Integration of variable and intermittent sources of electric power

Fig. 2: Upper: Total wind power in Bonneville Power Authority's area, January 2009. After exhibiting normal variability, the wind failed for 11 days. (Source: BPA). Lower: Increased NOx emissions predicted from a natural gas turbine that ramps up and down to follow wind's fluctuations.

Fig. 2: Upper: Total wind power in Bonneville Power Authority’s area, January 2009. After exhibiting normal variability, the wind failed for 11 days. (Source: BPA). Lower: Increased NOx emissions predicted from a natural gas turbine that ramps up and down to follow wind’s fluctuations.


The problem:

Legislation enacted in half the states and proposed in the 111th Congress mandates that 20 to 30% of electric power be produced by “renewable” technologies such as wind and solar. Unlike other generation sources the power output from these sources varies at both long and short time-scales (Figure 2 upper). Natural gas generators are predominantly used to make up for the fluctuations. However, as these generators ramp up and down, their emissions of CO2 and NOx increase over what they would be if the gas turbines ran steadily with no renewables (Figure 2, lower). In increasing wind and solar from 1% of U.S. power generation to 20 times that, a variety of issues such as this will be encountered in the integration of these sources into power systems, meeting reliability, quality, and conventional pollutant emission objectives.

The research:

In 2006, Jay Apt and his colleagues began research to understand the effects on decisions by utilities and regulators of the character of wind and solar power fluctuations using 1-second time resolution data, and the economics of electric storage. With support from the new Center, we will:

  1. develop wind fluctuation models that allow characterization of the phase and amplitude of the power spectrum to be used in wind-farm-scale models;
  2. examine the interaction between fluctuation in wind and solar power and grid frequency stability;
  3. model novel methods of cooperative wind and conventional generator interaction to smooth fluctuations;
  4. model the optimal placement of storage systems such as compressed air energy storage (both conventional and adiabatic CAES) to optimize the utilization of transmission lines that wind or solar’s fluctuations make otherwise uneconomic;
  5. examine the implications of “must-run” renewables on generation portfolio optimization strategies for firms under uncertain fuel availability and cost and gradually tightening pollution caps.

We will begin with engineering/economic and simulation modeling.  We will then explore the application of tools from decision analysis, real options and robust decision making to aid system operators.  It may also prove desirableto apply methods from agent-based modeling and expert elicitation. The work will be done in close cooperation with key players in the power industry, and will directly inform their decisions.

The decision makers:

A123 Systems, American Electric Power (AEP), Bonneville Power Administration (BPA), Caterpillar (CAT), EPRI, International Risk Governance Council (IRGC), NRDC, Ontario Ministry of the Environment, PA PUC, PJM (a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia.), SAP Labs LLC, Westinghouse Electric Corporation.