Haoyang Lu

Accurate power quality monitoring in microgrids

Traditional power grid is not resistant to severe weather conditions, especially in remote areas. For some areas with few people, such as islands, it is difficult and expensive to maintain their connectivity to the traditional power grid. Therefore, a self-sustainable microgrid is desired. However, given the limited local energy storage and energy generation, it is extremely challenging for a microgrid to balance the power demand and generation in real-time. To realize the real-time power quality monitoring, the power quality information of microgrid, such as voltage, frequency and phase angle in each home, needs to be collected in real- time. Furthermore, the unreliable sensing results and data collection in a microgrid make the real-time data collection more difficult. To address these challenges, we designed an accurate real-time power quality data sensing hardware to sense the voltage, frequency and phase angle in each home. A novel data management technique is also proposed to reconstruct the missing data caused by unreliable sensing. We implemented our system over off-the-shelf smartphones with a few peripheral hardware components, and realized an accuracy of 1.7 mHz and 0.01 rad for frequency and phase angle monitoring, respectively. We also show our data management technique can reconstruct the missing data with more than 99% accuracy.

A Microgrid Monitoring System Over Mobile Platforms

Real-time awareness of the phasor state, including the volatile frequency and phase angle, is critical to maintain reliable and stable operations of the power grid. However, the high cost and low accessibility of current synchrophasors restrict their large-scale deployment over highly distributed microgrids. In this paper, we present a practical system design for monitoring the microgrid frequency and phase angle over mobile platforms and significantly reduce the cost of such monitoring. Being different from current synchrophasors, our system does not rely on continuous GPS reception and hence it is highly accessible and applicable to heterogeneous microgrid scenarios. We develop various techniques to provide the timing signal that is necessary for precise microgrid monitoring. For frequency monitoring, the network time protocol is exploited for time synchronization. For phase angle monitoring which requires a higher timing accuracy, 200 Hz primary synchronization signal being embedded in the 4G LTE cellular signal is harvested for time synchronization. We implemented our system over off-the-shelf smartphones with a few peripheral hardware components and realized an accuracy of 1.7 MHz and 0.01 rad for frequency and phase angle monitoring, respectively. Although the accuracy of the prototype is lower than that of the GPS-based systems, the system could still satisfy the requirements of microgrid monitoring. The total cost of the system can be controlled within

Supporting real-time wireless traffic through a high-throughput side channel

100 and no installation cost is required. Experiment results compared with the traditional frequency disturbance recorders verify the effectiveness of our proposed system.

Power grid frequency monitoring over mobile platforms

Performance of modern cognitive and interactive mobile applications highly depends on the data transmission delay in the wireless link that is vital to supporting real-time wireless traffic. To eliminate wireless network congestion caused by large amounts of concurrent network traffic and support such real-time traffic, traditional schemes adopt various flow control and QoS-aware traffic scheduling techniques, but fail when the amount of network traffic further increases. In this paper, we present a novel design of high-throughput wireless side channel, which operates concurrently with the existing wireless network channel over the same spectrum but dedicates to real-time traffic. Our key idea of realizing such a side channel is to exploit the excessive SNR margin in the wireless network to encode data as patterned interference. We design such patterned interference in form of energy erasure over specific subcarriers in an OFDM-based wireless network, and achieve a data rate of 1.25 Mbps in the side channel without affecting the existing wireless network links. Experimental results over software-defined radio platforms demonstrate the effectiveness of our side channel design in reducing the latency of real-time wireless traffic, while providing sufficient data throughput for such traffic.

User-centric incentive design for participatory mobile phone sensing

Information about the frequency deviation is critical to reliable and stable operation of the power grid. Current wide-area power grid monitoring systems consist of Phasor Measurement Units (PMUs) at both high-voltage transmission level and low-voltage distribution level, but are generally unsatisfactory for large-scale deployment over highly distributed microgrids in individual households and local communities due to their high cost and low accessibility. In this paper, we present a practical system design which significantly improves the accessibility and reduces the cost of frequency monitoring by unleashing the capabilities of modern mobile platforms in computation, communication, and storage. In our system, the Network Time Protocol (NTP) is exploited for time synchronization, replacing inflexible GPS receivers that are widely used in current PMUs. A small quantity of peripheral hardware components are used to build up an embedded sensing component for efficient and accurate frequency measurement. The experiment results compared to the traditional Frequency Disturbance Recorders (FDRs) show the effectiveness of the proposed frequency monitoring system.

Scheduling dynamic wireless networks with limited operations

Mobile phone sensing is a critical underpinning of pervasive mobile computing, and is one of the key factors for improving people’s quality of life in modern society via collective utilization of the on-board sensing capabilities of people’s smartphones. The increasing demands for sensing services and ambient awareness in mobile environments highlight the necessity of active participation of individual mobile users in sensing tasks. User incentives for such participation have been continuously offered from an application-centric perspective, i.e., as payments from the sensing server, to compensate users’ sensing costs. These payments, however, are manipulated to maximize the benefits of the sensing server, ignoring the runtime flexibility and benefits of participating users. This paper presents a novel framework of user-centric incentive design, and develops a universal sensing platform which translates heterogenous sensing tasks to a generic sensing plan specifying the task-independent requirements of sensing performance. We use this sensing plan as input to reduce three categories of sensing costs, which together cover the possible sources hindering users’ participation in sensing.

A GPS-free power grid monitoring system over mobile platforms

Scheduling in wireless networks is critical to maximize the network throughput by avoiding interference among wireless links, and is usually formulated as solving the NP-hard Maximum Weighted Independent Set (MWIS) problem over a network confiict graph. Existing scheduling algorithms are designed to provide approximations to global optimality via distributed operations in wireless networks, but will frequently reschedule the entire network in cases of network dynamics regardless of the actual network area being affected by these dynamics. Such repetitive rescheduling results in a large amount of computation and communication overhead, most of which may be, however, unnecessarily incurred over the wireless links that remain unchanged. To reduce such overhead and improve the scheduling cost-effectiveness, in this paper we develop distributed algorithms that adaptively constrain network scheduling within the limited scope where network dynamics occur. The scheduling results from such limited operations are then combined with the previous scheduling results over the remaining portions of the network, hence still providing guaranteed network throughput. The performance of our proposed algorithms has been validated by formal analysis, and been verified by both numerical studies and real-world experiments.

Synchronized Wireless Measurement of High-Voltage Power System Frequency Using Mobile Embedded Systems

In smart grids, the deviation of frequency and phase angle serves as an important indicator of abnormal events, the detection of which is critical to maintain reliable and stable operations of the power grid. However, the high cost and low accessibility of current power grid monitoring systems restrict their large-scale deployment over highly distributed microgrids. In this paper, we present a practical frequency and phase angle monitoring system design over mobile platforms, which significantly reduces the cost of power grid monitoring by utilizing the functionalities of modern mobile devices. We harvest the 200 Hz Primary Synchronization Signal (PSS) embedded in the 4G Long Term Evolution (LTE) cellular signal for time synchronization in power grid monitoring, replacing the Pulse-Per-Second (PPS) signal that is retrieved from GPS receivers and being used by current monitoring systems. We implement our system over realistic smartphones with a few peripheral hardware, and realize a frequency monitoring accuracy of 0.2 mHz and a phase angle monitoring accuracy of 0.01 rad. Experiment results compared with the traditional Frequency Disturbance Recorders (FDRs) verify the effectiveness of our proposed system.

On Exploiting Dynamic Execution Patterns for Workload Offloading in Mobile Cloud Applications

This paper focuses on synchronized wireless measurement of high-voltage (HV) power system frequency using mobile embedded systems (MESs) integrated with a wireless electric field sensor (WEFS). Unlike traditional synchronized frequency measurement devices, which rely on potential transformers and current transformers physically connected to system elements, a WEFS is used to realize wireless signal acquisition in the vicinity of any HV apparatus. The MES performs real-time frequency estimation using a recursive discrete Fourier transform based algorithm. Network time protocol (NTP) is used for time synchronization, increasing the system flexibility by eliminating global positioning system reliance. An NTP-based synchronized sampling control method is proposed and implemented in MES to compensate the sampling time error caused by local time drift and division residue. The proposed system has the advantages of portability and lower cost, making it highly accessible and useful for a wide array of synchronized frequency measurement applications. Experiment results verify the accuracy and effectiveness of the proposed system.