Electric utility companies today constantly struggle to find a balance between generating sufficient power to satisfy their customers’ dynamic load requirements and minimizing their capital and operating costs. They spend a great deal of time and effort attempting to optimize every element of their generation, transmission and distribution systems to achieve both their physical and economic goals.
In many cases, “real” generators waste valuable resources – waste that if not managed efficiently can go directly to the bottom line. Energy companies therefore find the concept of a “virtual generator,” or a virtual source of energy that can be turned on when needed, very attractive. Although generally only representing a small percentage of utilities’ overall generation capacity, virtual generators are quick to deploy, affordable, cost-effective and represent a form of “green energy” that can help utilities meet carbon emission standards.
Virtual generators use forms of dynamic voltage and capacitance (Volt/ VAr) adjustments that are controlled through sensing, analytics and automation. The overall process involves first flattening or tightening the voltage profiles by adding additional voltage regulators to the distribution system. Then, by moving the voltage profile up or down within the operational voltage bounds, utilities can achieve significant benefits (Figure 1). It’s important to understand, however, that because voltage adjustments will influence VArs, utilities must also adjust both the placement and control of capacitors (Figure 2).
Various business drivers will influence the use of Volt/VAr. A utility could, for example, use Volt/VAr to:
- Respond to an external system-wide request for emergency load reduction;
- Assist in reducing a utility’s internal load – both regional and throughout the entire system;
- Target specific feeder load reduction through the distribution system;
- Respond as a peak load relief (a virtual peaker);
- Optimize Volt/VAr for better reliability and more resiliency;
- Maximize the efficiency of the system and subsequently reduce energy generation or purchasing needs;
- Achieve economic benefits, such as generating revenue by selling power on the spot market; and
- Supply VArs to supplement off-network deficiencies.
Each of the above potential benefits falls into one of four domains: peaking relief, energy conservation, VAr management or reliability enhancement. The peaking relief and energy conservation domains deal with load reduction; VAr management, logically enough, involves management of VArs; and reliability enhancement actually increases load. In this latter domain, the utility will use increased voltage to enable greater voltage tolerances in self-healing grid scenarios or to improve the performance of non-constant power devices to remove them from the system as soon as possible and therefore improve diversity.
Volt/VAr optimization can be applied to all of these scenarios. It is intended to either optimize a utility’s distribution network’s power factor toward unity, or to purposefully make the power factor leading in anticipation of a change in load characteristics.
Each of these potential benefits comes from solving a different business problem. Because of this, at times they can even be at odds with each other. Utilities must therefore create fairly complex business rules supported by automation to resolve any conflicts that arise.
Although the concept of load reduction using Volt/VAr techniques is not new, the ability to automate the capabilities in real time and drive the solutions with various business requirements is a relatively recent phenomenon. Energy produced with a virtual generator is neither free nor unlimited. However, it is real in the sense that it allows the system to use energy more efficiently.
A number of things are driving utilities’ current interest in virtual generators, including the fact that sensors, analytics, simulation, geospatial information, business process logic and other forms of information technology are increasingly affordable and robust. In addition, lower-cost intelligent electrical devices (IEDs) make virtual generators possible and bring them within reach of most electric utility companies.
The ability to innovate an entirely new solution to support the above business scenarios is now within the realm of possibility for the electric utility company. As an added benefit, much of the base IT infrastructure required for virtual generators is the same as that required for other forms of “smart grid” solutions, such as advanced meter infrastructure (AMI), demand side management (DSM), distributed generation (DG) and enhanced fault management. Utilities that implement a well-designed virtual generator solution will ultimately be able to align it with these other power management solutions, thus optimizing all customer offerings that will help reduce load.
HOW THE SOLUTION WORKS
All utilities are required, for regulatory or reliability reasons, to stay within certain high- and low-voltage parameters for all of their customers. In the United States the American Society for Testing and Materials (ATSM) guidelines specify that the nominal voltage for a residential single-phase service should be 120 volts with a plus or minus 6-volt variance (that is, 114 to 126 volts). Other countries around the world have similar guidelines. Whatever the actual values are, all utilities are required to operate within these high- and low-voltage “envelopes.” In some cases, additional requirements may be imposed as to the amount of variance – the number of volts changed or the percent change in the voltage – that can take place over a period of minutes or hours.
Commercial customers may have different high/low values, but the principle remains the same. In fact, it is the mixture of residential, commercial and industrial customers on the same feeder that makes the virtual generation solution almost a requirement if a utility wants to optimize its voltage regulation.
Although it would be ideal for a utility to deliver 120-volt power consistently to all customers, the physical properties of the distribution system as well as dynamic customer loading factors make this difficult. Most utilities are already trying to accomplish this through planning, network and equipment adjustments, and in many cases use of automated voltage control devices. Despite these efforts, however, in most networks utilities are required to run the feeder circuit at higher-than-nominal levels at the head of the circuit in order to provide sufficient voltage for downstream users, especially those at the tails or end points of the circuit.
In a few cases, electric utilities have added manual or automatic voltage regulators to step up voltage at one or more points in a feeder circuit because of nonuniform loading and/or varied circuit impedance characteristics throughout the circuit profile. This stepped-up slope, or curve, allows the utility company to comply with the voltage level requirements for all customers on the circuit. In addition, utilities can satisfy the VAr requirements for operational efficiency of inductive loads using switched capacitor banks, but they must coordinate those capacitor banks with voltage adjustments as well as power demand. Refining voltage profiles through virtual generation usually implies a tight corresponding control of capacitance as well.
The theory behind a robust Volt/ VAr regulated feeder circuit is based on the same principles but applied in an innovative manner. Rather than just using voltage regulators to keep the voltage profile within the regulatory envelope, utilities try to “flatten” the voltage curve or slope. In reality, the overall effect is a stepped/slope profile due to economic limitations on the number of voltage regulators applied per circuit. This flattening has the effect of allowing an overall reduction, or decrease, in nominal voltage. In turn the operator may choose to move the voltage curve up or down within the regulatory voltage envelope. Utilities can derive extra benefit from this solution because all customers within a given section of a feeder circuit could be provided with the same voltage level, which should result in less “problem” customers who may not be in the ideal place on the circuit. It could also minimize the possible power wastage of overdriving the voltage at the head of the feeder in order to satisfy customers at the tails.
THE ROLE OF AUTOMATION IN DELIVERING THE VIRTUAL GENERATOR
Although theoretically simple in concept, executing and maintaining a virtual generator solution is a complex task that requires real-time coordination of many assets and business rules. Electrical distribution networks are dynamic systems with constantly changing demands, parameters and influencers. Without automation, utilities would find it impossible to deliver and support virtual generators, because it’s infeasible to expect a human – or even a number of humans – to operate such systems affordably and reliably. Therefore, utilities must leverage automation to put humans in monitoring rather than controlling roles.
There are many “inputs” to an automated solution that supports a virtual generator. These include both dynamic and static information sources. For example, real-time sensor data monitoring the condition of the networks must be merged with geospatial information, weather data, spot energy pricing and historical data in a moment-by-moment, repeating cycle to optimize the business benefits of the virtual generator. Complicating this, in many cases the team managing the virtual generator will not “own” all of the inputs required to feed the automated system. Frequently, they must share this data with other applications and organizational stakeholders. It’s therefore critical that utilities put into place an open, collaborative and integrated technology infrastructure that supports multiple applications from different parts of the business.
One of the most critical aspects of automating a virtual generator is having the right analytical capabilities to decide where and how the virtual generator solution should be applied to support the organizations’ overall business objectives. For example, utilities should use load predictors and state estimators to determine future states of the network based on load projections given the various Volt/VAr scenarios they’re considering. Additionally, they should use advanced analytic analyses to determine the resiliency of the network or the probability of internal or external events influencing the virtual generator’s application requirements. Still other types of analyses can provide utilities with a current view of the state of the virtual generator and how much energy it’s returning to the system.
While it is important that all these techniques be used in developing a comprehensive load-management strategy, they must be unified into an actionable, business-driven solution. The business solution must incorporate the values achieved by the virtual generator solutions, their availability, and the ability to coordinate all of them at all times. A voltage management solution that is already being used to support customer load requirements throughout the peak day will be of little use to the utility for load management. It becomes imperative that the utility understand the effect of all the voltage management solutions when they are needed to support the energy demands on the system.