Planning for High Levels of Variable Renewable electricity - Analysis, Data and Stakeholders

KEY POINTS:

Integrating high levels of variable renewables into the electricity system requires an evolution in system planning to reflect the unique characteristics of solar and wind resources.

These resources, similar to hydro and geothermal resources, are location-specific and can be far from load centers, thus their development may require additional transmission and changes to transmission planning. Solar and wind generation also fluctuate due to weather patterns that cannot be perfectly predicted. Managing the variability and uncertainty of these resources involves planning for flexible electricity systems that can respond quickly to changes in supply and demand, for example, through novel operational practices , flexible generation , demand response , and storage . Finally, unlike conventional generation, wind and solar energy are non-synchronous, that is, they do not consistently operate at the frequency of the electricity system. Increasing the share of non-synchronous generation may require additional studies and changes to requirements for ancillary services, which help to ensure the continuous balance of demand and supply.

Novel data inputs and analyses can complement traditional planning methods to prepare the electricity system for higher levels of variable renewables while maintaining reliability and cost- effectiveness.

In particular, grid integration studies offer an analytical framework for evaluating power systems with high penetrations of variable renewables. These studies simulate electricity system operations under various renewables penetration scenarios, identify reliability constraints, and determine the relative costs of integration options. Such studies provide policy makers, system operators, and regulators with insights on the impacts of and solutions for renewable deployment, addressing concerns that a system can reliably and cost-effectively operate under various renewable electricity scenarios [1,2,3,5,6].

Grid integration studies  can draw on a variety of methods  and models, based on system- specific priorities.

Typically, grid integration studies use one or more of the following approaches to analyze the impacts of variable renewable energy resources:

?     Capacity expansion analyses identify where, when, and how much of different types of generation or transmission resources would achieve renewable electricity and other system goals at least capital and operational cost. These analyses often model 20 to 50 years into the future, with simplified spatial and temporal resolution, and without detailed analysis of operational and reliability impacts.

?     Production cost analyses assess the impacts of renewable electricity scenarios on system operations by determining the least-cost generator scheduling and dispatch needed to meet demand. These analyses can evaluate the operational feasibility of high renewable electricity  penetrations by assessing metrics such as renewable electricity  generator curtailment rates, generator ramping, plant load factors, emissions and operational costs. They will typically only model one year at a time, usually 5-10 years into the future, for each hourly or sub-hourly dispatch interval of the year.

?     Power flow analyses can include steady-state load flow, contingency, and dynamic stability assessments. They validate the ability of a system to operate reliably and respond to real- time disturbances such as unplanned outages. These models typically are not concerned with costs but instead focus on system reliability during a few key instances throughout the year at very high temporal resolution (sub-second to minutes).

While each type of analysis uses distinct methodologies, the results from one can inform the structure of another (Figure 1). For instance, results for the timing, placement and size of new generators and transmission from a capacity expansion analysis can be used as inputs to test for operational feasibility in a production cost model, which in turn can be used to identify ‘periods of interest’ (e.g. times of low demand and high renewable energy supply or vice versa) to be studied in a power flow analysis.

Figure 1: Depending on the priorities of stakeholders, grid integration studies can draw upon a variety of different analyses to examine the trade-offs and benefits of different variable renewable energy scenarios. This chart shows how different types of analyses can be iteratively implemented in order to arrive at a particular policy development [2].

Quality data, especially  concerning the spatial and temporal variability of renewable energy resources, are crucial to robust, reliable grid integration analysis.

High resolution  spatial resource data offer accurate, site-specific characterization of resource availability and can capture grid integration trade-offs among different renewable electricity siting strategies. High resolution temporal data (hourly or sub-hourly) are also essential to understand the operational and reliability implications of different renewables scenarios. For operational studies, solar and wind resource data that are time-synchronous with load data (i.e. the timesteps are of similar duration and align chronologically) are essential to capture correlations among weather, variable renewable electricity generation, and electricity demand. High resolution solar and wind resource data can be generated using models incorporating multiple years of historic data to capture inter-annual variability and extreme events. Calibrating modeled data using ground measurements is a best practice.

Grid integration studies also require detailed data to characterize load (magnitude, location, timing of historic and future electricity demand, etc.); generator, demand response and storage capabilities and costs; transmission infrastructure constraints; and (if available) forecast error for load and renewable resource availability [4]. These data can be acquired from vendors, energy agencies, regulators, generation and transmission companies, research organizations, and other electricity sector stakeholders.

Active stakeholder engagement helps ensure credible and relevant results.

Grid integration studies that engage a broad range of stakeholders at every step contribute to robust and actionable planning grounded in realistic assumptions that reflect industry and policymaker concerns (Figure 2). Relevant stakeholders for such studies are energy agencies, system operators, regulators, utilities, transmission providers, generation owners and operators, and researchers. Establishing a Technical Review Committee (TRC) and a Modeling Working Group (MWG) is best practice for stakeholder engagement in grid integration studies. A TRC provides strategic input and guidance from a broad group of stakeholders. TRCs determine study objectives, core assumptions, and scenarios; review methods and data sources; interpret results and translate them to policy or regulatory action; and endorse the rigor and validity of the study. The MWG conducts the detailed analysis; leads data collection, validation and model development; verifies results; compiles technical documentation; and communicates findings.

Figure 2: Grid integration studies offer an analytical framework for evaluating the ability of a power system to incorporate high levels of renewable energy economically, while meeting reliability requirements. A grid integration study consists of four key steps (data collection, scenario development, power system modeling and analysis and reporting) with relevant stakeholder input cultivated at each step [1].

Grid integration  studies  can  give  electricity  system planners the  confidence and  evidence needed to establish  and take steps to achieve  ambitious renewable electricity  and power sector development  goals.

For example, a recent grid integration study for India used  a production cost  model to confirm the technical and  economic viability of reaching  the  Government of India’s  policy target of 175 GW renewable energy by 2022 (which includes  160  GW of wind and solar resources). The study also evaluated strategies to improve system flexibility, and found, for example, that coal plant flexibility will be key to meeting  solar and wind targets and that coordinating  scheduling and dispatch at the regional and  national  level (instead of the  state level) would lower electricity  system operational costs. More than  150 experts and various  institutions offered  technical review and guidance throughout the  study to ensure accurate assumptions and actionable results that can inform the transformation of India’s electricity system [5].

References

[1] Katz, J. and Chernyakhovskiy, I, (2016), Grid Integration Studies: Advancing Clean Energy Planning and Deployment. NREL/TP-6A20-6650. Golden, CO: National Renewable Energy Laboratory.

[2] Katz, J. and Chernyakhovskiy, I. Forthcoming. Variable Renewable Energy Grid Integration Studies: A Guidebook for Practitioners. Golden, CO: National Renewable Energy Laboratory.

[3] Bloom et al, (2016), Eastern Renewable Generation  Integration Study.  NREL/TP-6A20-64472. Golden, CO: National Renewable Energy Laboratory.

[4] Katz, J, (2015), Grid Integration Studies:  Data Requirements. NREL/FS-6A20-6304. Golden, CO: National Renewable Energy Laboratory.

[5] Palchak et al, (2017), Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India’s Electric Grid, Vol. I—National  Study. Golden, CO: National Renewable Energy Laboratory.

[6]  Holttinen  et al, (2013),  Expert  group  report  on recommended practices (16. Wind Integration Studies). Technical Report Edition 2013.

[7] Milligan, M. and Katz, J, (2016), The Evolution of Power System Planning with High Levels of Variable Renewable Generation. NREL/TP-6A20-6303. Golden, CO: National Renewable Energy Laboratory.