This paper describes a utility demand-side management (DSM) strategy, built on intensive campaigns with limited geographical coverage, rather than conventional DSM programmes with broad coverage but modest impact. Recent analytic advances in accurately determining utilities' area-specific costs have important implications for DSM design. Unlike the system-level utility costs, which are most sensitive to costs of generation and bulk transmission costs, area-specific costs depend most on distribution and local transmission costs. For utilities with relatively slow total load growth, the latter costs can represent a large share of their current investment needs. If utilities know what their area-specific costs are, they will know where and when their costs are significantly higher than the system average. The timing is important, because costs must be forward looking: once costs are sunk, the opportunities to reduce or defer them are lost. Thus, high-cost areas move around in space and time. Higher costs mean higher avoided costs for DSM, allowing more expensive measures and therefore larger energy and demand savings to be cost-effective. These high-cost areas justify intensive DSM investments - 'blitz' programmes to capture a large energy-saving fraction - in certain places at certain times. With area-specific cost information available, an improved DSM strategy can exploit these opportunities fully where and when they occur, rather than doing broadbased programmes that achieve small savings and low participation rates. After doing a 'blitz' in one target area, one can identify different areas to 'blitz' later. This DSM strategy gives large savings per customer and large participation rates in the target areas, and thus large total savings in that area. This strategy is also shown to be more promising than the conventional approach for maintaining incentives for DSM under utility deregulation. © 1996.
Swisher, J., & Orans, R. (1995). The use of area-specific utility costs to target intensive DSM campaigns. Utilities Policy, 5(3–4), 185–197. https://doi.org/10.1016/0957-1787(96)82791-3