Power Quality Monitoring during RE Connections

The article describes the importance of monitoring power quality parameters for stabilising the electricity grid. The recurrent and intermittent renewable energy connections also induce voltage fluctuations, harmonics, surges and imbalances in the grid. These are power quality issues which need to be addressed. - Jayant Sinha

Grid-tied renewable energy (RE) generation is characterised by geographical diversity, meteorological unpredictability and supply variability. The challenges are compounded because the RE generators have to cope up with power quality issues such as harmonic distortions, voltage irregularities and transient currents. These problems not only lead to grid threshold violations, but also liable to invite regulatory penalties. They also have a potentially debilitating impact on the grid with adverse impact on both the economy and environment.

The power quality challenges of modern grid call for adoption of methods and solutions to visualise the state of the network in real-time, study the level of grid disturbances due to variable RE connections or disconnections and take appropriate steps to improve power quality and maintain grid stability. This article explains the necessity of power quality monitoring in balancing the supply vs demand in an optimum manner, amidst growing penetration of RE generators, in compliance with the grid code and standards of performance.

Power Quality issues in a volatile grid

In any microgrid implementation involving grid integration of Distributed Energy Resources (DER) or RE systems, the importance of power quality measurements cannot be overlooked. Monitoring of power quality is the key for stable and reliable operations of the grid. With advancements in technology, continuous monitoring and analysis of the electrical quality parameters has become possible, which helps to safeguard the grid and enhance the life of electrical assets.

The integration of geographically diverse RE generation to the main grid has pushed the demand for power quality data measurements, logging, transmission, processing and centralised display. Time series analysis of voltage, current, frequency and phase help address a host of power quality issues such as voltage swells, sags, flicker, harmonics or phase imbalance. Power quality disturbances can also arise from the load end such as from inefficient motors, improper earthing or insulation, loose connections, switching operations, power electronic devices or arcing loads.

Power quality of the electrical system is not just about availability and continuity of power supply, but also about the level of deviation or distortion in pure, sinusoidal waveform. Due to volatile nature of diverse RE generators, increasing non-linear loads connected to the system and the absence of centralised power quality monitoring, the grid frequently suffers voltage threshold violations, harmonics, flicker and voltage distortions.

The RE generators are a diverse mix of solar PV, wind and battery energy storage systems. The demand also fluctuates depending on weather and time-of-day loading conditions. These cause the voltage levels to deviate from normal acceptable levels which result in voltage sags and swells. The intermittent renewable generating sources also inject harmonics, transients and reactive power into the grid, which create power quality problems. These power quality problems result in technical losses, grid capacity reduction, network deterioration and possibility of network failure. Therefore, there is a need to manage geographically diverse RE microgrid connections to the main grid in real-time or ‘near’ real-time, with optimum utilisation of various sources of generation, while maintaining the grid stability and reliability at all times.

Mitigation of Power Quality issues

Several methods are employed for power quality monitoring such as the use of multimeters, oscilloscopes, Disturbance Fault Recorder (DFRs), spectrum analysers, energy meters and smart relays. To address the power quality issues, the trend is rapidly shifting from traditional to modern methods of electrical signal processing and applying them for harmonics filtering and waveform correction.

Another method which is now being used for on-line monitoring of grid power quality parameters, and using the information for controlling and prioritising RE connections is called Active Network Management (ANM). ANM is a smart grid application to manage all the connected RE generating sources remotely in unison. The Smart Grid ANM solution monitors real-time or ‘near’ real-time data collected from SCADA/ HMI of the different energy generators connecting to the grid on a unified dashboard.

The solution is powered by an intelligent algorithm to monitor the grid electrical parameters. Due to intermittent and variable characteristic of RE generation, the system has to respond frequently to the imbalance between energy feed and demand, causing both voltage and frequency fluctuations. The intelligent ANM solution monitors the grid events classified as abnormal, performs time-series analysis and helps balance fluctuating generation by generating appropriate decision signals, communicated through a centralized ANM controller, to multiple grid-connected DER systems or RE generators to ramp up, ramp down, connect or disconnect in a sequence which minimizes voltage fluctuations and helps maintain grid stability.

With the ANM solution, it is possible to monitor multiple Distributed Energy Resources (DER) and monitor the impact on power quality when these DER systems (RE generators) connect or disconnect with the grid. ANM also signals the RE generators the actual capacity they should each contribute to the grid, in an optimum manner, so that the system balance is maintained without causing instability or electrical threshold violations in the network. The solution works in both recommendatory mode or control mode. In the former, only recommendations are offered as to the demand to be met by each generating resource, the sequence of connection and ramping rate. In the latter, ANM takes control of the resources by overriding local controls in case it senses any power quality violations or destabilising effect on the grid by a particular RE generator.

Solution Implementation

The heart of the solution is the central ANM controller, an intelligent device which aggregates data from all local RE controllers. The local DER controller is connected with SCADA or DCS of the local RE generation plant, capturing electrical parameters including the power quality parameters and environment data. The local DER controllers encrypts and transmit this data to the central ANM controller, which is then transmitted to the central dashboard for analytics and graphical display, in a two-way communication.

The dashboard application is configured for the required parametric thresholds and informs the operator of any power quality breaches or standard of performance violations, notified through software alarms and annunciation system. The dashboard software performs an integrated analysis of various operating parameters for the safe loading and back down of the DER generators to the best of their merit rating and ensure that the grid remains stable and efficient.

The share of RE injected into the grid from each DER generator is selected based on the generator capacity, capability (ramp rate), asset status, environmental conditions of generation and quality of supply. In addition, pricing (ToD tariff) signals are also incorporated in the algorithm to optimise the cost of generation.

The ANM control systems are based on open standards architecture, which can connect to different SCADA systems using OLE process controls (OPC) and various applications conforming to international standards. ANM offers reliable voltage regulation and alerts the operator in real-time of any breach in power quality and reliability parameters. This enables proactive control actions for the efficient management of different RE generators.

Benefits of Real-Time Monitoring

Real-time monitoring of grid parameters helps minimise technical losses by recommending or triggering control actions to regulate voltage, current, active power, and reactive power. Real-time measurements of instantaneous parameters with threshold values reduce the risk for grid breakdowns. ANM provides load balancing information and enables the grid operator to take timely preventive action against disturbances arising from intermittent DER system (RE generators) connecting with the grid, non-linear loads, switching capacitor banks, tap changers, variable drives and battery storage systems. Implementing ANM and monitoring real-time power quality parameters of the grid, especially during volatile RE connections, offer the following benefits:

  • Better visibility of DER availability and relative performance measurement of DERs
  • Coordinated management of DER generators and ensuring secure connections with the grid
  • Balancing of energy demand vis-à-vis supply and ensuring stable operation of the grid
  • Being in control of fluctuating renewable capacities and ensure optimum DER utilisation
  • Ensuring quality and reliable power, with variable RE mix
  • Deferment of capital asset replacements by preventing grid disturbances and breakdown
  • Compliance of electricity regulations (power quality and reliability indices), standards of performance (grid stability) and environmental obligations (carbon footprint reduction).

Conclusion

The benefits of introducing power quality measurement systems for managing the power distribution networks far outweighs the investment needed for a viable solution. This allows early identification of network vulnerabilities, such as harmonics, transients, phase imbalance, overloading and voltage sags or swells. It also allows informed decision making to prevent major breakdowns, thus, saving huge cost of network maintenance and capital replacements. Moreover, timely corrective action to control power quality violations help improve network reliability, safety and asset life improvement.

These benefits – technical, commercial and regulatory – are now the driving force behind the burgeoning market offering power quality monitoring solutions for conventional grid and smart grid systems. At the same time, it is equally important that we select the technology and partners wisely, after careful assessment of the power quality problems and system requirements.