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In recent years, integration of renewable resources has been growing for many grid operators, with the expansion being spurred on by the advancement of technology and capital cost reduction, particularly of wind and solar generation. Typically, the goal is to lower the overall production cost (mostly fuel cost) and/or emissions by replacing generation from traditional thermal units, but a desire for fuel diversity and other region-specific objectives may also play a part.

Regardless of the specific goal, maximizing renewable generation is largely achieved by minimizing curtailments. The various wind and solar integration studies performed to date point out the need for system flexibility to accommodate the intermittency and variability of these resources. Study recommendations generally focus on enhanced ancillary services and transmission expansion that help balance the system while maximizing the renewable potential.

Typically, system flexibility is assumed to be provided by the existing thermal and/or hydro generators, demand response or storage. The transmission system helps by increasing renewable resource diversity, reducing the aggregated net load variability and allowing the system operator to draw the required flexibility from a larger pool of resources; these are benefits of a large interconnected system. The underlying assumption is that the transmission system has a fixed capacity and topology and, therefore, is not a source of any operational flexibility to help reduce renewable curtailments.

Curtailments of renewable resources occur largely for two reasons: minimum generation limits of the traditional thermal and/or hydro units, and the lack of transmission capacity. Curtailments due to minimum generation limits occur when the output of the non-renewable units – needed for providing energy or ancillary services – cannot be reduced and is higher than the net load. Under these circumstances, renewable resources will be curtailed until the net load becomes higher than the minimum generation limit of the non-renewable units.

Curtailments also occur when the renewable resources – often built far from the load centers – are unable to send power to serve load because the transmission system cannot accommodate additional transfers. Increasing transfer capabilities will reduce renewable curtailments for the latter reason but also, in some cases, can reduce minimum generation-related curtailments. This is because increased transfer capability allows the system operator to secure the needed energy or ancillary services from a larger group of resources that may have lower minimum generation limits.

Traditionally, increasing transfer capability was addressed by upgrading existing lines or adding new lines, both of which require intense capital expenditure and multiple years of planning, on top of the various regulatory hurdles and stakeholder management.

However, options with a lower cost and faster turn-around to increase the transfer capability of transmission systems have been developed in recent years.

The transfer capability of transmission facilities is defined largely by two factors: the physical transfer capability of individual lines and the network topology of these lines. The transfer capability of individual lines is defined primarily by the temperature of the line, which directly affects how much the line will sag. Line temperature increases as more power flows, due to the resistive heating phenomenon. The temperature is also affected by the ambient conditions and the resulting cooling effects of the physical lines. Topology defines the distribution of the flows (including parallel flows or loop flows) based on Kirchhoff’s Law.

Currently, both the transfer capability and topology are generally considered to be fixed with little to no flexibility. However, new technologies are being developed to explore the application of both the transfer capabilities and system topologies, and will significantly contribute to reducing renewable curtailment. Examples of such technologies include dynamic line ratings, adaptive line ratings and transmission topology control.

Dynamic line ratings. Dynamic line ratings and adaptive line ratings address the transfer capability of individual lines. An individual line’s transfer capability is rated under a very conservative set of conditions. Dynamic line ratings improve upon this rating by using real-time measurements from the field, thereby estimating more accurately the ambient condition’s cooling effects of the lines.

Ambient conditions including air temperature, humidity level and wind speed impact the cooling effect. For example, windier conditions will have increased cooling effects and can lead to higher transfer capabilities. This can be ideal for reducing wind curtailments because when the wind is stronger, the wind plants can generate more, and the increased transfer capability allows the delivery of energy from these wind plants.

A dynamic line rating study performed by Oncor Electric Delivery Co. in 2013 showed that significant congestion mitigation can be obtained with as little as a 5% to 10% increase in capacity over the currently used line ratings. The Oncor study demonstrated that the effective congestion mitigation could be in the range of 60% to 100% on the lines monitored. Although this study analyzed only 12 representative days, a 5% increase in transfer capability using dynamic line ratings is assumed to lead to a 3% reduction in annual wind curtailment, with the largest monthly reduction exceeding 40%. Other systems in the U.S. and Europe have been studying this technology as well.

Investment required for dynamic line ratings is mostly in the new hardware for measuring the ambient conditions (temperature, wind, humidity) or the actual sag level of the transmission lines. There are no needs to build new lines or gain the rights of way for new paths.

Adaptive line ratings. Adaptive line ratings change the post-contingency transfer capability based on the length of time the system takes to respond to a contingency event. Normally, a conservative estimate of the response time is used to calculate the post-contingency transfer capability. With a more accurate time estimate, adaptive line rating allows the post-contingency rating to be higher, with the knowledge that the system can reduce the post-contingent flow before the line temperature reaches its limit. Because most transmission constraints tend to be contingency constraints, increasing post-contingency transfer capabilities can be very effective in reducing congestion and associated renewable curtailments.

Figures 1 and 2 illustrate an example of how the transfer limit can be increased for a contingency event with a fast response time.



ISO New England anticipates that implementing adaptive line ratings would increase post-contingency ratings by 11% on average, and eliminate congested bottlenecks 44% of the time. Implementation of this technology does not require any hardware and can be done by modifying or enhancing operational (and planning) software.

Transmission topology control. Transmission topology control attempts to improve the overall transfer capability of the system by changing the distribution of the power flow on any individual line. For a given system, the flow distribution will depend on location and levels of generation and load, and the transmission topology that connects the generators and loads. By strategically opening and closing certain lines, this technology can redistribute the flow from a constrained part of the system to other parts of the system. This has been done in the past for reliability reasons.

For example, it has been a common practice to open a constrained low voltage line if the load can be carried on a higher voltage line. However, these operations were based on the operators’ experience and not part of any formulated operational procedure.

Some recent developments of topology control, including an Advanced Research Projects Agency - Energy (ARPA-E)-funded project (led by the authors of this article), focus on software that allows the system operator to systematically open and close lines to control topology.

Interim results of the ARPA-E project indicate an up to 30% increase in transfer capability between regions of PJM and an up to 50% reduction in renewable curtailments under a 30% renewable penetration scenario. Figures 3 and 4 show an example of curtailment reduction for one early morning off-peak hour during winter.



Investments required for implementing this technology are mainly on software development and expected to require few hardware upgrades. To achieve similar control of the flow distribution through other means would be prohibitively expensive.

For example, phase angle regulators (PARs) are known to control flow distribution. A recently installed PAR between Michigan and Ontario has an annual carrying cost of over $10 million. To control flow on a system level, numerous PARs would need to be built throughout the system.

As these examples demonstrate, new emerging technologies that allow flexible operation of the transmission systems to increase the transfer capability of the existing physical system seem to provide a promising benefit for increasing renewable penetration and reducing their curtailment.

In general, these emerging technologies require minimal capital investment and require less turn-around time to implement them than the traditional option of adding PARs or upgrading the existing transmission system.

It should be emphasized that these technologies are not replacements for transmission expansion. Rather, these technologies should be reviewed as complementary to longer-term system expansion solutions; they increase system flexibility in circumstances in which a transmission expansion option is not possible due to economic or regulatory reasons. w


T. Bruce Tsuchida is principal, Xiaoguang Li is consultant and Pablo A. Ruiz is senior associate at The Brattle Group, a Boston-based consultancy. The authors are electrical and mechanical engineers working as engineering and economic consultants with a focus on renewable integration, electricity markets, power systems planning and operations. They are core members of an ARPA-E project led by Boston University developing topology control algorithms. They can be reached at bruce.tsuchide@brattle.com, xiao.li@brattle.com and pablo.ruiz@brattle.com.

Industry At Large: Wind Integration

Reducing Renewable Curtailments Through Flexible Operation

By T. Bruce Tsuchida, Xiaoguang Li & Pablo A. Ruiz

Newly developed technologies could significantly help the integration of clean energy, such as wind and solar, into the grid.





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