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Phasor measurement unit (PMU) technology is a need of the power system due to its better resolution than conventional estimation devices used for wide-area monitoring. PMUs can provide synchronized phasor and magnitude of voltage and current measurements for state estimation of the power system to prevent blackouts. The drawbacks of a PMU are the high cost of the device and its installation. The main aspect of using PMUs in electrical networks is the property to observe the adjacent buses, thereby making it possible to observe the system with fewer PMUs than the number of buses through their optimal placement. In the last two decades, exhaustive research has been done on this issue. Considering the importance of this field, a comprehensive review of the progress achieved until now is carried out and the limitations of existing reviews in the literature are highlighted. This paper can be seen as a major attempt to provide an up-to-date review of the research work carried out in this all-important field of PMU placement and indicates that some perspectives of optimal PMU placement still need attention. Eventually, the work will open a new standpoint for the research community to fill the research gap.

Synchrophasor technology opens a new window for power system observability. Phasor measurement units (PMUs) are able to provide synchronized and accurate data such as frequency, voltage and current phasors, vibration, and temperature for power systems. Thus, the utilization of PMUs has become quite important in the fast monitoring, protection, and even the control of new and complicated distribution systems. However, data quality and communication are the main concerns for synchrophasor applications. This study presents a comprehensive survey on wide-area monitoring systems (WAMSs), PMUs, data quality, and communication requirements for the main applications of PMUs in a modern and smart distribution system with a variety of energy resources and loads. In addition, the main challenges for PMU applications as well as opportunities for the future use of this intelligent device in distribution systems will be presented in this paper.

The electrical network is a man-made complex network that makes it difficult to monitor and control the power system with traditional monitoring devices. Traditional devices have some limitations in real-time synchronization monitoring which leads to unwanted behavior and causes new challenges in the operation and control of the power systems. A Phasor measurement unit (PMU) is an advanced metering device that provides an accurate real-time and synchronized measurement of the voltage and current waveforms of the buses in which the PMU devices are directly connected in the grid station. The device is connected to the busbars of the power grid in the electrical distribution and transmission systems and provides time-synchronized measurement with the help of the Global Positioning System (GPS). However, the implementation and maintenance cost of the device is not bearable for the electrical utilities. Therefore, in recent work, many optimization approaches have been developed to overcome optimal placement of PMU problems to reduce the overall cost by providing complete electrical network observability with a minimal number of PMUs. This research paper reviews the importance of PMU for the modern electrical power system, the architecture of PMU, the differences between PMU, micro-PMU, SCADA, and smart grid (SG) relation with PMU, the sinusoidal waveform, and its phasor representation, and finally a list of PMU applications. The applications of PMU are widely involved in the operation of power systems ranging from power system control and monitor, distribution grid control, load shedding control and analyses, and state estimation which shows the importance of PMU for the modern world.

Due to the increasing development of renewables in power systems, the requirements for phasor measurement units (PMUs) becomes higher. A PMU calibrator is an important tool to test and calibrate PMUs to ensure their measurement performance. This device can provide accurate reference values for error analysis of PMUs. In this paper, a phasor algorithm with low computational complexity and high accuracy is proposed for the PMU calibrator. This method reduces the processor requirements and development costs of the calibrator, thereby facilitating its popularization. At first, an enhanced discrete Fourier transform (DFT) method is put forward: 1) the frequency response of the windowed DFT method is analyzed to reveal its large measurement errors under dynamic conditions; 2) the parameter requirements of the DFT window that is regarded as a lowpass filter are analyzed, and thus a lowpass filter with better filtering performance is designed as the window coefficients to improve the estimation accuracy. Then, based on the enhanced DFT algorithm, a calibrator algorithm framework consisting of two-stage filters and a signal recognition module is established. This algorithm can consider the anti-interference ability and dynamic measurement accuracy at a low reporting rate. Simulation and experimental test results show that the proposed calibrator algorithm provides high-accuracy measurements of the static and dynamic signals with low computational complexity.

The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work.

Synchrophasor-driven smart grid applications aiming to orchestrate a diverse set of Distributed Energy Resources (DERs) require extensive infrastructure including substantial instrumentation hardware, communication network extensions and controller installations for coordinated operation. This can make the overall installation expensive. Additionally, due to the computational complexity and data-intensive nature of the PDC functionality, most of the existing PDC implementations are on a purely software level, making them unsuitable for the real-time applications. To address this, the current paper proposes an alternate architecture for the real-time synchrophasor-based control of DER applications (e.g., microgrids) incorporating a centralized synchronization hardware designed to replace aggregation Phasor Data Concentrators (PDCs) and supplementary control algorithms into a singular reconfigurable hardware. This particular hardware is termed a Synchrophasor Synchronization Gateway and Controller (SSGC). The robustness of the proposed architecture is tested by using real-time (RT) Controller Hardware-In-the-Loop (CHIL) simulation-based experiments by manipulating the communication network that connects the SSGC with multiple Phasor Measurement Unit (PMU) streams broadcasting data through the IEEE C37.118.2 protocol in real time. These PMU streams were generated by using a real-time microgrid model running on a Typhoon HIL 604 simulator. To manipulate the communication interface between the proposed SSGC hardware and the PMU streams, a configurable Wide Area Network (WAN) emulator and communication network impairment appliance deployed in the Candela Technologies CT910 external hardware was utilized. The real-time control system was expanded by incorporating a low-pass filter to eliminate the potential overswitching of a Battery Energy Storage System (BESS). The proposed architecture demonstrated a reliable performance under ideal to moderately tampered communication networks. However, under a significantly corrupted network, the performance of this architecture is acutely affected.

The pursuit of achieving total power network observability in smart grids using Phasor Measurement Units (PMUs) carries a significant promise of real-time Wide-Area Monitoring, Protection, and Control (WAMPAC). PMU applications eliminate periodical measurements, thereby increasing accuracy through a high sampling rate of the measured power systems quantities. The high costs of installation of PMUs for total power system observability presents a challenge in the implementation of PMUs. This is due to the expensive costs of PMU devices. This has led to a prominent optimal PMU placement (OPP) problem that researchers tirelessly aim to solve by ensuring a complete power network observability while using the least installed PMU devices possible. In this paper, a novel Binary Firefly Algorithm (BFA) based on the node degree centrality scores of each bus is proposed to minimize PMU installations. The BFA solves the OPP problem in consideration of the effect of Zero Injection Buses (ZIBs) under normal operation and single PMU outage (SPO). The robustness and efficiency of the proposed algorithm is tested on IEEE-approved test systems and visualized with a force-directed technique on an undirected power network graph. The proposed BFA yields the same but better optimal PMU numbers, obtained by existing meta-heuristic optimization techniques found in the literature for each of the IEEE test cases, as well as highlighting the cost–benefit of having a robust system against single PMU loss while considering the ZIB effect for an improved system measurement availability.

Compact, energy-efficient, and autonomous wireless sensor nodes offer incredible versatility for various applications across different environments. Although these devices transmit and receive real-time data, efficient energy storage (ES) is crucial for their operation, especially in remote or hard-to-reach locations. Rechargeable batteries are commonly used, although they often have limited storage capacity. To address this, ultra-low-power design techniques (ULPDT) can be implemented to reduce energy consumption and prolong battery life. The Energy Harvesting Technique (EHT) enables perpetual operation in an eco-friendly manner, but may not fully replace batteries due to its intermittent nature and limited power generation. To ensure uninterrupted power supply, devices such as ES and power management unit (PMU) are needed. This review focuses on the importance of minimizing power consumption and maximizing energy efficiency to improve the autonomy and longevity of these sensor nodes. It examines current advancements, challenges, and future direction in ULPDT, ES, PMU, wireless communication protocols, and EHT to develop and implement robust and eco-friendly technology solutions for practical and long-lasting use in real-world scenarios.

Phasor measurement units (PMUs) provide synchronized measurements to enhance power system monitoring, strategically placed to achieve full network observability with minimal cost. In this paper, the PMU placement problem for critical buses is addressed using integer linear programming, taking into account both PMU contingencies and the impact of zero-injection buses. The primary contribution is the development of a multi-stage approach to place PMUs on critical buses. Moreover, it is demonstrated that considering PMU contingencies inherently accounts for line contingencies. Furthermore, a new performance metric, the Bus Coverage Index (BCI), is proposed to evaluate the effectiveness of the placement strategy. This index overcomes the limitations of existing indices, such as the Sum of Redundancy Index (SORI) and Bus Observability Index (BOI). The results are tested on various IEEE benchmark systems under four different cases, showing significantly improved results in terms of network observability and minimized number of PMUs. In Case 1, SORI values improved significantly for the IEEE 7 and IEEE 118 bus systems, while in Case 2, enhancements were observed in the IEEE 30 and IEEE 118 systems. Case 3 demonstrated consistency in results across systems. Notably, in Case 4, the number of required PMUs was reduced in the IEEE 30, IEEE 57, IEEE 118, and New England 39 bus systems, with complete network observability.

Phasor measurement units (PMUs) are deployed at power grid nodes around the transmission grid, determining precise power system monitoring conditions. In real life, it is not realistic to place a PMU at every power grid node; thus, the lowest PMU number is optimally selected for the full observation of the entire network. In this study, the PMU placement model is reconsidered, taking into account single- and multi-capacity placement models rather than the well-studied PMU placement model with an unrestricted number of channels. A restricted number of channels per monitoring device is used, instead of supposing that a PMU is able to observe all incident buses through the transmission connectivity lines. The optimization models are declared closely to the power dominating set and minimum edge cover problem in graph theory. These discrete optimization problems are directly related with the minimum set covering problem. Initially, the allocation model is declared as a constrained mixed-integer linear program implemented by mathematical and stochastic algorithms. Then, the 0/1 integer linear problem is reformulated into a non-convex constraint program to find optimality. The mathematical models are solved either in binary form or in the continuous domain using specialized optimization libraries, and are all implemented in YALMIP software in conjunction with MATLAB. Mixed-integer linear solvers, nonlinear programming solvers, and heuristic algorithms are utilized in the aforementioned software packages to locate the global solution for each instance solved in this application, which considers the transformation of the existing power grids to smart grids.