Renewables

Projects Illustrate Strategies for Comprehensive Design Tools

Issue 11 and Volume 118.

by Zach Platsis and Tom Fitzpatrick, SSOE Group

When renewable energy is part of the total energy equation for an industrial plant or utility, a feasibility study provides invaluable cost-benefit information for decision makers. Performed during the planning phase of a project, a feasibility study is an even better value when engineers can generate realistic potential outcomes quickly, easily and cost effectively.

For the solar facility project, engineers used the modeling tool for a cost-effective analysis of 18 initial permutations of project parameters.
For the solar facility project, engineers used the modeling tool for a cost-effective analysis of 18 initial permutations of project parameters.

Comprehensive Renewable Energy Study and Preliminary Design

A leading car and truck manufacturing plant in the south is an instructive example of the benefit of such a feasibility study. In the planning phase, SSOE performed a comprehensive renewable energy study that forecasted cost-benefit information for various design alternatives. Specifically, the engineers used the company’s solar-field computer modeling program to develop a preliminary design that optimized energy production on the proposed site. The study presented options for responding to two major constraints associated with the solar field: a high expectation for renewable energy use and a site that consisted of noncontiguous areas. The solar aspect was only a small part of the overall renewable energy study and initially was not chosen. Instead, Landfill Gas (LFG) Energy was chosen. Only after the manufacturing plant was completed did the manufacturer change back to solar. In the end, the array was designed, built, and is owned by a local solar developer.

As industrial manufacturing facilities go, the plant is a very energy-intensive site. Because it was aiming for LEED certification, the project set a high target for renewable energy.

A comprehensive planning process is about more than information modeling; it is also about bringing all the key players to the planning table. Balancing their interests, needs and values-and measuring these accurately–can be one of the most challenging parts of the planning process. It can also be one of the most productive in terms of a project’s success. Consider the following stakeholders:

  • Building group: project capital cost or payback or both
  • Operations: annual operation and maintenance cost
  • Sustainability: total energy production and LEED-credit value
  • Environment: regulations and permitting
  • Marketing: corporate branding

Although such groups may initially appear as obstacles to project managers, they can offer insights into unforeseen costs, as well as cost-saving opportunities. The operations group, for example, will identify costs associated with O&M – costs that could be addressed by refining the design.

Managing project costs requires the design to maximize the area of the existing site while minimizing construction costs, such as the need to level a hilly site. The locations of the central or distributed inverter system and the array medium voltage transformers also affect project capital cost, to which engineers must assign dollar amounts. They must also factor in additional costs associated with the interests of internal groups and third parties such as regulators and federal, state, and local governments. Using a modeling tool, these costs can quickly be calculated to refine the design and generate cost-benefit data.

uStation Tool

An innovative design tool was developed for use at the Bentley MicroStation, an information modeling environment for architecture, engineering, construction and operation of infrastructure, including utility systems. The software tools let engineers optimize solar arrangements quickly, easily, and cost effectively, especially for large, utility-scale fields. Engineers used software to determine the optimal arrangement of solar panels and to ensure that the configuration would fit within the site.

The tool works in four phases. First, the engineer enters a digital survey drawing, map, or aerial photograph into the modeling tool and traces the perimeter. Second, he specifies potential parameters of the installation, including panel type, panel angle, and arrangement. Third, the tool automatically fills the field and computes the total number of panels that will fit in the space. Finally, the tool is used to compare alternatives based on varying arrangements and panel angles, which enables the engineer to discover the optimal design of the solar field to generate maximum power.

Ohio Solar Facility

A second application of modeling tools is demonstrated by the solar facility in Ohio, a 3.54-MW AC facility with more than 17,000 crystalline silicon panels.

The client opted for a cost-effective, customized solution rather than a third-party developer for a standard turnkey system. Engineers were hired to handle the following tasks: determine the solar capacity of the site; provide basic layouts of the arrays; simulate solar production from multiple layouts and module technologies; complete a full-cost pro forma for the final arrangement; and, lastly, develop specifications for general and electrical construction of the power island.

To assess the feasibility of the project, the engineers analyzed 18 initial permutations of project parameters. These included module technology, panel angle, and space available on the 20-acre site based on various configurations of land usage. They used their company’s solar-field computer modeling program to develop a preliminary design.

The Ohio site is comprised of several parcels of land with varying dimensions and shapes, including one unit with an acute angular perimeter. Allowing for roads, fencing, and shading clearances, the site configuration created several challenges. The first was simply to maximize the number of panels required to generate approximately 4 MW of power. The second was to deploy the system in a heavily wooded site. The third was a requirement for one section to be maintained as green space. Lastly, one section was off limits because of its wetland designation.

Engineers analyzed three module technologies and weighed the advantages and disadvantages of each. The first option-crystalline silicon-historically had the highest initial cost but has since achieved cost parity; it was also the most efficient of the three. Cadmium telluride, the second option, was the lowest in initial cost and efficiency. The third technology-amorphous silicon-was a mid-range solution in initial cost and efficiency.

For the solar facility project, engineers used the modeling tool for a cost-effective analysis of 18 initial permutations of project parameters. This included three module technologies of varying initial costs and efficiencies, three panel angles, and the space available on the 20-acre site based on various configurations of land usage. The engineers ran through various permutations. For example, they moved or removed a row of solar panels to provide shading clearance or road access. They filled more of the angles in the perimeters of the land units. They compared energy production at panel angles of 10, 20, and 30 degrees. By making fine adjustments and avoiding blocked access to infrastructure, they optimized panel angles and maximized the total number of panels that could be fit into the space.

For each configuration, engineers ran a simulation to generate the annual estimated energy output over 25 years. They then associated a cost for that system based on the type and total number of panels. Factoring in site costs, engineers generated an estimated cost pro-forma for each scenario. As a result, they determined that crystalline silicon technology was the most cost-effective technology for this project.

By making the design decisions described in this overview, and by using proprietary software simulation tools to model multiple panel and technology arrangements, SSOE maximized production and minimized risk for the initial development project. Detailed financial modeling and iterations optimized the client’s investment return. As the project demonstrates, owners can develop customized utility-scale solar facilities cost effectively and in a short time period by relying on consulting engineers with the right tools and expertise.

Authors:

Zach Platsis is an Energy Consultant for SSOE Group.

Thomas Fitzpatrick is a Power Department Manager at SSOE Group.

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