heterogeneous Wireless Networks,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 6, July 2012, pp. 1061-1074.

This paper presents a good overview of the economic dispatch problem in the microgrid motivating the use of a communication infrastructure for its solution. The authors propose the use of short-range, wireless technologies for the exchange of loads and generator capacities within the microgrid and assess the application of the distributed consensus algorithm for finding the optimal solution of economic dispatch, including the communication costs and impairments in the overall cost model. In the next step, the authors complement the proposed solution with cellular network support, showing that limited use of cellular links can reducethe total operation cost of the microgrid. Another strong point is that the results are based on real-world data.

M. Erol-Kantarci and H. T. Moufath, ”Wireless Sensor Networks for Cost Efficient Residential Energy Management in Smart Grid,” IEEE Transactions on Smart Grid, vol. 2, no.2, June 2011, pp. 314-325. 

This paper discusses and reviews home energy management techniques, whose aim is an efficient demand/supply balance and reduction of electricity expenses and carbon emissions. Different load types are considered, including electric vehicles. The authors propose use of wireless sensor home area network as a low-power communication infrastructure for residential energy management. The paper provides a performance comparison of home energy management systems using IEEE802.15.4 based networked systems.

H. Farhangi, ”The Path of the Smart Grid,” IEEE Power and Energy Magazine, vol. 8, no. 1, January/February 2010, pp. 18-28. 

This paper discusses the evolution of the existing grid to a smart grid and the associated drivers, technologies, standards, research, development, and demonstration. It conveys a clear vision to the reader that, “regardless of how quickly various utilities embrace smart grid concepts, technologies, and systems, they all agree on the inevitability of this massive transformation.”

Y. Liu, P. Ning, and M. K. Reiter, ”False Data Injection Attacks against State Estimation in Electric Power Grids,” ACM Transactions on Information and System Security, Article No. 13, vol. 14, no. 1, May 2011, pp. 21-32.

This paper introduces the new class of false data injection attacks, which are targeted towards state estimation tasks in power systems. The paper presents attack vector designs that have the following features: 1) the presence of an attack vector cannot be detected by classical bad data detectors, and 2) arbitrary errors on the state estimate are inflicted. The authors show how the attacker can systematically and efficiently construct attack vectors in two realistic scenarios.

O. Kosut, L. Jia, R. J. Thomas, and L. Tong, ”Malicious Data Attacks on the Smart Grid,” IEEE Transactions on Smart Grid, vol. 2, no. 4, December 2011, pp. 645-658. 

The paper investigates malicious attacks against power systems, in which an adversary controls a set of meters and is able to alter the measurements from those meters. Two attack regimes are defined, strong and weak, respectively. Taking the perspective of the adversary, the trade-off between maximizing estimation error at the control center and minimizing detection probability of the launched attack is examined. Finally, the paper proposes an optimal attack based on minimum energy leakage.

F. Pasqualetti, F. Dorfler, and F. Bullo, ”Attack Detection and Identification in Cyber-Physical Systems,” IEEE Transactions on Automatic Control, vol.58, no. 11, November 2013, pp.2715-2729.

The paper develops a general framework for attack detection in cyber-physical systems modeled by linear dynamical equations.  The paper considers attacks that alter the (time-varying) system state as well as the system output measurements. The framework is quite general, subsuming previous attack models, such as false data injection attacks on the linear measurement model. Building upon this framework, conditions for the detection and identification of attacks are derived, while centralized and distributed monitoring strategies are developed. Ample numerical tests are provided. 

D. Bakken, A. Bose, C. Hauser, D. Whitehead, and G. Zweigle, ”Smart Generation and Transmission with Coherent Real-Time Data,” Proceedings of the IEEE, vol. 99, no. 6, June 2011, pp. 928-951. 

This paper introduces a well-recognized communication framework for the synchronous data delivery, GridStat, which provides an important infrastructure to study the cyber security and privacy in the context of the smart grid.

V.C. Gungor, B. Lu, and G.P. Hancke, ”Opportunities and Challenges of Wireless Sensor Networks in Smart Grid,” IEEE Transactions on Industrial Electronics, vol. 57, no. 10, October 2010, pp. 3557-3564.

The paper provides an overview of the application of wireless sensor networks for the smart grid, describing opportunities and challenges. The paper also includes an experimental study on the statistical characterization of the relevant wireless channel based on field tests performed on IEEE 802.15.4-compliant wireless sensor nodes. The paper brings a range of possible applications of wireless sensor networks in the smart grid, identifies research gaps and proposes future research directions. The experimental study brings valuable insights into performance and implementation issues of the IEEE 802.15.4-based sensor network deployment in different electric power systems. It is a good starting point for studying and designing wireless sensor networks for the smart grid.

Y.-J. Kim, M. Thottan, V. Kolesnikov, and W. Lee, ”A Secure Decentralized Data-Centric Information Infrastructure for Smart Grid,” IEEE Communications Magazine, vol. 48, no. 11, November 2010, pp.58-65. 

The article proposes an IP (Internet Protocol)-based, data-centric information infrastructure, i.e., middleware, for smart grid networks. The proposed infrastructure is decentralized, secure, and supports distributed data sources, self-healing and self-configurability. The paper brings a nice survey of commonly used data transport protocols for smart grid applications. It provides an outline of decentralized data-centric information infrastructure for power generation, transmission, distribution, and consumption. It addresses security and practical implementation issues, and it is a comprehensive reference for everyone studying and researching communication and networking in the smart grid.

T. Sauter and M. Lobashov, ”End-to-end Communication Architecture for Smart Grids,” IEEE Transactions on Industrial Electronics, vol. 58, no. 4, April 2011, pp. 1218-1228. 

This paper describes a two-tier heterogeneous network infrastructure for smart grids, consisting of IP-based and suitable field-level networks. Particular attention is paid to the metering and supervisory control applications. The feasibility of the proposed approach is demonstrated using power-line communication networks. This is a well-written and presented paper, a good reference for heterogeneous networking for data acquisition and metering in smart grid networks. Though the paper studies power-line communications in detail, the proposed modifications at the transport layer for network integration are generic.

J. M. Guerrero, M. Chandorkar, T. Lee, and P. C. Loh, ”Advanced Control Architectures for Intelligent Microgrids—Part I: Decentralized and Hierarchical Control,” IEEE Transactions on Industrial Electronics, vol.60, no.4, April 2013, pp. 1254-1262.

J. M. Guerrero, P. C. Loh, T. Lee and M. Chandorkar, ”Advanced Control Architectures for Intelligent Microgrids—Part II: Power Quality, Energy Storage, and AC/DC Microgrids,” IEEE Transactions on Industrial Electronics, vol.60, no.4, April 2013, pp.1263-1270.

This is a two-part paper, presenting a review of advanced control techniques for microgrid operation. The focus of the first part is on the decentralized and hierarchical control and the methods to analyze and assess the microgrid stability, both for the islanded and grid-connected modes of operation. The second part deals with specific microgrid aspects, like power quality, distributed energy storage and control of AC/DC microgrids. Overall, the paper motivates the use of communication systems in order to implement distributed multiagent control of microgrids, outlining the important issues from the control perspective that should be facilitated by the underlying communication infrastructure.

F. Katiraei, M. R. Iravani and P. W. Lehn, ”Micro-Grid Autonomous Operation During and Subsequent to Islanding Process,” IEEE Transactions on Power Delivery, vol. 20, no. 1, January 2005, pp. 248-257. 

This is one of the most cited articles in the field of microgrid operations. The paper investigates the formation of a microgrid through islanding of a distribution subsystem either due to preplanned switching or due to fault events. The main conclusion of the paper is that the presence of an electronically-interfaced DG (Distributed Generation) unit makes the concept of micro-grid a technically viable option.

C. W. Gellings, ”The Smart Grid: Enabling Energy Efficiency and Demand Response,” CRC Press, 2009, ISBN 978-1-4398-1574-8.

The book was written by an expert in the field and a former Vice-President of the Electric Power Research Institute (EPRI). The book is an insider's guide to how the power grid operates and what is needed to transition to a smart grid.

C.-L. Su and D. Kirschen, ”Quantifying the Effect of Demand Response on Electricity Markets,” IEEE Transactions on Power Systems, vol. 24, no. 3, August 2009, pp. 1199-1207. 

This paper introduces a way to regulate demand/response using a centralized bidding system. This centralized complex-bid market-clearing mechanism takes into account the load shifting behavior of consumers who submit price-sensitive bids. The paper provides a variety of simulation results that show how price outcomes relate to demand response elasticity. This is in contrast to most studies on price-responsive demand which assume loads are price takers. The aim of the paper is to provide concrete examples of the effect of large participation of deferrable load in the market.The paper is often cited to justify DR (Demand Response).

F. Rahimi, and A. Ipakchi, ”Demand Response as a Market Resource under the Smart Grid Paradigm,”IEEE Transactions on Smart Grid, vol. 1, no. 1, June 2010, pp. 82-88. 

Readers who are interested in research on Demand-Response (DR) can gain insight from this well-written paper. It summarizes existing and evolving programs and market designs in different Whole-Sale Electricity Market ISOs/RTOs (independent system operators/ regional transmission organizations) aimed at the participation of DR Aggregators. The paper also describes the challenges of implementing such a system.

A. J. Conejo, J. M. Morales, and L.Baringo, ”Real-Time Demand Response Model,” IEEE Transactions on Smart Grid, vol. 1, no. 3, December 2010, pp. 236-242. 

This is a widely cited early paper introducing a Home Energy Management Systems (HEMS) optimization model. In this model, the customers receive dynamic prices and can use the proposed model to adjust the hourly load level of a given consumer in response to hourly electricity prices. The paper discusses how to use robust optimization to cope with price uncertainty and how to maximize the utility of the consumers, subject to constraints on a minimum daily energy-consumption level, maximum and minimum hourly load levels, and ramping limits on such load levels. Bidirectional communication between the power supplier and the consumer is instrumental for the model used in the paper.

R. Malhamé and C.-Y. Chong, ”Electric Load Model Synthesis by Diffusion Approximation of a High-Order Hybrid-State Stochastic System”, IEEE Transactions on Automatic Control, vol. 30, no. 9, 1985, pp. 854-860. 

This article develops a statistical approach to modeling the dynamics of aggregations of homogenous thermostatic loads, which is challenging because each load is best described (individually) as a hybrid-state stochastic system. The aggregate system is innovatively modeled with coupled ordinary and partial differential equations (Fokker-Planck equations). At the time this paper was published, demand response was mainly limited to peak load shedding and so the proposed applications were limited to two: (1) a better understanding of aggregate load behavior and (2) a way to estimate the potential response of loads to load shedding signals. It wasn’t until years later that the full value of this work became clear, specifically, that the models proposed here could be used within real-time feedback control algorithms. In recent years, many researchers have gone back to this work – as a foundation for variety of new approaches.

M. Roozbehani, M. Dahleh, and S. Mitter, ”Volatility of Power Grids Under Real-Time Pricing,” IEEE Transactions on Power Systems, vol. 27, no. 4, November 2012, pp. 1926-1940. 

This work develops methods to model and analyze the dynamics of electricity markets with large amounts of demand response “actuated” by real-time pricing (RTP). This compelling paper is perhaps the first to provide a detailed investigation into the effect of RTP on the dynamics of the full power system. Importantly, it models RTP as a closed loop feedback control signal – which is not typically the way these problems are formulated. This paper is an excellent counterpart to recent papers that advocate RTP as the simplest and best solution for achieving DR. By highlighting the important issues that could arise if RTP were implemented on a large scale, it has spurred significant re-thinking about this type of problems and research into ways to overcome them.

A.-H. Mohsenian-Rad, V. W. S. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, “Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid,”IEEE Transactions on Smart Grid, vol. 1, no. 3, December 2010, pp. 320-331.

This paper presents an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid. This is in contrast to most of the existing demand-side management programs that focus primarily on the interactions between a utility company and its customers/users.  The paper uses a game-theoretic framework and shows that for a common scenario, with a single utility company serving multiple customers, the global optimal performance in terms of minimizing the energy costs is achieved at the Nash equilibrium of the formulated energy consumption scheduling game. It is shown that users will have the incentives to participate in the energy consumption scheduling game and subscribing to such services. As a result, the proposed approach can reduce the peak-to-average ratio of the total energy demand, the total energy costs, as well as each user’s individual daily electricity charges.

D. Callaway, ”Tapping the Energy Storage Potential in Electric Loads to Deliver Load Following and Regulation, with Application to Wind Energy,” Energy Conversion and Management, vol. 50, no. 5,May 2009, pp. 1389-1400. 

The paper presents an exact solution to the coupled Fokker-Planck equations derived in R. Malhamé and C.-Y. Chong, “Electric load model synthesis by diffusion approximation of a high-order hybrid-state stochastic system,” IEEE Transactions on Automatic Control, vol. AC-30, no. 9, pp. 854–860, 1985. It is the first paper to develop load models and control strategies to provide ancillary services via thermostat set point manipulation. This paper has sparked an enormous amount of work including direct extensions of various aspects of the methodology and alternate methodsto handle some of the drawbacks to this initial approach including methods to handle parameter heterogeneity, imprecise thermostats, etc. The paper demonstrates that ancillary services could be effectively provided by aggregations of air conditioners with very small set point manipulations (non-disruptive to the consumer) and only a modest communication system. Much subsequent work has tried to “beat” these results – this paper provides a very nice benchmark.

L.Chen, N. Li, L. Jiang, S. H. Low, ”Optimal Demand Response: Problem Formulation and Deterministic Case,” Chapter in “Control and Optimization Theory for Electric Smart Grids,” A.Chakarabortty and M. Ilic (Editors), Springer, 2011, ISBN 978-1-4614-1605-0. 

This book chapter considers a set of users served by a single load-serving entity (LSE). The LSE procures capacity a day ahead. When random renewable energy is realized at delivery time, it manages user load through real-time demand response and purchases balancing power on the spot market to meet the aggregate demand. Hence, optimal supply procurement by the LSE and the consumption decisions by the users must be coordinated over two timescales, a day ahead and in real time, in the presence of supply uncertainty. Moreover, they must be computed jointly by the LSE and the users since the necessary information is distributed among them. This article presents a simple yet versatile user model and formulates the problem as a dynamic program that maximizes expected social welfare. When random renewable generation is absent, optimal demand response reduces to joint scheduling of the procurement and consumption decisions. In this case, optimal prices exist that coordinate individual user decisions to maximize the social welfare, and present a decentralized algorithm to optimally schedule a day in advance the LSE’s procurement and the users’ consumptions. This paper also provides mathematical models to characterize the use of different residential appliances.

C. Chen, J. Wang, Y. Heo, and S. Kishore, ”MPC-Based Appliance Scheduling for Residential Building Energy Management Controller,” IEEE Transactions on Smart Grid, vol. 4, no. 3, September 2013, pp. 1401-1410. 

This paper proposes a novel appliance scheduling scheme for residential building energy management controllers, by taking advantage of the time-varying retail pricing enabled by the two-way communication infrastructure of the smart grid. Finite-horizon scheduling optimization problems are formulated to exploit operational flexibilities of thermal and non-thermal appliances using a model predictive control (MPC) method which incorporates both forecasts and newly updated information. For thermal appliance scheduling, the thermal mass of the building, which serves as thermal storage, is integrated into the optimization problem by modeling the thermodynamics of rooms in a building as constraints. This paper has very novel ideas and approach on the topic of demand response. Its application to a real building management control is even more significant. Authored by experts from a interdisciplinary area, it provides a comprehensive direction on what demand response system for the future building technology of tomorrow might be. It is a must read for anybody who would like to know about or is working on demand response for the smart grid.

J. Kwac, J. Flora,and R. Rajagopal, ”Household Energy Consumption Segmentation Using Hourly Data,” IEEE Transactions on Smart Grid, vol. 5, no. 1, January 2014, pp. 420-430.

This paper takes a fresh and original look at the data analysis of household electricity consumption profiles. The authors propose a novel approach, decomposing the profiles into a daily total usage and a normalized load shape, and apply it to one of the largest (if not, the largest) electricity consumption data sets ever reported in scientific literature: 220k residential consumers are analyzed and clustered.

G. Chicco, ”Overview and Performance Assessment of the Clustering Methods for Electrical Load Pattern Grouping,” Energy, vol. 42, no. 1, June 2012, pp. 68-80. 

This paper is one of the most complete and accessible surveys to date on the clustering of electrical consumption profile analysis. The problem is clearly introduced, and all stages of a clustering procedure and the sub-problems (including references to bad data detection and elimination) nicely summarized. Moreover, apart from classifying and relating the various clustering approaches to each other qualitatively, and presents a quantitative comparison reporting multiple performance metrics.

L. Hernandez, C. Baladron, J. Aguiar, B. Carro, A. Sanchez-Esguevillas, J. Lloret, and J. Massana, ”A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings,” IEEE Communications Surveys & Tutorials, vol. 16, no. 3, Third Quarter 2014, pp. 1460-1495. 

This is an overview paper on power demand forecasting. It provides a very extensive definition of the various time scales and applications of such forecasting. The basic forecasting techniques are explained in simple terms accessible to a generalist reader. The survey also goes back to the early days, and provides a historical insight of work in this area (with the oldest reference even dating back to 1956). State-of-the-art techniques are insightfully classified in overview pictures and tables. In summary, this is an extremely solid reference work useful both for the researcher active in this area, as well as a more generalist smart grid practitioner.

I. S.Bayram, G. Michailidis, M. Devetsikiotis, and F. Granelli, ”Electric Power Allocation in a Network of Fast Charging Stations,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 7, July 2013, pp. 1235-1246. 

This paper presents a novel framework for charging a network of electrical vehicle (EV) stations and routing EVs to explore the load flexibility of this problem. Three schemes are developed that trade off complexity with performance. Overall, this paper explores a new direction on using data management and analytics for managing future electric vehicle demand at scale.

A.G. Phadke and J.S. Thorp, ”Synchronized Phasor Measurements and Their Applications (Power Electronics and Power Systems),” Springer, 2008, ISBN 978-0-3877-6535-8. 

This book provides a comprehensive introduction on the principles, designs and applications of phasor measurement unit (PMU), which is the important instrument device to collect real-time and fine data for analyzing the status of the power network. It helps to understand how the data is collected and analyzed for monitoring and controlling power networks.

Y. Zhang, P. Markham, T. Xia, L. Chen, Y. Ye, Z. Wu, Z. Yuan,L. Wang,J. Bank, J. Burgett, R. W. Conners, and Y. Liu, ”Wide-Area Frequency Monitoring Network (FNET) Architecture and Applications,” IEEE Transactions on Smart Grid, vol. 1, no. 2, September 2010, pp. 159-167.

This paper explains the mechanism of frequency monitoring network (FNET) which can monitor the status of the whole US power grid. It helps to understand how the data is collected and analyzed for power networks.

G. Giannakis, V.Kekatos, N. Gatsis, S. J. Kim, H. Zhu, and B.Wollenberg, ”Monitoring and Optimization for Power Grids: A Signal Processing Perspective,” IEEE Signal Processing Magazine, vol. 30, no. 5, September 2013, pp. 107-128. 

This paper provides a tutorial review of important advances in statistical signal processing that can be leveraged to enhance the data management/processing for future power system monitoring and optimization.

Z. Wang, M. Begovic, and J. Wang, ”Analysis of Conservation Voltage Reduction Effects Based on Multistage SVR and Stochastic Process,” IEEE Transactions on Smart Grid, vol. 5, no. 1, January 2014, pp. 431-439. 

This paper presents a useful analytic framework for characterizing the performance benefits of conservation voltage reduction (CVR). CVR is considered to be an important future direction for reducing power losses and/or peak demand at distribution networks.

D. W. H.Cai, S.Adlakha, S. H. Low, P. De Martini, and K. Mani Chandy, ”Impact of residential PV adoption on Retail Electricity Rates,” Energy Policy 62, 2013, pp. 830-843. 

An important element in energy data analytics is the price of electricity. In emerging smart grids, it is expected that the price of electricity will depend very much on renewables, e.g., home rooftop photo voltaic (PV) solar cells. What happens when this price can fall below the retail price of grid electricity? This paper provides a very rigorous study of the energy data analytics and management of prices of electricity for residential households in view that there is economic incentive to install rooftop PV systems and reduce their purchases of electricity from the grid. In addition to stochastic fluctuation, the paper also for the first time brings out the uncertainties that include possible changes in rate structures, such as the introduction of connection charges, possibility of PV prices dropping significantly in the future, etc.