Are you having trouble choosing a site for your renewable energy project? Finding a location that offers the necessary grid capacity can be challenging. Fortunately, a shift factor analysis can help.
Once a niche concept in the power engineering industry, shift factor is now a critical puzzle piece for renewable energy developers and other stakeholders trying to determine the feasibility of generation projects and manage grid congestion. This article explains what a shift factor is and why it is important, and shows how the latest modeling tools can expedite shift factor analysis to save you time and money.
A shift factor (also known as DFAX) relates to how much power a single generation project contributes to a specific grid transmission line. Because the grid is a highly complex web, power coming from one project can go in hundreds or even thousands of directions. A shift factor is essentially the percentage of power (1 to 100%) a project is injecting into the network toward any one asset at a given time.
Figure 1: This image shows an issue caused by a new generation project, and the project’s corresponding shift factor of 4%. (Source: EPE InSights software)
Shift factor analysis helps keep the power grid stable by determining which projects to curtail, or turn down. It is critical when congestion or other negative issues come up on a transmission line. To keep power flowing, grid operators must tell certain generators to curtail when there is too much power on the grid. Whether an operator must curtail depends on two factors:
1. Bid price. This is the amount the grid is paying the generator for the energy produced. Generally speaking, the price of fossil fuel power is higher than solar or wind.
2. Shift factor. A generator that has a higher shift factor (because it has more power contributing to the problem on the transmission line) is more likely to have to curtail than a generator with a lower shift factor.
When determining which generators must curtail to avoid overloads and maintain the most cost-effective solution, grid operators use a dispatch algorithm called SCED (security-constrained economic dispatch). This algorithm is designed to find the optimal solution, balancing the total cost of electricity while ensuring the generator dispatches are feasible.
Figure 2: This image illustrates how a generation project is contributing to a shift factor of 10% on one transmission line, and 60% on another line. Notice how the line with the higher percentage is the one closer and more directly connected to the generator’s point of interconnection (POI). (Source: EPE InSights software)
In the past, finding a place to build a solar, wind, or battery storage project was straightforward. Most of the grid had capacity for new generation, so a developer just needed the right parcel of land. But over the last few years, siting has become more challenging.
Out of 100 potential sites where it makes sense for a developer to acquire land and develop a project, 90 might turn out to not have capacity. Why? Because of the ballooning backlog of planned renewable energy projects in the queue. But a shift factor analysis informs developers’ grid strategies by uncovering the real capacity for new renewable projects.
A shift factor is like X-ray vision goggles that reveal a deeper layer of grid capacity that improves the feasibility of your generation projects.
Figures 3 and 4: These images show how a South Texas site that seems undevelopable at first actually has grid capacity when different shift factor assumptions are trialed. (Source: EPE InSights software)
Note that in some cases, depending on the area, shift factor percentages may not be as relevant when factoring in other competitive generation projects and their shift factors.
The job of grid operators is to make sure the grid remains stable under any conditions. They operate on an N-1 contingency basis — keeping power flow at a level where the network will continue to function even during a negative event.
The U.S. power grid is made up of regions, and each region has its own processes for approving new projects. But before any new generation project is approved, grid operators always conduct computationally intensive shift factor analyses to determine the effect the project would have on grid congestion, and whether it would cause a negative issue for transmission lines.
Figure 5: This image illustrates siting a 500 MW solar farm in Morehouse Parish, Louisiana. The shift factor is lower at the Perryville bus. It shows that hosting capacity is available and that upgrade cost estimates will be lower than tapping into lines further south. (Source: EPE InSights software)
In most areas, if the potential project would cause an issue that could be avoided by upgrading the grid, the grid operator then determines the developer’s portion of the shared upgrade costs. Nearby generators would also potentially split the cost, with their share depending on factors like shift factor and MW generated. The developer then would decide whether they want to proceed with the project.
In Texas, project approval takes a different path. ERCOT allows developers to build without paying for any grid upgrades. But after they connect to the grid, generators may not get the ROI they expected for their project because they are forced to frequently curtail their power to prevent overloading.
The process for determining whether the grid has capacity for new projects can be cumbersome and expensive for developers. An engineer must run detailed studies and analyses, and evaluating each site can cost a substantial amount of money. Because of current siting challenges, developers could spend hundreds of thousands or even millions of dollars to study unsuitable sites, not to mention the time wasted.
Fortunately, developers have access to specialized software to speed up the process. These new tools offer highly detailed maps of the grids in different transmission planning regions. They enable users to model a potential generation project’s effect on the grid without having to hire an engineer. The tools take a snapshot in time (summer peak case, for example), allow the user to choose the exact location for a project, and run models to determine whether the grid would have enough capacity.
Figure 6: This image shows a sample area of SPP’s capacity for new generation during relaxed conditions. (Source: EPE InSights software)
The software helps the developer narrow down their site list before proceeding with next steps. By ruling out unfeasible projects, they potentially save hundreds of thousands of dollars and countless planning hours. Amid today’s skyrocketing demand for electrification, the shift factor analysis is an essential tool for uncovering more renewable energy development opportunities.
Consider this hypothetical scenario. A developer is looking to build a 100 MW solar farm in Texas. Using EPE’s InSights software, they can pull up an updated map of ERCOT and model a case, such as summer peak in 2027 and a shift factor of 3. In this situation, the available capacity is limited. But when they increase the shift factor to 10, a lot more capacity becomes available.
Curious to know what your renewable project’s shift factor will be? Schedule a free demo of our EPE’s InSights tool and find out how to streamline site selection.
