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As electrical resiliency needs continue to escalate, potential solutions consisting of large, integrated microgrids with ever increasing islanding capabilities supplemented by renewables and storage are desired. All of these potential solutions will have one thing in common, a very high initial cost, and for those development efforts that get funded and become real-life projects, many will experience additional start-up and retrofit costs from unforeseen electrical issues.
The electrical grid is often called the most complex system ever created as it involves millions of individual devices working simultaneously so that every electron generated is continuously balanced to serve every watt of demand. Although microgrids operate on scales orders of magnitude smaller, this balancing act must still be performed properly to ensure these loads are balanced through a wide range of operating and upset conditions. Performing electrical modeling during development allows you to “bench test” your microgrid’s responses to these changing conditions to avoid startup delays, additional costs and unwelcome surprises. The two project scenarios below detail typical microgrid control and stability issues that were mitigated during development using electrical modeling.
Scenario #1 - Microgrid with Multiple Parallel Units – Controlling Circulating Currents
Large-scale microgrids capable of extended islanding times typical involve a heterogeneous mix of distributed generation (DG) for generation diversity and to lower costs by using existing DGs. DG equipment include solar panels, battery storage, natural gas generators, wind turbines, solar panels, microturbines and fuel cells. Using a mix of DG sources as part of a microgrid almost always require the need to parallel multiple generators or other DG sources with themselves or the utility supply. Controlling circulating currents when paralleling generators in a microgrid that shares a common neutral can be challenging. When DGs are paralleled, it is critical that voltages produced by the generating equipment are as closely matched as possible. To properly match voltages, not only do the DG RMS values need to be similar but the instantaneous values, which are determined by the voltage waveshapes, should be similar as well.
This voltage and waveform mismatch is often experienced with microgrids which attempt to parallel a mix of new and existing isochronous generators with different winding pitch configurations. Circulating currents will likely appear in the common neutral which ties the wye connections of the generating sources. These circulating currents can cause overheating in the generator windings and false tripping of overcurrent protection equipment, particularly ground fault detection schemes. Performing electrical stability modeling during both steady-state and transient conditions allowed the design team to identify circulating currents which would have created problems with the substations neutral grounding resistors during operation if not mitigated during the design phase with reactors.
Scenario #2 - Using Decentralized Autonomous Controlfor Microgrid Stability
Since microgrids are typical deployed to serve critical loads, electrical modeling is also an essential tool to help quantify system availabilities and identify failure modes that can be mitigated during the design phase. This analysis was performed on a microgrid which consisted of supplementing existing solar panels, fuel cells and synchronous stand-by generators with large-scale battery storage to enable long-term islanding during utility outages in addition to peak-shaving in response to economic signals. The initial design of the system involved the use of a central control strategy which presented too much operational risk from single point failures. This control strategy was later revised to a decentralized scheme involving autonomous control of the anchor DGs:
Each of the anchor DG sources autonomously balances the power on the islanded microgrid using a power vs. frequency droop controller. For this specifi c project the new lithium-ion battery and the existing isochronous generators would serve as the anchor generators and perform this using frequency and voltage droop control. The existing fuel cell and the existing photovoltaic inverters were essential for long[1]term islanding and were run in a power mode and therefore do not track load, control voltage or frequency. Modeling was performed for a full spectrum of normal and upset conditions. For example, if a step-load of +20%was to occur while in island operation, what happens to the distribution voltage and frequency waveform as the storage system instantaneously provides the extra power. At maximum output the frequency controls are designed to drop no more than 1%. If there is inadequate energy to meet the load, the frequency will drop below the normal operating range, signaling the non-critical loads to shed. The coordination between sources and loads is through frequency.
Modeling during development also revealed that with small errors in voltage set points between the anchor DGs would result in circulating currents exceeding unit ratings. This analysis showed a need for the battery storage inverters and the isochronous generators to not only control the voltage but to also mitigate circulating reactive currents between the anchor units. This led to a control design utilizing a voltage vs. reactive power droop controller so that, as the reactive power generated by the unit becomes more capacitive, the local voltage set point is reduced. Finally, baseline modeling of the existing loads revealed high reactive power demands which when coupled with the on-site PV inverters operating near unity power factor led to a low power factor at the utility point of common coupling. In order to avoid low power factor costs from the utility, reactive power compensation would be needed. Modeling of this capacitor bank also increased stability during islanding events which further improved overall system resiliency.
Electrical transient and steady-state modeling is essential during microgrid development to ensure the microgrid stability during both grid-parallel and islanded operation. The use of intermittent renewables and existing DGs can often add variables and uncertainties that make this due diligence even more important. It is important that this analysis includes transient events such as separation and automatic re-synchronizing with the grid, Class I level power quality during utility faults, large unbalanced loading and stable operation during major events.
The electrical grid is often called the most complex system ever created as it involves millions of individual devices working simultaneously so that every electron generated is continuously balanced to serve every watt of demand. Although microgrids operate on scales orders of magnitude smaller, this balancing act must still be performed properly to ensure these loads are balanced through a wide range of operating and upset conditions. Performing electrical modeling during development allows you to “bench test” your microgrid’s responses to these changing conditions to avoid startup delays, additional costs and unwelcome surprises. The two project scenarios below detail typical microgrid control and stability issues that were mitigated during development using electrical modeling.
Scenario #1 - Microgrid with Multiple Parallel Units – Controlling Circulating Currents
Large-scale microgrids capable of extended islanding times typical involve a heterogeneous mix of distributed generation (DG) for generation diversity and to lower costs by using existing DGs. DG equipment include solar panels, battery storage, natural gas generators, wind turbines, solar panels, microturbines and fuel cells. Using a mix of DG sources as part of a microgrid almost always require the need to parallel multiple generators or other DG sources with themselves or the utility supply. Controlling circulating currents when paralleling generators in a microgrid that shares a common neutral can be challenging. When DGs are paralleled, it is critical that voltages produced by the generating equipment are as closely matched as possible. To properly match voltages, not only do the DG RMS values need to be similar but the instantaneous values, which are determined by the voltage waveshapes, should be similar as well.
Modeling was performed for a full spectrum of normal and upset conditions. For example, if a step-load of +20%was to occur while in island operation, what happens to the distribution voltage and frequen
Each of the anchor DG sources autonomously balances the power on the islanded microgrid using a power vs. frequency droop controller. For this specifi c project the new lithium-ion battery and the existing isochronous generators would serve as the anchor generators and perform this using frequency and voltage droop control. The existing fuel cell and the existing photovoltaic inverters were essential for long[1]term islanding and were run in a power mode and therefore do not track load, control voltage or frequency. Modeling was performed for a full spectrum of normal and upset conditions. For example, if a step-load of +20%was to occur while in island operation, what happens to the distribution voltage and frequency waveform as the storage system instantaneously provides the extra power. At maximum output the frequency controls are designed to drop no more than 1%. If there is inadequate energy to meet the load, the frequency will drop below the normal operating range, signaling the non-critical loads to shed. The coordination between sources and loads is through frequency.
Modeling during development also revealed that with small errors in voltage set points between the anchor DGs would result in circulating currents exceeding unit ratings. This analysis showed a need for the battery storage inverters and the isochronous generators to not only control the voltage but to also mitigate circulating reactive currents between the anchor units. This led to a control design utilizing a voltage vs. reactive power droop controller so that, as the reactive power generated by the unit becomes more capacitive, the local voltage set point is reduced. Finally, baseline modeling of the existing loads revealed high reactive power demands which when coupled with the on-site PV inverters operating near unity power factor led to a low power factor at the utility point of common coupling. In order to avoid low power factor costs from the utility, reactive power compensation would be needed. Modeling of this capacitor bank also increased stability during islanding events which further improved overall system resiliency.
Electrical transient and steady-state modeling is essential during microgrid development to ensure the microgrid stability during both grid-parallel and islanded operation. The use of intermittent renewables and existing DGs can often add variables and uncertainties that make this due diligence even more important. It is important that this analysis includes transient events such as separation and automatic re-synchronizing with the grid, Class I level power quality during utility faults, large unbalanced loading and stable operation during major events.
