Jie Duan

Bio: Jie Duan is an academic researcher from North Carolina State University. The author has contributed to research in topics: Distributed generation & Microgrid. The author has an hindex of 10, co-authored 19 publications receiving 411 citations. Previous affiliations of Jie Duan include Xi'an Jiaotong University.

To Centralize or to Distribute: That Is the Question: A Comparison of Advanced Microgrid Management Systems

Abstract: The advanced microgrid is envisioned to be a critical part of the future smart grid because of its local intelligence, automation, interoperability, and distributed energy resources (DER) hosting capability. The enabling technology of advanced microgrids is the microgrid management system (MGMS). In this article, we discuss and review the concept of the MGMS and state-of-the-art solutions regarding centralized and distributed MGMSs in the primary, secondary, and tertiary levels, from which we observe a general tendency toward decentralization.

Distributed Adaptive Droop Control for Optimal Power Dispatch in DC Microgrid

Abstract: In this paper, a coordinated adaptive droop control is addressed for DC microgrid to optimize its power distribution. The optimal solution for economical dispatch problem (EDP) of the microgrid is found through a fully distributed hierarchical control. The consensus-based economical regulator calculating the optimal solution for the generator is fully distributed. Thus, it eliminates the requirement of centralized coordinator. The droop controller receives the reference from the economical regulator and ensures the output power converging to the reference while maintaining the power balance of the system. Moreover, the economical regulator can estimate the load information of the system based on the characteristics of droop control. Thus, the information from load or renewable energy source is no longer required to solve the EDP that consequently decreases the number of communication nodes. This will reduce infrastructure cost, enhance the reliability, and fasten the converging speed of algorithm. The dynamic model is established and parameter selection guideline are given in this paper. A low-voltage dc-microgrid prototype platform is utilized to validate the effectiveness of the proposed control.

Day-Ahead Smart Grid Cooperative Distributed Energy Scheduling With Renewable and Storage Integration

Abstract: Day-ahead scheduling of generation units and storage devices is essential for the economic and efficient operation of a power system. Conventionally, a control center calculates the dispatch schedule by gathering information from all of the devices. However, this centralized control structure makes the system vulnerable to single point of failure and communication failures, and raises privacy concerns. In this paper, a fully distributed algorithm is proposed to find the optimal dispatch schedule for a smart grid with renewable and energy storage integration. The algorithm considers modified dc power flow constraints, branch energy losses, and energy storage charging and discharging efficiencies. In this algorithm, each bus of the system is modeled as an agent. By solely exchanging information with its neighbors, the optimal dispatch schedule of the conventional generators and energy storage can be achieved in an iterative manner. The effectiveness of the algorithm is demonstrated through several representative case studies.

Resilient Distributed DC Optimal Power Flow Against Data Integrity Attack

Abstract: This paper investigates and addresses the vulnerability of the distributed DC optimal power flow (DC-OPF) algorithm to data integrity attacks. In particular, we first show that a compromised distributed controller on a single bus could manipulate the power dispatch result by sharing false information to neighboring buses. Two malicious scenarios of launching the data integrity attack are considered, namely economic-driven and infeasibility-driven attacks, respectively. These vulnerabilities demonstrate a growing need for anomaly detection and mitigation mechanisms that fit into the distributed power system framework to counteract highly skilled malicious cyber attackers. We then introduce a resilient distributed DC-OPF algorithm with an embedded attack-resilient control mechanism. It performs two major functions in a fully distributed way: 1) verifying the correctness of the shared information from neighboring buses while protecting each other’s privacy and 2) identifying the compromised distributed controllers and recovering the optimal power dispatch result from the impact of data integrity attacks. The effectiveness of the proposed attack-resilient mechanism is illustrated through case studies in the IEEE 14-bus system.

A Novel Data Integrity Attack on Consensus-Based Distributed Energy Management Algorithm Using Local Information

Abstract: This paper introduces a novel data integrity attack on the well-developed consensus-based energy management algorithm. In particular, we show that by sending out elaborately falsified information during the consensus iterations, attackers could manipulate the system operating point and gain extra economic benefits. Meanwhile, the system-level and device-level constraints are still satisfied, e.g., the power generation and demand are balanced, and the operation of individual device respects physical constraints. This data integrity attack has two major features: First, attackers rely only on local information to complete the attack; neither additional information about system topology nor additional colluders are required; second, the attacking effect is accumulative, which enables attackers to choose to finish in either single or multiple iterations. By revealing such vulnerability of consensus-based applications to data integrity attack, this paper conveys the message that besides the efforts of designing novel distributed energy management algorithms to address the renewable energy integration challenges, it is equally important to protect the distributed energy management algorithms from possible malicious attacks to avoid potential economic losses. The proposed attack is illustrated in the Future Renewable Electric Energy Delivery and Management system.

Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid

Abstract: Implementing blockchain techniques has enabled secure smart trading in many realms, e.g. neighboring energy trading. However, trading information recorded on the blockchain also brings privacy concerns. Attackers can utilize data mining algorithms to obtain users’ privacy, specially, when the user group is located in nearby geographic positions. In this paper, we present a consortium blockchain-oriented approach to solve the problem of privacy leakage without restricting trading functions. The proposed approach mainly addresses energy trading users’ privacy in smart grid and screens the distribution of energy sale of sellers deriving from the fact that various energy trading volumes can be mined to detect its relationships with other information, such as physical location and energy usage. Experiment evaluations have demonstrated the effectiveness of the proposed approach.

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Abstract: Industrial cyber-physical systems (CPSs) are large-scale, geographically dispersed, and life-critical systems, in which lots of sensors and actuators are embedded and networked together to facilitate real-time monitoring and closed-loop control. Their intrinsic features in geographic space and resources put forward to urgent requirements of reliability and scalability for designed filtering or control schemes. This paper presents a review of the state-of-the-art of distributed filtering and control of industrial CPSs described by differential dynamics models. Special attention is paid to sensor networks, manipulators, and power systems. For real-time monitoring, some typical Kalman-based distributed algorithms are summarized and their performances on calculation burden and communication burden, as well as scalability, are discussed in depth. Then, the characteristics of non-Kalman cases are further disclosed in light of constructed filter structures. Furthermore, the latest development is surveyed for distributed cooperative control of mobile manipulators and distributed model predictive control in industrial automation systems. By resorting to droop characteristics, representative distributed control strategies classified by controller structures are systematically summarized for power systems with the requirements of power sharing and voltage and frequency regulation. In addition, distributed security control of industrial CPSs is reviewed when cyber-attacks are taken into consideration. Finally, some challenges are raised to guide the future research.

A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids

Abstract: Cyber-physical attacks are the main substantial threats facing the utilization and development of the various smart grid technologies. Among these attacks, false data injection attack represents a main category with its widely varied types and impacts that have been extensively reported recently. In addressing this threat, several detection algorithms have been developed in the last few years. These were either model-based or data-driven algorithms. This paper provides an intensive summary of these algorithms by categorizing them and elaborating on the pros and cons of each category. The paper starts by introducing the various cyber-physical attacks along with the main reported incidents in history. The significance and the impacts of the false data injection attacks are then reported. The concluding remarks present the main criteria that should be considered in developing future detection algorithms for the false data injection attacks.

Cyber-physical attacks and defences in the smart grid: a survey

Abstract: The smart grid is arguably one of the most complex cyber-physical systems (CPS). Complex security challenges have been revealed in both the physical and the cyber parts of the smart grid, and an integrative analysis on the cyber-physical (CP) security is emerging. This paper provides a comprehensive and systematic review of the critical attack threats and defence strategies in the smart grid. We start this survey with an overview of the smart grid security from the CP perspective, and then focuses on prominent CP attack schemes with significant impact on the smart grid operation and corresponding defense solutions. With an in-depth review of the attacks and defences, we then discuss the opportunities and challenges along the smart grid CP security. We hope this paper raises awareness of the CP attack threats and defence strategies in complex CPS-based infrastructures such as the smart grid and inspires research effort toward the development of secure and resilient CP infrastructures.