Introducing lighting controls into a demand response strategy

Intelligent light control systems make lighting predictive, responsive, and linear—and demand response simpler and more economical.

02/25/2013


In basic terms, demand response (DR) is a strategy for managing customer electricity consumption in response to fluctuations in the electrical supply. The overarching goal of DR is to keep electricity supply at a steady and controllable state, and the impetus for DR implementation can vary. It can be motivated by a temporary need to avoid outages resulting from environmental factors (environmental DR) or a more permanent need to manage daily electricity usage for economic considerations. Because electricity is a traded commodity, its price is set by basic supply and demand, and managing daily peaks has an economic advantage (economic DR).   

Figure 1: According to Enerlogic Networks Inc.’s Demand Response Operations Model, regional differences define how DR programs are administrated. Courtesy: Lutron Electronics, based on Enerlogic Networks Inc.Companies are motivated to participate in DR programs based on a variety of factors including how much of their own electricity they produce and the on-site systems that enable them to control, generate, and/or store regulated power. Depending on the area of the country, a company may be dealing directly with the utility bulk supplier (like the manufacturer) or a third party—either a regional transmissions operator (RTO) or independent systems operator (ISO) that coordinates, controls, and monitors grid operation with the use of curtailment service providers (CSPs) that interface with the facility (see Figure 1). Any or all of these entities may be involved in the setup, administration, and control of the DR programs in a given area. Participation requirements, program flexibility, and the existence of nonparticipation penalties vary depending on location, creating a veritable smorgasbord of programs to choose from.

Regardless of which program a company chooses, the higher the risk, the higher the reward. In other words, the faster a company can react to a demand event, the more attractive the economic payback. The incentive to participate may be even greater if a company produces much of its own power, as in a micro-grid. In a micro-grid, a company is responsible for balancing its own power requirements for its building demand independent of the utility. As micro-grids do not have the benefit of gross aggregation to provide a cushion against fluctuations in demand of single buildings, a predictive state and quick reaction to demand events are critical goals. 

Demand response and energy savings

DR often is confused with energy savings. The two can be linked, but they are not interchangeable. The overall goal of DR is to keep the electrical supply at a steady and controllable state, but not necessarily to save energy. It is not unusual, however, for the temporary strategies put in place to achieve DR goals to become permanent strategies to save energy, especially when lighting DR is employed. Annually, lighting and HVAC use in commercial buildings are essentially equal, and both can contribute to an effective DR strategy. But unlike HVAC curtailment, lighting power can be reduced quickly and managed easily, delivering immediate response levels that HVAC can achieve only over time. In addition to responding to demand events, lighting DR strategies also deliver significant energy savings by immediately reducing lighting power with no recovery period required to return to pre-demand levels. The benefits of using both HVAC and lighting DR strategies will be examined in Part II of our series.


Scott Ziegenfus is a senior applications engineer with Lutron Electronics Co. Inc. Ziegenfus has an electrical engineering degree from Lafayette College. He is an educational programs chair and board member for the Delaware Valley Chapter of the U.S. Green Building Council and is a certified LEED Study Guide Facilitator. Ziegenfus also serves on ASHRAE standards committees SPC 201P–Facility Smart Grid Information Model and SSPC 135–BACnet.



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