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We use time-and frequency-domain techniques to quantify the extent to which long-distance interconnection of wind plants in the United States would reduce the variability of wind power output. Previous work has shown that interconnection of just a few wind plants across moderate distances could greatly reduce the ratio of fast-to slow-ramping generators in the balancing portfolio. We find that interconnection of aggregate regional wind plants would not reduce this ratio further but would reduce variability at all frequencies examined. Further, interconnection of just a few wind plants reduces the average hourly change in power output, but interconnection across regions provides little further reduction. Interconnection also reduces the magnitude of low-probability step changes and doubles firm power output (capacity available at least 92% of the time) compared with a single region. First-order analysis indicates that balancing wind and providing firm power with local natural gas turbines would be more cost-effective than with transmission interconnection. For net load, increased wind capacity would require more balancing resources but in the same proportions by frequency as currently, justifying the practice of treating wind as negative load.

As installed wind power capacity grows, subhourly variability in wind power output becomes increasingly important for determining the system flexibility needs, operating reserve requirements, and cost associated with wind integration. This paper presents a new methodology for simulating subhourly wind power output based on hourly average time series, which are often produced for system planning analyses, for both existing wind plants and expanded, hypothetical portfolios of wind plants. The subhourly model has an AR(p)-ARCH(q) structure with exogenous input in the heteroskedasticity term. Model coefficients may be fit directly to high-pass filtered historical data if it exists; for sets of wind plants containing hypothetical plants for which there are no historical data, this paper presents a method to determine model coefficients based on wind plant capacities, capacity factors, and pairwise distances. Unlike predecessors, the model presented in this paper is independent of wind speed data, captures explicitly the high variability associated with intermediate levels of power output, and captures distance-dependent correlation between the power output of wind plants across subhourly frequencies. The model is parameterized with 1-minute 2014 plant-level wind power data from Electric Reliability Council of Texas (ERCOT) and validated out-of-sample against analogous 2015 data. The expanded-capacity model, fit to 2014 data, produces accurate subhourly time series for the 2015 wind fleet (a 49% capacity expansion) based only on the 2015 system's wind plant capacities, capacity factors, and pairwise distances. This supports its use in simulating subhourly fleet aggregate wind power variability for future high-wind scenarios. KEYWORDS ERCOT, frequency domain, grid integration, operating reserve, time series, stochastic processes INTRODUCTIONWind power output is variable at all time scales relevant to power system planning and operations, from interannual to subsecond. In order to keep electricity supply and demand in balance and maintain grid reliability, fluctuations in wind power output must be matched by the ramping of other generators or by controllable loads. At low wind power penetration, variability in wind power output does not substantially impact system operations. However, as installed wind capacity increases, system operators begin to face challenges such as excess power generation leading to wind curtailment, underutilization of thermal generators, and increased requirements for fast-ramping reserve.Wind power curtailment and thermal capacity utilization can be quantified using hourly averaged data. A common method is production cost analysis, in which security-constrained unit commitment and economic dispatch are simulated for a given generation portfolio, load time series, and renewable power output time series, typically at hourly resolution. To account for the subhourly system ramping requirements introduced by wind power, operating reserves such as frequency regulation and spinning reserve are schedule...

Pumped hydropower storage can smooth output from intermittent renewable electricity generators, facilitating their large-scale use in energy systems. Germany has aggressive plans for wind power expansion, and pumped storage ramps quickly enough to smooth wind power and could profit from arbitrage on the short-term price fluctuations wind power strengthens. We consider five capacity alternatives for a pumped storage facility in Norway that practices arbitrage in the German spot market. Price forecasts given increased wind capacity are used to calculate profit-maximizing production schedules and annual revenue streams. Real options theory is used to value the investment opportunity, since unlike net present value, it accounts for uncertainty and intertemporal choice. Results show that the optimal investment strategy under the base scenario is to invest in the largest available plant approximately eight years into the option lifetime.