Special Issue on Smart Grid and Emerging Technology Integration

Electrification for the world through the vast networks of electricity has been considered by the National Academy of Engineering as the most important engineering achievement of the twentieth century. The achievement is reflected by the generally successful management of power system complexity, which lies in its physical requirement of continuous balancing of supply and demand. The complexity, however, has been dramatically increased in the past decade, with the increasing penetration of variable-output renewable energy, the widespread of distributed generation and demand-side resources, and the electrification of transportation systems.

To power the world’s economic growth and to meet societal needs, it becomes more apparent that the current power grid needs to be modernized so that the grid can be more reliable, flexible, efficient, and resilient. This gives rise to the notion of the smart grid, a power system characterized by a diverse generation resource mix, a combination of centralized and distributed generation, active demand participation, and a robust transmission and distribution network enhanced by advanced digital sensor, communication, and control technologies.

While the vision of the smart grid is clear, there are many obstacles in implementing the various concepts. On the generation side, the variable-output nature of major renewable resources (wind and solar energy) poses considerable difficulties in maintaining system reliability. On the demand side, if not managed properly, more actively engaged distributed generation and demand-response resources will add more fluctuations to the system. On the transmission and distribution side, the increased uncertainty from both the supply and demand side calls for swift and flexible operations.

This special issue is dedicated to address many of the challenges faced by the transitioning to the smart grid. More specifically, it focuses on four major topics, as follows: (1) renewable integration, (2) smart transmission, (3) distributed generation and storage, and (4) flexible demand resources. In aiding renewable generation integration to the grid, the paper “Joint Probability Distribution and Correlation Analysis of Wind and Solar Power Forecast Errors in the Western Interconnection” by J. Zhang, B.-M. Hodge, and A. Florita investigates how to utilize the correlation between wind and solar forecast errors to improve forecasting, and hence to facilitate the integration of both wind and solar into the grid. In the paper “Optimal Management of Wind Energy with Storage: Structural Implications for Policy and Market Design” by N. R. Kirby, L. C. Anderson, and M. Davison, they investigate strategies to bundle energy storage with wind energy to reduce variability and to increase operational and planning efficiency. While in “Impacts of the Renewable Portfolio Standard on Regional Electricity Markets” by Y. Zhou and T. Liu, they study the impacts of policies on the development of renewable energy.

Aided by smart devices, power grids’ transmission networks can be operated more flexibly to both meet the challenges of the increasing uncertainty and to improve systems’ reliability. The paper “N-1 Reliable Unit Commitment via Progressive Hedging” by C. Li, M. Zhang, and K. W. Hedman proposes a customized stochastic programming method, based on the progressive hedging algorithm, to improve the unit commitment process while explicitly accounting for uncertainties. In “Real Time Corrective Transmission Switching in Response to N-m Events,” P. Balasubramanian and K. W. Hedman design a heuristic algorithm to improve the computational performance of the joint optimization of economic dispatch and transmission topology control.

As a defining characteristic of the smart grid is to shift from centralized to distributed generation (DG), two papers in this special issue discuss several DG technologies. In “Novel Fuzzy Controlled Energy Storage for Low-Voltage Distribution Networks with Photovoltaic Systems under Highly Cloudy Conditions” by J. Wong, Y. S. Lim, and E. Morris, they develop a novel fuzzy control method to manage low-voltage photovoltaic (PV) systems coupled with storage resources. While in the paper “Stochastic, Multiobjective, Mixed-Integer Optimization Model for Wastewater-Derived Energy” by C. U-tapao, S. A. Gabriel, C. P. E. Peot, and M. Ramirez, a multiobjective, mixed-integer optimization model is developed for a wastewater-treatment plant, which can convert the solid end product from wastewater into renewable energy.

Last but certainly not the least, as active demand participation is considered as a cornerstone for the smart grid, four papers in this special issue are dedicated to address the various aspects of demand response. In the paper “Is Deferrable Demand an Effective Alternative to Upgrading Transmission Capacity?” by A. J. Lamadrid, T. D. Mount, W. Jeon, and H. Lu, they investigate the many benefits of having deferrable load in the system, including reducing transmission congestion, lowering average wholesale electricity prices, and reducing the need of having extra generation capacity to maintain system reliability. From consumers’ perspective, F. Chen, L. V. Snyder, and S. Kishore in their paper “Efficient Algorithms and Policies for Demand Response Scheduling” propose several algorithms based on approximate dynamic programming to optimize energy consumption in a single electricity-consuming facility. While efficient management demand response (DR) resources is certainly important, another critical aspect is cyber security and privacy. In addressing this aspect, the paper “Achievable Privacy in Aggregate Residential Energy Management Systems,” by C. Chen, L. He, P. Venkitasubramaniam, S. Kishore, and L. V. Snyder, proposes strategies, such as inserting dummy packets into the communication between individual consumers and the central DR schedulers, to achieve anonymity in data transmission. On a completely different approach of implementing DR, Z. Wang and J. Wang in their paper “Analysis of Performance and Efficiency of Conservation Voltage Optimization Considering Load Model Uncertainty” discuss how to use the conservation voltage reduction (CVR) method to realize flexibility in demand and its effectiveness.

As there exist many challenges and obstacles to transition from our current power grid to the future smart grid, research in many of the related areas has just been started. The purpose of this special issue is to encourage researchers in multiple fields, especially in operations research, electrical engineering, and computer science to work together on tackling the many challenges, hence accelerating the transition. The writers want to thank all the researchers for their quality work and are very grateful to all the reviewers for their efforts in improving the papers. Finally, the writers are very thankful to Dr. Chung-Li Chung, Editor-in-Chief of the Journal of Energy Engineering, for his vision and generous help for making this special issue a reality.