(1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Energy function analysis for power system stability

In this paper, we propose a novel transactive energy trading (TET) framework to deal with the economic issues in energy trading and the technical issues in distribution system operation in a holistic manner In particular, we innovatively integrate a bilateral energy trading mechanism with the optimal power flow (OPF) technique to increase economic benefits to individual participants, and meanwhile ensure the reliability and security of the system operation In order to resolve the inherent conflict of interests, Nash bargaining theory is used to model the TET problem, which is further decomposed into a multiperiod OPF problem and a payment bargaining problem Moreover, we develop an efficient distributed algorithm for solving the TET problem base on alternating direction method of multipliers (ADMM) Instead of directly solving optimization subproblems like most ADMM-based distributed algorithms, we derive closed-form solutions to all subproblems to significantly improve the computational efficiency Finally, numerical tests on the IEEE 37-bus and 123-bus distribution systems demonstrate the effectiveness of our proposed framework and the efficiency of our distributed algorithm

Distributed Transactive Energy Trading Framework in Distribution Networks

The increased penetration of distributed energy resources (DER) will significantly increase the number of devices that are owned and controlled by consumers and third-parties. These devices have a significant dependency on digital communication and control, which presents a growing risk from cyber-attacks. This study proposes a holistic attack-resilient framework to protect the integrated DER and the critical power grid infrastructure from malicious cyber-attacks, helping ensure the secure integration of DER without harming the grid reliability and stability. Specifically, the authors discuss the architecture of the cyber-physical power system with a high penetration of DER and analyse the unique cybersecurity challenges introduced by DER integration. Next, they summarise important attack scenarios against DER, propose a systematic DER resilience analysis methodology, and develop effective and quantifiable resilience metrics and design principles. Finally, they introduce attack prevention, detection, and response measures specifically designed for DER integration across cyber, physical device, and utility layers of the future smart grid.

Cybersecurity for distributed energy resources and smart inverters

Electric vehicles (EVs) are promising to provide frequency regulation services due to their fast regulating characteristics. However, when EVs participate in supplementary frequency regulation, it is challenging to simultaneously achieve the dispatch of the control center and the expected state of charge (SOC) levels of EV batteries. To solve this problem, in this paper we propose a vehicle-to-grid (V2G) control strategy, in which an uncertain dispatch is implemented in the control center without detailed EV charging/discharging information. The regulation from the control center is achieved by allocating the regulation task within the frequency regulation capacity of EVs. The expected SOC levels of EV batteries are guaranteed by a real-time correction of their scheduled V2G power in EV charging stations. Simulations on an interconnected two-area power system validate the effectiveness of the proposed V2G control in achieving both the frequency regulation and the expected SOC levels of EVs.

https://ieeexplore.ieee.org/ielaam/5165411/8388565/7790841-aam.pdf

EV Dispatch Control for Supplementary Frequency Regulation Considering the Expectation of EV Owners

This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form model for PEV fast-charging stations’ service abilities, which considers heterogeneous PEV driving ranges and charging demands. We utilize a modified capacitated flow refueling location model based on subpaths (CFRLM_SP) to explicitly capture time-varying PEV charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM_SP to enhance model accuracy and computational efficiency. We then propose a stochastic mixed-integer second-order cone programming model for PEV fast-charging station planning. The model considers the transportation network constraints of CFRLM_SP and the power network constraints with ac power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.

A Second-Order Cone Programming Model for Planning PEV Fast-Charging Stations

Power system outages/blackouts, especially weather related, are becoming more and more frequent, incurring significant economic and social costs The ability to restore power services quickly after a blackout is crucial for power system resilience Power system restoration is an extremely complicated process, involving multiple steps, highly combinatorial operational decisions, and highly nonlinear technical constraints, which make restoration planning an exceptionally challenging task This paper will first introduce the restoration process and operations, examine important issues in restoration, and survey the state of the art in the research and practice of power system restoration planning Then, we will focus on the commonly used buildup restoration planning strategy, in which the system is sectionalized into smaller subsystems with initial power sources, and then the subsystems are restored in parallel Due to the complexity, existing approaches treat the sectionalization and restoration separately, leading to a suboptimal restoration plan We will introduce an integrated restoration planning approach to improve the quality of restoration plans globally (such as shorter overall restoration time) by using mathematical programming and simulation in an interactive and iterative way Case studies will be provided to illustrate the effectiveness of the proposed approach

An Integrated Approach for Power System Restoration Planning

Small-Signal Stability Constrained Optimal Power Flow (SSSC-OPF) can provide additional stability measures and control strategies to guarantee the system to be small-signal stable. However, due to the nonsmooth property of the spectral abscissa function, existing algorithms solving SSSC-OPF cannot guarantee convergence. To tackle this computational challenge of SSSC-OPF, we propose a Sequential Quadratic Programming (SQP) method combined with gradient sampling for SSSC-OPF. At each iteration of the proposed SQP, the gradient of the spectral abscissa function is randomly sampled at the current iterate and additional nearby points to make the search direction computation effective in nonsmooth regions. The method can guarantee SSSC-OPF is globally and efficiently convergent to stationary points with probability one. The effectiveness of the proposed method is tested and validated on WSCC 3-machine 9-bus system, New England 10-machine 39-bus system, and IEEE 54-machine 118-bus system.

An SQP Method Combined With Gradient Sampling for Small-Signal Stability Constrained OPF

Vehicle-to-grid (V2G) control of electric vehicles (EVs) has the potential to provide frequency regulation for power system operation. The authors study the frequency droop control with EVs’ participation. The challenge is to simultaneously suppress frequency fluctuation and satisfy transportation usages of EV owners. A V2G control consisting of frequency droop control and scheduled charging is developed to overcome this challenge. Frequency droop control can suppress frequency fluctuation by responding to frequency deviation signal, while scheduled charging can achieve the charging demands of EV owners. Although uncertain regulation may result in deviation of the battery energy levels from the expected, the scheduled charging made based on the departure time, the real-time, the real-time battery energy levels, and the expected battery energy levels can compensate this change in real time. The proposed V2G control can ensure different types of charging demands such as holding battery energy levels and elevating battery energy levels, unlike existing methods in which different V2G control strategies have to be developed. Simulations on a two-area interconnected power grid using real power grid data in China validate the effectiveness of the proposed V2G control in suppressing frequency fluctuation and achieving the charging demands of EV owners.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2016.0554

Frequency droop control with scheduled charging of electric vehicles

This paper presents the framework of a power-dispatching automation system (PDAS) based on a virtual private cloud, which extracts advantages of technologies, such as a virtual private cloud, a virtual private network, an https protocol, etc. Unlike existing on-premise or public cloud hosted PDASs that are vulnerable and may be subject to blackouts due to extreme conditions, such as natural disasters or cyberattacks, the proposed framework operates more safely and securely under those conditions, while at the same time meeting the reliability requirements for power systems as well. This paper presents the theory, architectural design, characteristics, and implementation process of the system, as well as its reliability and cyber security measurements. The annual failure time of the proposed system is reduced from 61.2 to about 0.43 min, about 142 times less than those of existing PDASs. This framework has been implemented in the Lipu power system in China since May 2016. Results show that the proposed system is reliable, safe, and cost-effective, with a bright prospect for future applications.

/pdf/virtual-private-cloud-based-power-dispatching-automation-1ohfpz4au2.pdf

Peijie Li

Papers

EV Dispatch Control for Supplementary Frequency Regulation Considering the Expectation of EV Owners

An Integrated Approach for Power System Restoration Planning

An SQP Method Combined With Gradient Sampling for Small-Signal Stability Constrained OPF

Frequency droop control with scheduled charging of electric vehicles

Virtual Private Cloud Based Power-Dispatching Automation System—Architecture and Application