Dynamic Electricity Pricing to Smart Homes

With the rapid growth in residential smart meters across the United States in recent years, most homes in the United States will soon be capable of moving to time-varying prices for electricity. We develop a methodology for studying the welfare impacts of different pricing strategies on an electricity market when homes deploy smart, price-responsive appliances with forward-looking capabilities. Without assuming any functional form for dynamic prices, we show conditions under which asymptotically, as the number of homes increases, social welfare-maximizing price schedules in equilibrium are linear in load, are the same for all homes, and incrementally equal expected marginal supply costs over equilibrium loads. We provide an algorithm to compute equilibria for a large population. Using real-world data to calibrate a smart thermostat model, we compare this dynamic pricing strategy against flat and peak pricing strategies when smart thermostats are deployed across ComEd's service region of approximately 35 million residential homes. We show that dynamic pricing in equilibrium dominates these competing pricing strategies and measure the expected improvements as smart thermostats are increasingly deployed. As compared against the current status quo of relatively few smart thermostats and flat pricing, we reduce adopters' monthly power bills and generation costs from air conditioning loads by 41% and 35%, respectively, while simultaneously increasing social welfare and consumer surplus. Despite these benefits, supplier surplus from adopters decreases by half.