TELVENT - Renew Grid; The Interplay Between Distribution Automation and Demand Response
by Jeff Meyers, head of smart grid strategy and development.
Managing peak load is one of the most critical drivers in the utility industry, even though the slow economy has resulted in flatter load growth. With rising fuel and construction costs, as well as the long lead time required to plan for and build generation resources, many utilities are concentrating on using a smarter grid to help delay or even eliminate constructing new plants.
In fact, the majority of smart grid projects coming online are focused on reducing peak load and using a variety of technologies - including distributed renewables and energy storage.
In addition, customer-incented load reduction and grid optimization techniques are among the most promising initiatives to reduce demand. As smart metering and building technologies proliferate, demand-response (DR) programs are growing in number and sophistication. Some utilities have implemented advanced distribution management systems (DMS) to optimize the network for voltage and VARs using a technique called distribution system DR (DSDR) to reduce peak demand.
These two approaches try to address the peak load problem by starting from different points. DR works from the demand side, while DSDR seeks to make the supply side more efficient. Each method can be effective at limiting peak load. A closer look at both ideas gives a sense of the current technology, and provides a picture of a future where both supply and demand management are combined to create a holistic approach to controlling peak load.
DSDR: The 'other' DR approach
Making the distribution system more efficient seems like a worthwhile goal. Most distribution systems have plenty of headroom when it comes to operating efficiency, including managing voltage and VARs for optimum performance. Some utilities are discovering that, among many other benefits of distribution automation (DA), significant peak reductions can be achieved through implementing a DSDR approach to peak load management from the supply side.
DSDR reduces load by reducing voltage. Voltage drop is an inherent characteristic of all distribution feeders; voltage is higher near the source substation and declines the further each load is electrically from the source. Providing adequate voltage is often the key driver in feeder configuration. DSDR works by flattening the voltage profile of feeders in the system under normal operating conditions, providing margin to reduce voltage under emergency or peak load conditions.
The DSDR concept involves both information technology (IT) and operations technology (OT) improvements. Changes and additions to OT usually include adding more voltage regulation and capacitive reactance, and may also involve switches and tie-line additions to increase operating flexibility. IT improvements involve using advanced analytics to monitor and control voltage and VARs, keeping the system within a tight operating range for normal conditions.
It is this optimization that enables the distribution operator to reduce voltage under peak conditions without compromising system reliability. When system voltage is reduced, all real power loads are reduced in proportion.
Of course, volt/VAR optimization is not trivial, especially in large and complex distribution systems. In order to operate the distribution grid within a tight range of parameters, a detailed network model and a highly advanced analytical engine are required. This is where a tool like an advanced DMS earns its keep, monitoring and controlling the grid as load and configuration change. The system manages complexities, becoming the 'better brain' of the smart grid.
DSDR benefits can be significant. Depending on the characteristics of the utility, including generation profile and distribution configuration, savings of 1.5% to 3% in peak are within reach for many companies. Because DSDR typically replaces peaking power that is generated or purchased at the highest incremental cost, the savings are substantial.
Customer-facing DR
A number of DR models are currently in play, but all rely on the basic idea that a customer can achieve economic (and possibly other) benefits by altering or reducing load at certain times.
There are simple direct load-control schemes, where the network operator can send a signal to turn off certain appliances and equipment. The more sophisticated methods are based on time-of-use tariffs, which allow the customer to decide on energy usage by using pricing signals. In all cases, DR programs aim to reduce peak by offering incentives to the customer.
Many grid operators interact directly with customers through such programs, while others choose to engage an aggregator to manage DR programs. Aggregators sell DR services by offering rate incentives to end-use customers. Aggregators then broker total peak load reductions to the grid operator (or, sometimes the transmission or generation operator). Some industry observers posit that the expansion of smart meters will make it easier and more desirable for the utility to have a direct DR relationship with its customers, potentially eliminating the role of the aggregator.
Although smart meters provide a potential platform for extending DR capabilities to all electric customers, the nature of load at most utilities dictates that the key targets for demand management are usually commercial and industrial (C&I) customers.
On average, C&I loads make up 4% to 8% of the metered customers, but represent 60% to 80% of peak load, so they constitute a fertile field for DR-based peak reduction. Further, because of the rapid growth in smart building technology, many larger electrical consumers are better equipped to automate the management of their energy usage while minimizing the impact on overall operations.
In fact, smart building technology has progressed to include managing energy and demand in an integrated environment with process and machines, IT and server rooms, building asset and security management - all under a single umbrella. By implementing an integrated smart buildings toolset, college campuses, factories and large commercial and retail operations can see significant savings in energy and demand costs - as much as 2.5% to 5% or more – without a noticeable impact in commercial operations.