Preparing your grid for flexible operation as renewable resource advance
The investment in renewable resources, particularly photovoltaic (PV), has the potential to become substantial for certain feeders. Adoption patterns are being studied to understand the influences from natural socioeconomic and spatial neighbor effects to policy-influenced deployment, driven by programs such as “shared solar” or “community-based solar”. Minor levels of adoption will initially provide minimal load reduction or peak shaving; however, when adoption rates reach a critical mass they can offer more than simply load control. PV injection can be applied to substantially improve the power quality of the grid’s operation.
Power quality is a problem faced by utilities worldwide. Problems such as high feeder losses related to reactive power flows and feeder voltage problems are serious operational issues in many locations. Whereas many utilities initially addressed the smart grid by installing self- healing technology to improve feeder reliability, they didn’t consider the quality problems that were imposed on the affected feeders caused by sudden load shifts when unfaulted loads were transferred to backup circuits. These technologies must be considered in synergism with one another.
If these dynamic operational power quality deficits can be improved or resolved through renewable resource investment, its smart deployment will enhance the initial financial justification based on load control alone. Renewable resources can be utilized to shorten the repayment period of the investment through strategic automation of the resource by improving the costly power quality issues related to optimized grid operations.
The question is, are the renewable resources being positioned to maximize their operational effectiveness?
Ownership that Maximizes Effectiveness
Whoever owns the resource may have a large impact on the effectiveness of the resource in grid operations and its significance with regards to financial payback. Typically, government subsidies which provide economic incentives to encourage renewable investment often favor private participation rather than utility-owned deployment. The ability to maximize the operational benefit of the resource is largely affected by ownership. For example:
If the renewable resource is privately owned and installed, the value to the utility may be limited since the resource’s functional objective may be restricted to the load that it serves. Its primary use case will likely be targeted to reduce the owner’s billable load. The added expense of deploying complex controllers that can leverage the resource’s operational advantage may not be recognized as an important feature by the private owner. The public-owned resource’s effectiveness may be of value to the utility only during extreme situations, such as emergency conditions, related to the high cost of energy or microgrid operation. However, under normal operational conditions, its value will be primarily for the benefit of the owner in reducing energy consumption.
If the renewable resource is utility-owned, its value to grid operations can be exploited for broader operational impact, which includes lowering feeder operational costs while improving the feeder’s energy transfer capability. Since these objectives transcend the DER’s benefit to the load alone, the added investment in enabling dynamic control capability would be recognized to be of value only by the utility.
To maximize the advantage of the resource, its operation must be integrated into the operational infrastructure of the DMS/ADMS and DERMS. The overall data collection and control architecture, and the interfaces that are needed, must be established to enable the flexible operation of the renewable resource in its participatory role in a wide range of use cases.
DER Interfaces that Improve Effectiveness
Unfortunately, many of today’s smart inverters are designed for minimum current capability to reduce the inverter cost. This design consideration limits the control usability of the resource. A typical DER, such as a PV inverter, is rated as follows:
Wmax: maximum real power output
VAmax: maximum apparent power
VArmax; maximum reactive power, injection or absorb
Amax/rms: maximum AC current
In many cases, the name plate ratings define the operating limits of the DER. However, the ratings do not infer that the inverter offers dynamic set point operational control of the four-quadrant output. It must be understood that control adjustments to some classes of “smart inverters” are intended to be a manual on-site adjustment.
In many cases, the output setting is a voltage setting, and does not allow for the DMS/DERMS to issue a feeder strategic VAR setting to inject or absorb reactive power for the overall benefit of the feeder’s electrical power quality. This shortcoming may limit the DER’s effectiveness towards a strategic control ensuring the feeder’s viability. In this instance, the DER’s function independently of each other at their point of common coupling (PCC).
Strategically, to derive the maximum financial and operational benefit of the DERs, it is necessary to orchestrate their operation to the optimal operational profile for each feeder. The feeder’s operational security and effectiveness for all loads is achieved when maximum renewable injection can be achieved at minimum feeder losses, operating under a flattened, minimum voltage profile. This objective is achieved when all the available resources of the feeder are operated in a single harmonized control scheme, driven by the dynamic feeder automation application.
Role of the DERMS
The real-time application that calculates the optimum settings of each feeder will have different smart grid objective functions. The synergistic operationally critical DERMS functions include:
To meet these objectives, the effective real-time control of the feeder’s resources will encompass a three-pass control loop ranging from course to intermediate to fine control of the feeder’s operation. The devices that must be considered and controlled to achieve the optimum operation includes the following:
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