Business Plan and Detailed Technical Design

Presented for the U.S. Department of Energy Marine Energy Collegiate Competition 2020-2021

Lightning: A Wave Energy Converter to

Power the Future of Ocean Observation

by Obseaver Marine Energy

Oregon State University

Christian Bergin Courtney Beringer Diane Brandt Megan Carlson-Funk Chris Dizon Daniel Gaebele Andres Gonzalez Carson Gray Leila Kenner Deven Leon-Patino Nicholas May-Varas Jorren Mills Paris Myers Nicholas Touchette Carson Williams

Faculty Advisors: Bryson Robertson and Pedro Lomónaco

Table of Contents Executive Summary ...... 3 Business Plan ...... 5 Concept Overview ...... 5 Relevant Stakeholders ...... 6 Market Opportunity ...... 7 Development and Operations ...... 12 Detailed Technical Design ...... 13 Design Objective ...... 13 Design Details ...... 15 Hydrodynamic Modeling ...... 17 WEC-Sim Modelling...... 18 Analytic Model of Reduced Dynamics ...... 23 Incorporation of Environmental and Sustainability Factors...... 25 References...... 26

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Executive Summary

Our team investigated an attenuator style wave energy converter (WEC). This device, named The Lightning, has two floats that rotate around a center nacelle which houses the power take-off system (Figure 1). Our goal was to create a low impact wave energy convertor to house an array of oceanographic sensors and instruments that could collect quality data year-round regardless of sea-state (through WEC stabilization control), greatly reduce the need for expensive boat time (through longer deployments), and mitigate the current issues of power access (through generation of renewable wave power). These are our social, technical, environmental, and financial goals. To meet these goals, we designed the power electronics and controls to meet the needs of a suite of oceanographic sensors. The design includes a mounting system for sensors and a rechargeable battery, as well proof of concept for a stabilizing control algorithm that aims to reduce the WEC motion in harsh sea conditions.

Figure 1: Attenuator style WEC used in collaboration with our industry mentor, C-Power

Ocean observation is federally required to monitor environmental impacts and is also central in academia and industry to observe and react to the health and conditions of our oceans. Therefore, we proposed a business, named the Obseaver Marine Energy to provide a versatile WEC platform for various oceanographic sensors: acoustic sensors, pH monitors, temperature sensors, pressure gauges, cameras, chemical sensors, velocity meters, and more.

Two areas of need in the oceanographic sensing blue economy market sector are the need for reliable, clean energy and the option for a stable sensor platform to increase data accuracy. The team’s engagement with sector stakeholders indicated that oceanographic sensors typically rely on pre-charged batteries, limiting the length of deployment. For some sensors, their data accuracy is dependent on the motion of their platform. The motion of the waves both powers the sensors and potentially disrupts accurate data collection. We designed a “stable operation” mode option for sensors that require a stable platform. The WEC will has two operating modes: one for storing generated power and one for stabilization (Figure 2).

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Figure 2: Dual-mode Operation Models

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Business Plan

Our goal was to create a low impact wave energy convertor that could house an array of oceanographic sensors and instruments that could collect quality data year-round regardless of sea-state (through WEC stabilization control), greatly reduce the need for expensive boat time (through longer deployments), and mitigate the current demands for an arsenal of batteries (through the generation of renewable wave power). These summarize our social, technical, environmental, and financial goals which will be further expanded upon throughout the report.

Concept Overview

Business Model/Vision Obseaver Marine Energy is a hypothetical company located in Portland, Oregon. Our product, the Lightning wave energy converter (WEC), is designed as a customizable attenuator style WEC to power sensors for metocean observation and research. Our baseline design provides consistent, reliable, and renewable power to the rechargeable batteries. In addition to designing a WEC to mount and power sensors, we incorporated a stabilization mode with controls informed by data collection issues on currently deployed buoys. The stabilization mode solves the issue of sensors collecting bad data during extreme sea states. Featuring two sensor mounting platforms (above and below the water level), the Lighting WEC can accommodate a wide variety of oceanographic measurements and customer needs. Obseaver Marine Energy has two product offerings. The base model for the Lighting WEC includes the energy storage system for renewable energy generation, battery storage, stabilization control, and the sensor attachment system all shown in Figure 1. Given the broad array of sensors available for oceanographic measurements (acoustic sensors, pH monitors, temperature sensors, pressure gauges, cameras, chemical sensors, and velocity meters), Obseaver has an extended model which allows clients to customize for specific sensors they need on the device to accomplish their mission. The extended model builds off the base model and allows Obseaver to customize the Lighting WEC with the sensors; based on client requirements.

Triple Bottom Line Our Lighting WEC address two primary financial obstacles present with traditional battery-powered buoys. The first is the life of the battery. Researchers and federal agencies are limited on the number of sensors they can attach to oceanographic buoys and how much data they can collect, due to battery energy budgets. This is especially prevalent when the data is being transmitted telemetrically. Our device generates its own reliable, consistent renewable energy to allow for increased deployment length and reduced battery storage requirements. This ability has larger financial implications by reducing ship time to service and replace batteries on buoys which is expensive.

Socially, there is pressure for organizations to move to more sustainable solutions. This is important so that future generations can enjoy a healthy environment with lower carbon emissions. Many companies follow the triple bottom line framework for ensuring that they are focusing on social and environmental goals as opposed to just their profits. Obseaver’s vision and mission required a triple-bottom-line approach to all company activities.

Environmentally, oceanographic sensing is important in understanding changing ocean environments, impacts of climate change, bathymetric mapping, ocean observations, etc. The Lighting WEC offers a low- impact platform to secure these needed datasets by using wave energy instead of batteries and significant

5 | Oregon State University fuel usage for deploying/picking up equipment. This minimizes the impact on the ocean environment while expanding out the collective ability to study ocean processes to inform current and future ocean activities. With a continually changing ecosystem, it is necessary to continually monitor the ocean to build understanding. The lighting WEC provides this transformational ability.

Relevant Stakeholders

Obseaver Marine Energy has identified several key stakeholders from coastal communities to government agencies who use observation buoys. Outreach conversations with private marine energy companies like C-Power, university professors, and attending seminars such as Waves to Wind - Marine Energy in the Pacific Northwest by the Oregon Wave Energy Trust (OWET) were key to understanding the different groups of people impacted by our company. The oceanographic sensing market is currently reliant on battery-powered sensors and intermittent renewables like solar. We want to help this industry in making the leap to wave-powered sensors. The current stakeholders of battery-powered buoys need a safe and reliable alternative to make this transition. Key collaborators are detailed below and identified in Table 1.

The National Oceanic and Atmospheric Administration is a key stakeholder as they are the main governing agency in the United States for monitoring and observing the ocean. The NOAA runs the National Data Buoy Center which has deployed 1,432 observation stations (National Data Buoy Center, 2021). These are composed of ships, Argo Floats, drifting buoys, and most importantly moored buoys. The Coastal Data Information Program (CDIP), which is under the University of California San Diego (UCSD), is another key stakeholder. CDIP is responsible for the deployment and monitoring of hundreds of buoys across the coast of the United States. They use moored buoys that can transmit data wirelessly through radio and satellite communications. (Instrumentation — CDIP 1.1 Documentation, n.d.).

Similar to UCSD’s CDIP program, many coastal universities have similar programs at varying scales. These coastal universities use observation buoys for research, learning, community engagement, and industry- focused R&D. They would benefit from implementing WEC-powered buoys into their programs. Oregon State University’s Hatfield Marine Science Center is a research center for NOAA, the Environmental Protection Agency (EPA), U.S Fish and Wildlife Service (USFWS), the Oregon Department of Fish and Wildlife (ODFW), and the U.S. Department of Agriculture (USDA). They also research aquaculture which provides an opportunity for the use of WECs for renewable energy (Hatfield Marine Science Center Oregon State University, n.d.).

The Navy and all military departments that are involved with the ocean are stakeholders in our WEC device development. The military is in need of oceanographic observation for defense, monitoring infrastructure, research, and underwater navigational hazards. Likewise, port facilities would benefit from the sensing capabilities of a WEC-Powered observation device that can operate for long durations without the need of refueling or replacing batteries. Ocean observation is federally required to monitor the environmental impacts of construction projects. These projects include offshore wind turbines and oil platforms to name a few.

Outreach was conducted with a variety of stakeholders. Obseaver Marine Energy met with C-Power where we learned about the needs of private companies designing WECs. At an Oregon Wave Energy Trust (OWET) seminar, we were able to ask questions about the needs of their organization as a state-level investor in developing ocean energy. Table 1 provides a list of many of the individuals we collaborated with.

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Table 1: List of many of the individuals we collaborated with

Name of individual Affiliation Roberto Racca JASCO Applied Sciences Jim Moum CEOAS mixing group Jonathon Fram Ocean Observatories Institute (OOI) Tim McGinnis University of Washington Applied Physics Laboratory (UW APL) John Garret OSU graduate student researching wave energy economic development Reenst Lesemann CEO of C-Power Pedro Lomónaco Director, O.H. Hinsdale Wave Research Laboratory Bryson Robertson Associate Professor / Co-Director, Pacific Marine Energy Center

Market Opportunity

Assessment of a Specific Market Obseaver Marine Energy identified oceanographic sensing in the blue economy as a huge market opportunity. This sector has opportunities to serve governmental research, academic research, and private companies. Our wave energy converter will provide yearlong power to sensing equipment, removing the problem of a battery with limited capacity to power sensors. Instead, sensors will be able to access power throughout the research period and even collect larger data quantities.

Initial market outreach was focused on the blue economy in general because for many of us at Obseaver this was our first introduction to the blue economy. Surveys, emails, and interviews were held with scientists, engineers, and CEOs across the globe to help us gain knowledge on the blue economy (listed in Table 1). We began by interviewing people who were currently building and investing in wave energy to see what kind of problems, costs, or barriers they were experiencing that could potentially help us going forward. Many issues were specific to their designs and at first, it was tough to see common themes or issues between sectors and companies Obseaver Marine Energy could potentially help solve. Tim McGinnis (UW APL) helped guide us to identify a gap in the industry and communicate between scientists and engineers to establish the criteria of what potential customers need and what is feasible to engineer. Many problems or issues experienced by the CEOs of larger companies were also experienced by the smaller research groups as well, two common problems that seemed to be a part of almost everyone’s experience in this sector of the blue economy were batteries and boat time. So, if we could cut down on these and potentially collect better quality data in high sea states then we can get ahead of the competition.

Through our industry mentor, C-Power, we established the approximate scale for oceanographic sensing, power requirements, and specific design criteria such as mooring. An average Oceanographic sensing buoy requires between 50W to 20kW (“SeaRay”, 2020). Jonathon Fram (OOI) helped us refine our scope to a minimum of 200W and ideally 1kW based on common OOI and NDBC buoys. Thanks to the interviews and surveys done with researchers like Jim Moum who works for the OSU mixing group, Obseaver Marine Energy gained a new understanding of oceanographic sensing and the importance of real-time data for oceanographic (and meteorological) scientists. It also proved to Obseaver that ocean scientists are highly interested in exploring marine energy as a way to power their sensors in the ocean. This sector of the blue economy would allow us to provide real-time data to our customers and clients; who would be academic researchers, private companies, or for governmental research depending on where the device is deployed and what kind of sensors are powered with the Lighting WEC.

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Potential Solutions One of the largest barriers today with oceanography and associated measurements requirements today is access. Even if you do have access to the open ocean, boat time is expensive. So, our goal was to create a low impact wave energy convertor that could house an array of oceanographic sensors and instruments that could collect quality data year-round regardless of sea-state (through WEC stabilization control), greatly reduce the need for expensive boat time (through longer deployments), and mitigate the current demands for an arsenal of batteries (through the generation of renewable wave power). These are our social, technical, environmental, and financial goals.

Not only is physical access extremely important for oceanographic research, but real-time data access is what researchers, companies, and governments are looking for. Across the globe, scientists and researchers need real-time data from their deployed instruments so that their research and datasets are current. Our interviews with oceanographers and engineers from the Ocean Observatories Initiative (OOI) expressed their preference in generating enough power for telemetry and data transfer back to shore (Ocean Observatories Initiative, 2020, September 25). This need for time-sensitive data is the purpose of the OOI, to provide real-time, open data to the public. This real-time data collection from the OOI is still being used by researchers across the west coast and beyond. Without telemetered data, the data is accessed infrequently, on the order of a few times a year or less, and with the use of expensive boat time. This causes data to be expensive and outdated.

Through these interviews, another issue we identified was that data transmission is fairly energy- intensive. Meaning we will have to size our WEC to the point where it generates enough power to power the sensors, send the data back via satellite communication, and still have enough power for controlling the power take-off system. Current research buoys are plagued with the choice of packing enough batteries to send out data in real-time or have the buoy collect data until the buoy is retrieved. Neither of which is sustainable. Often, if the research buoy/station is sent out to collect data without transmitting it, there is no way to tell if your sensors/instrument is properly working and recording data. The stakeholders we interviewed expressed that generating enough power for data telemetry alone would reduce the majority of their batteries. Looking back on data produced from organizations, like the OOI, there are often gaps in the data from periods where seas were too intense to record, instruments failed, or a device was having maintenance work done in it. Whatever the reason, is there is plenty of room left to improve how data collection occurs off our coast to get better, more consistent data. This is an opportunity for wave-powered instrumentation.

Consequently, the two main issues we’re attempting to solve are the energy budget (batteries) and the expense (boat time) for oceanographic observations. We learned through our interviews that for just one day, the cost of a boat to deploy a research buoy costs anywhere from 35-50k or higher. Another issue is the fact that battery usage across the blue economy is rampant, unsustainable, and environmentally damaging. If we could cut down on both battery usage and the number of boat days, then we will have made a device that can save thousands of dollars annually and allows for increased data accessibility. Publicly available data eliminate cost barriers to research and democratizes ocean observation, allowing for more opportunities for innovation, and Obseaver Marine Energy wants to be a part of that effort.

Another obstacle that our team came across during the outreach process is the fact that sensitive instruments are subject to collecting “bad” data during high sea conditions. Jonathon Fram from OOI and Roberto Racca from JASCO helped us understand specific sensors in more detail, and were the first to mention how some sensors are affected by sea state. We learned through our market research that some instruments are more “sensitive” than others and subject to collecting worse data during non-ideal

8 | Oregon State University conditions. Data during non-ideal conditions is often the most valuable to understanding our changing ocean environments, and knowledge of these events is limited.

To understand this phenomenon more, we performed data analysis of the Oregon Offshore Surface Mooring buoy (CE04OSSM), deployed off the coast of Newport, Oregon, and monitored by OOI, to understand the sensors and how real ocean conditions affect their performance. From interviews and research, we found that acoustic doppler current profilers (ADCP) produce “bad data”. The data is “bad” if one of the four acoustic beams is out of sync with the other three, often caused by bubbles, large tilt angles, or marine life passing through. The ADCP used by OOI reports a “percent good” of data collected over a small time scale (minutes). Bubbles also negatively impact optical sensors like dissolved oxygen sensors, and pumping sensors like pH monitors, CO2 sensors, and conductivity depth sensors.

Figure 3 plots the “percent good” from the ADCP vs the pitch and roll angles of the buoy over one day. The bad data is driven by steep changes in pitch and roll, likely from cavitation and bubbles around the instruments. This data analysis validates the need for stabilization of sensors to improve data collection. From July 2019 to July 2020, 4% of the ADCP data was “bad” in the 5 meters below the sensor. Optical sensors and pumping sensors listed previously would experience a similar magnitude of unusable data. This loss of data may disproportionally affect high-security sensing applications which rely on a constant knowledge stream. Unlike a buoy, our Lightning attenuator style WEC has two floats and actuators to control the movement of the device. In addition to designing a WEC to mount and power sensors, we incorporated a stabilization mode with controls informed by the results in Figure 3. This control scheme is expanded in the detailed technical design and has a goal of increasing the amount of “good” data collected by sensors.

Figure 3: Percent good data of the acoustic doppler current profiler on the Oregon Offshore Surface buoy (CE04OSSM) near- surface instrument frame (NSIF)

Most research buoys don’t have a mechanism for stability or an ability to collect good data during high seas. For example, smaller buoys and moored devices often have a certain buoyancy so when the sea states reach extreme levels these buoys will simply roll under the waves as a protection mechanism. When 9 | Oregon State University this occurs, many sensors are not collecting data due to bubbles and submersion. Off the Oregon coast, we are subject to high seas in the winter so we wanted to build a device that not only can cut down on boat time and batteries but also still collect good data during these periods of non-ideal conditions. One such mode would allow the device to use stored energy to counteract the waves, acting as a stable platform for these sensitive instruments to collect data. The other mode of operation would be when the WEC is generating power. Being able to go back and forth between power generation and stability modes will allow our WEC to generate energy and collect good data year-round regardless of conditions. More on the modes of operation can be found in the detailed technical design section.

Competition Analyses There are a wide variety of companies, products, and buoys in the oceanographic observation industry. Each addresses the specific needs of their clients, such as offshore operations, oil, and gas, ports, shipping, and renewables (such as offshore wind). The companies we analyzed include AXYS technologies and Datawell BV who field a variety of buoys with sensors specific to tasks like measuring wave currents or weather data.

AXYS technologies offers a range of buoys such as their 3 Metre Buoy and TRIAXYS Directional Wave Buoy. The base package 3 Metre Buoy houses sensors for monitoring meteorological, oceanographic, and water quality (3 Metre Buoy | AXYS, n.d.). The buoy can also be configured to store sensors for the specific needs of a client. This is relevant to our team as we wish to provide our clients with the option to customize their WEC with the sensors they require. Seeing another company do this successfully helps to validate our business plan. This buoy has an exceptionally long service life of twenty years (with annual service intervals). The device has a battery with a capacity of 800-amp hours as well as an onboard solar panel to recharge sensors. The device sensors have telemetry capability so that data can be analyzed in real-time.

Another buoy from AXYS technology we analyzed was the TRIAXYS Directional Wave Buoy (TRIAXYS G3 Wave Sensor Validation WHITEPAPER, n.d.). This one is smaller than the 3 Metre Buoy and is in a sphere- like shape as opposed to a more traditional vertical buoy. This buoy is made for conducting wave measurements. The sensors are contained in the protective sphere, can store data onboard for two years, and transmit data through telemetry. It is solar powered with panels in a 360-degree configuration. It can be moored in waters as deep as 300 meters. In addition to the base TRIAXYS model, the company also offers two variants on the design which are the TRIAXYS Mini Wave Buoy and the TRIAXYS with Currents Buoy. The TRIAXYS Mini Wave Buoy offers the same benefits as the base model whilst being smaller in size at 0.6 meters in diameter. The TRIAXYS with Currents Buoy provides wave measurements with the addition of ocean current data.

Datawell BV is another company that designs buoys called the Waverider. This buoy is spherical and measures 0.7 meters in diameter. Its value proposition is that the sensors housed on it are gravity stabilized allowing for accurate data with low battery usage. Its sensors measure wave height, wave direction, surface current, and water temperature. Datawell offers a variety of customizations for the buoy such as increased telemetry capabilities, additional sensors, and a solar panel attachment. None of the competitors' products allow for battery recharge during the long dark months of winter when solar is unavailable, or provide a stabilization method to improve data quality.

Value Proposition The end goal of our device, given what we’ve learned from our market outreach communicating with stakeholders, scientists, engineers, and various companies from robotics to physical ocean mixing groups, is to offer a low impact platform for various oceanographic sensors that self generates power, can operate

10 | Oregon State University yearlong under high sea conditions, and still collect good consistent data. This device could power any typical oceanographic sensor, yet it would most benefit those sensors considered to be more sensitive to bubbles and tilt angles. This design greatly reduces the costs of boat time and battery usage. It will reduce battery usage by generating power and, as we mentioned earlier, the current battery usage for data telemetry is very high so contributing to real-time data just using wave power alone is a huge step towards the future of renewable oceanographic practices.

The pricing information on many buoys is not publicly available. Several businesses were contacted for insight into their prices, however, they were unable to disclose this information. In outreach discussions, we learned that the TRIAXYs buoys base package starts at $60,000 and can easily exceed $1,000,000. According to Miros Group, a buoy can cost up to $170,000 a year to maintain (“Wave Buoys...”, 2020).

State, Federal, Nonprofit Incentives A wide array of business support and commercial development incentives exist for start-up companies such as Obseaver Marine Energy. The Department of Energy’s office of Energy Efficiency and Renewable Energy (EERE) offers funding through their Small Business Innovation Research SBIR and STTR programs. These grants are for businesses developing and researching new renewable energy technology. The grant starts at Phase I which offers $200,000 for designing a proof of concept. During Phase II, approximately $1.6 million to $4.9 million is available for research and development and commercialization over two years. Phase III has no limit to the amount of federal or private funding (“Small business innovation…”, n.d.).

NOAA also offers SBIR grants to businesses innovating in the ocean and atmosphere. Similar to DOE SBIR grants, there are phases to accessing the full amount of grant money. The first and second phases are directed to research and development with the third for commercialization. Phase I is approximately $150,000 over six months, Phase II is 500,000 over two years, and Phase III seeks to gain funding from a private or non SBIR government source (NOAA, 2019). Business Oregon is a state-run program that invests in Oregon businesses, communities, and people. They offer an SBIR matching program. Phase I grants provide additional support for companies with successful proof-of-concept SBIRS from other agencies (approximately $150,000) and Phase II grants for developing commercial products are $1.5 million (SBIR, n.d.).

Our team also has the option of pursuing a Small Business Technology Transfer. This requires the business to be paired with a nonprofit research institution. Oregon State University is available as a research institution that would allow access to researchers, experts, and continued use of testing facilities (“The SBIR and SBTT…”, n.d.). Testing and Expertise for Marine Energy (TEAMER) is sponsored by the DOE and directed by the Pacific Ocean Energy Trust (POET). They provide access to testing resources and funding for marine renewable energy. Money is available to support the testing and development of companies like ours (“About Teamer”, n.d.). The Oregon Technology Business Center (OTBC) is a non-profit that supports startups. They offer coaching, mentoring, market strategizing, and affordable office space. Their Beaverton Startup Challenge offers $25,000 to small businesses as well as legal, accounting, HR, and marketing services. The office space and services provided by this nonprofit make it a key resource in moving to a commercialized product.

Financial and Benefits Analysis The Powering the Blue Economy report estimates the total market value for surveying, hydrographic, oceanographic, hydrological, meteorological, or geophysical instruments, and appliances was approximately $10.1 billion (LiVecchi et.al., 2019). This report shows substantial growth in this market

11 | Oregon State University over the past twenty years. We feel confident targeting this market with the available grant money and the social and business needs to move towards renewable energy. More and more platforms are needed for tsunami early warning, meteorology, and oceanographic sensing. As developing nations in the Oceania region grow, they will need access to survey data or their own sensing equipment. We estimate that our device will be priced at $140,000 for the base package. This includes the WEC battery, hull, shipping. Optional customizations are $100,000 and this includes mooring, sensors, and telemetry capability. Our marginal cost is $60,000 for each base package unit and $90,000 if a customized unit is purchased. Because these are large manufactured devices with sensitive electronics, we expect the cost of each unit to be high. We expect that annual operating expenses will be $100,000 for maintenance, HR, accounting, etc. With continued maintenance on operational Lighting WECs, we expect their service life to be twenty years. Each boat trip to check on the devices is assumed to be $50,000 a day.

Based on the selection of grants available above, we have access to approximately $6,425,000 with most of the funding coming from federal SBIR grants. This figure includes capital from all phases of grants. Our business plans on applying to the phase one grants to receive funding. This funding would allow us to build a full-scale model of the device as well as to conduct extensive testing in the ocean. Organizations like TEAMER and OTBC will allow us to reach our R&D growth goals to apply for phase two and three funding. This substantial increase in funding will allow us to move towards commercialization. OTBC business operations services, such as HR and accounting, as well as their ability to provide research and industry expertise will allow us to have the partnerships necessary to grow our business. We would expect that the business would have to hire more employees to manufacture the Lightning WEC as well as fulfill customization requests for sensing requirements. We will also need sales personal familiar with the needs of organizations like NOAA, university researchers, and foreign markets to be commercially successful.

Development and Operations

Research and development for the Lightning WEC have included stakeholder interviews, customer feedback sessions, and technical discussions with field experts. These processes will continue to advance the design, improve the market strategy, and adapt to changing customer needs. The manufacturing, transportation, and deployment & recovery of the Lightning WEC are all important considerations for the design. The device is designed to fit in standard highway shipping trucks and be deployed on common workboats. The general dimensions of the efficient storage method are 5.55m x 2.65m x 2.2m and a mass of 859kg. Partnerships with NOAA, OOI, research groups, and private sensing companies like JASCO have already been established. Continuing relationships with these sensing groups will allow our design to be universal but also customizable to fit the sensing need.

There are several important social and environmental implications to consider for the Lightning WEC. Public awareness of wave energy in the Pacific Northwest, specifically, is fairly low compared to wind and solar energy. However, the public has a positive attitude towards the development of marine renewable energy (Boudet, 2020). According to Oregon’s Statewide Goal 19 on Ocean Resources, conserving marine resources and ecological functions are of great importance (“Oregon’s Statewide Planning...”, 2001). Ocean activities like commercial and recreational fishing should not be impacted by new ocean activities, such as marine renewable energy, or there should be a strategy to ensure equitable distribution of benefits to mitigate any impacts to traditional extractive ocean industries. Oceanographic sensing and the buoys that serve observing functions are already well-established ocean activities, therefore the adoption of a new way to power oceanographic observation should not cause added disruption to current ocean activities.

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Detailed Technical Design

There are many proposed opportunities to co-design marine energy systems and existing sectors of the blue economy. One of the areas for innovation is designing wave energy converters to power oceanographic sensors. Obstacles that currently exist in oceanographic sensing include a lack of sustained power at sea and data loss due to buoy instabilities. These obstacles led us to work on a dual-mode operation WEC, one mode to produce power and one mode to provide stability to maximize sensor data collection.

Design Objective

The main design objective was to size an attenuator style WEC to power a suite of oceanographic sensors commonly found on data collection buoys; like those deployed for the Ocean Observatories Institute (OOI) or the National Data Buoy Center. Obseaver Marine Energy started with a WEC designed by our industry partner, C-Power, and adapted it from a megawatt-scale to hundreds of watts scale, shown in Figure 4. The sensors and telecommunications are all powered from a battery stored in the damper plate of the device. Power is generated from the relative rotational motion between the floats and nacelle of the Lighting WEC, with separate power take-off (PTO) systems for both the forward and aft floats. The Lightning WEC can be moored or drifting to accommodate the varying needs of our customers in the oceanographic sensing field.

Figure 4: Lightning WEC with major components labeled

Our stakeholder interviews provided valuable information for designing the Lightning WEC to serve oceanographic sensing needs. Oceanographic sensing buoys operated by OOI need a minimum of 200 W to operate sensors and data transmission devices. Ideally, the customers would like 1kW which would allow for more frequent data collection, higher power sensing devices, and more frequent data transmission. Our design aimed to maintain this minimum requirement to accommodate a wider range of customer needs. Oceanographic sensing buoys often include a wide variety of sensors; sensors above the water surface, sensors a few meters below the water surface, and (if moored) sensors along the mooring

13 | Oregon State University down to the ocean floor. To support these needs, we designed sensor mounting platforms above the device and on the damper plate as a sub-surface mounting platform.

The additional design objective was to develop a dual-mode control system that physically stabilizes the WEC to improve sensor data collection and transmission. Currently, buoys that house oceanographic sensors have no control over their physical response to the ocean waves. In certain sea states, the motion of the buoy causes sensors and data transmission devices to be inoperable, causing a loss of data. This inability to capture and transmit data is often due to both large tilt angles of the buoy and the presence of air bubbles around sensors. To meet our customers’ needs of powering sensors and getting reliable, robust data, we have developed a dual-mode control system: one for power production and one for platform stabilization.

In the power production mode, the WEC power take-off operates as a generator and charges the battery and the sensors collect data (as shown by green lightning bolts in Figure 5). In the platform stabilization mode, the WEC PTO operates as a motor, utilizing the energy stored in the batteries, and actuates the fore and aft floats to stabilize the nacelle and damper plate (as shown by red lightning bolts in Figure 5). The nacelle and damper plate are stabilized because they house the sensors. The sensors are now able to collect and send data in sea states that they previously could not when mounted on traditional buoy systems. Figure 5 demonstrates this dual-mode operation. The Lightning WEC will operate mostly in the power production mode, with a minimum of 4% of the year in the platform stabilization mode as indicated by the ADCP percent good data previously discussed. The platform stabilization mode is enabled when the damper plate experiences certain motions that are correlated with data loss such as high pitch accelerations and high pitch angles.

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Figure 5: Dual-mode operation of the Lighting WEC

Design Details

The Lightning is an attenuator style WEC with a central nacelle, a fore, and an aft float. The basic dimensions are listed in Table 2 and a simplified drawing is shown in Figure 6. The Lightning WEC design has considered standard operating forces and moments in material selection as well as planned for extreme wave condition safety mode as discussed in subsequent sections.

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Table 2: Lightning Dimensions

Feature Dimension Nacelle 1.75 meters in length Forward Float 1.90 meters in width Aft Float 2.10 meters in width Dry mass 859.80 kg

Figure 6. Engineering Drawing of Lightning

Sensor Attachment System A key feature of the Lightning is the incorporation of a sensor attachment system; both above the surface and below the surface. The system shown in Figure 7 incorporates perforated metal sheets to provide a variety of attachment points for sensors. As well as being functionally designed around sensor attachment, the size of the perforated metal sheets can be modified efficiently for scaling purposes. Another feature of the sensor attachment system that provides modularity to the design is the use of 80/20 T-Slot Framing in the main structure of the system. The horizontal 80/20 T-Slot framing components can be shifted up or down to provide more options for various types of sensors, such as those that require more surface area. Another advantage of the 80/20 T-Slot framing is that it provides a strong frame to maintain the structural integrity of the sensor attachment system. This design was based on sensor mounting systems on OOI buoys.

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Figure 7: Sensor Attachment System Hydrodynamic Modeling

The hydrodynamic model is based on the Computer-Aided Drafting (CAD) model provided by our industry partner C-Power. To obtain the linear frequency domain hydrodynamic coefficients of the WEC, we used the BEM solver ANSYS AQWA. To do so, we created a simplified geometry of the SolidWorks model in the AQWA Design modeler and used the inertial properties of the more detailed CAD model, shown in Figure 8. The meshing and definition of the environment were done in AQWA's subsequent functions via a Graphical User Interface. The resulting hydrodynamic coefficients are post-processed with help of WEC- Sim’s BEMIO code and used for the time domain simulation with WEC-Sim.

Figure 8: We used SolidWorks to identify the mass and the inertial properties of each of the 3 bodies that make up the WEC.

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WEC-Sim Modelling

Toolbox Overview The toolbox WEC-Sim (Wave Energy Converter SIMulator) is an open-source code for simulating WECs that uses MATLAB & Simulink along with the multi-body dynamics modeling toolbox Simscape (WEC- Sim, 2021). WEC-Sim models the hydrodynamic response of a user’s unique WEC system through various user-defined sea states by solving the governing equations of motion (EOM) of the WEC in 6 degrees of freedom (DOF) in the time domain. WEC-Sim additionally gives users the ability to model different mooring, power take-off (PTO), and constraint configurations specific to their system that will also impact how their device responds to the sea state. To run a model in the toolbox, WEC-Sim requires several files to be present in the working directory, depending on the simulation configurations. When linear buoyancy and Froude-Krylov excitation forces are assumed, the files necessary to run the model are the hydrodynamic output files from either WAMIT, ANSYS AQWA, or NEMOH; software used to solve the three-dimensional radiation-diffraction problem using panel methods. When nonlinear buoyancy and Froude-Krylov excitation forces are assumed, the previously mentioned hydrodynamic files are necessary as well as geometry files (such as a stereolithography file) for each body which is used as the surface on which the nonlinear pressure forces are integrated (WEC-Sim, 2021). The former was assumed for the competition as nonlinear behavior was not encountered (or expected) during preliminary simulations, however, geometry files were used for visual aesthetics.

Sea State Conditions The location chosen to characterize sea states the device is simulated under was the PacWave location off the coast of Oregon in the U.S. Pacific Northwest. This site represents an area where future WEC technologies will be tested, solar is not ample year-round, and rough sea states can occur, yielding an ideal location to test the response and power output of our device. Additionally, many of the stakeholders interviewed use their devices in this region of the U.S. giving more reason to PacWave’s location as a relevant site. Sea states for testing were determined through a k-means clustering analysis from five years' worth of data (1980 - 1985) to determine eight sea states that best characterize the PacWave location, shown in Table 3.

Lightning Setup In WEC-Sim, the Lightning is modeled as a 3-body system – the aft float, forward float, and the nacelle/damper plate. As described previously, hydrodynamic files were obtained using ANSYS AQWA where the hydrodynamic responses of each body were simulated over pre-determined ranges of frequencies which are dependent on the design. Geometry files for each body were obtained using SolidWorks. Simulink is used to describe how the bodies are connected, seen in Figure 9. From this, the reader can visually tell that the aft and forward floats are connected to the nacelle through rotational PTO’s, the nacelle is constrained to move in 3-DOF, and there is a mooring system.

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Figure 9: Simulink Setup Lightning for WEC-Sim modeling

In addition to this, the wecSimInput.m initialization script defines properties of the Simulink blocks and other parameters used during simulation. These properties include irregular user-defined sea states, body class information (respective hydrodynamic and geometry file, mass, moment of inertia (MOI)), constraint class information (location the constraint acts on the body), mooring class information (spring stiffness values and DOF constrained to), and PTO class information (location the PTO acts on body, stiffness and damping values). The irregular sea states used were based on a Pierson-Moskowitz spectrum. Inputs needed by WEC-Sim to simulate the device over this spectrum require values of significant wave height and peak period, of which values were chosen based on the results in Table 3.

The body class hydrodynamic and geometry information is obtained as described earlier, and mass and MOI values were found from Solidworks modeling. Constraint class information consisted of the location of the 3-DOF constraint which was placed at the nacelle’s waterline. A 3-DOF constraint was chosen as the mooring system tested on the physical device greatly restricted movement in sway, roll, and yaw. Surge motion was also restricted, simulated by the use of a mooring matrix with spring stiffness values of 342 N/m in surge (determined by scaling tank tests). This was multiplied by four as the physical device uses four lines, each with one spring. PTO locations were adjusted until the rotation of the arms that attach the floats to the ends of the nacelle were rotating about the axis that runs through the middle of the nacelle length-wise. PTO damping values were optimized until maximum power was obtained for the sea state simulated in Table 3. An image of the system in mid-simulation is shown in Figure 10 where the left represents an isometric view and the right represents a side view to better depict the rotation of the floats in relation to the nacelle.

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Figure 10: (left) isometric view of the 5 times scaled Lightning; (right) side view of the 5 times scaled Lightning, nacelle highlighted for better visual of float placement and rotation

Power Results Power in WEC-Sim for each PTO is calculated by: 퐹푃푇푂 = 푐푃푇푂 ∗ 푋̇ (1) 2 퐹푃푇푂 = 푐푃푇푂 ∗ 푋̇ (2) where FPTO is the force from the PTO, cPTO is the PTO damping value, and Ẋ is the velocity the float is rotating about the nacelle length-wise center axis.

As there are two PTOs, the time series of the power outputs from the individual PTOs are summed to represent the total. A global maximum in damping is also observed as increasing the value increases power, but also slows down velocity. As an example, the power outputs from a sea state of 3.5 m and 9.4 s produced the time series results over a 20 minute simulation period shown in Figure 11 (blue line). To get a useable value, the mean of the time series was taken also shown in Figure 11 by the red line. Power outputs for various damping values are shown in Figure 12, noting the maximum. This was repeated for the sea states considered with power outputs and maximum pitch encountered shown in Table 4. The maximum pitch of the nacelle/damper plate was noted as this gives an idea of which sea states will require stabilization control to be utilized to ensure the operation of the sensors. The damping value on each PTO that obtained the maximum power output is also listed.

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Figure 11. Power time series of aft and forward PTOs summed for a 20-minute simulation over a 3.5 m and 9.4 s sea state

Figure 12. Power output vs damping values for a 3.5 m and 9.4 s sea state, indicating a global maximum for a damping value of 3000 N/m(rad/s)

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Table 3. Eight sea states that characterize the PacWave location over five years’ worth of data after k-means clustering analysis. Mean power results of the Lightning WEC after 20-minute simulations under the eight characterized sea states; maximum nacelle/damper plate pitch encountered is listed as well Sea State Peak Period Significant Mean Power Max Pitch Damping Value (Tp) [s] Wave Height [W] Anlge [deg] [N/m/(rad/s)] (Hs) [m] 1 14.2 3 104 20 2500 2 12.5 5.5 599 25 2000 3 12.1 1.9 85 10 3000 4 11.5 3.4 346 15 2500 5 10.3 1.8 158 15 2000 6 9.4 3.5 839 40 3000 7 8.7 1.6 258 20 1500 8 7.1 1.7 628 30 1500

Five out of the eight sea states meet the base power requirement of 200 W. It is noted that these sea states generally had more pitch movement which resulted in more rotation of the PTOs, outputting a higher power.

Energy Storage The range of energy ripple produced by the Lightning WEC was determined by integrating the power time series after removing the average power, to represent the energy leftover to be stored. To establish the upper storage capacity needed, the time series was taken from the sea state that produced the most power; Hs of 3.5 m and Tp of 9.4 s. The power, and power, and energy ripple time series of this scenario are shown in Figure 13.

Figure 13. Power and power and energy ripple time series for a 3.5 m and 9.4 s sea state

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The battery capacity needed to meet the energy range is: 퐸푚푎푥 퐵푎푡푡 = 푠 (3) 푐푎푝 3600 ∗푉 ℎ푟 where Battcap [Ah] is the capacity of the battery, Emax [J] is the maximum energy to be stored, and V [V] is the voltage of the power system (assumed to be 12 V). This results in a battery capacity of 1.7 Ah or 20.4 Wh. Simulations with longer simulation times would better characterize the battery capacity.

Analytic Model of Reduced Dynamics

To stabilize the main body of the WEC, which carries the oceanographic sensors, we identify the surge, heave, and pitch to be the most important. We will derive the dynamics in those modes based to obtain the internal dynamics to lastly design a state feedback control law that can limit the pitch motion in the case of high energetic sea states. Our approach is based on Ling et al. recent work addressing modeling and control for Attenuator Style WEC with one arm (Ling et al, 2020). We model after first order principle to receive State Space representation, with state vector 푇 푠 = [푥1푧1휃1푥2푧2휃2푥3푧3휃3] (4) The torques from generators act on the acceleration of angle positions 1 1 1 1 휃̈1 = 푓 ( 푇푓 + 푇푎), 휃̈2 = 푓 (− 푇푓), 휃̈3 = 푓 (− 푇푎) (5,6,7) 퐼1 퐼1 퐼2 퐼3 Where Tf and Ta represent the torque from the for float and aft float generator respectively and are 푇 contained in the vector 흉PTO = [푇f 푇a] . The pitch moment of inertia of body i is denoted 퐼푖. This representation of the system dynamics with s enable us to use the hydrodynamic properties identified with the BEM solver to describe the dynamics of the reduced state vector by using the Cummins equation −ퟏ Ex 풔̈ = 푴∞ (푯풔 + (푫퐑 + 푵)풔̇ + 푪R풇퐑 + 푭 ) + 푩흉PTO (8) The matrix contains the 푴∞ mass and added mass components of the respective DoF. The hydrostatic restoring force is considered with 푯풔 and the force due to viscous drag with 푵풔̇. The radiation problem is assumed to be linear and the resulting radiation force vector 푭Rad approximated with the linear state space representation, ̇ 풇R = 푨R풇R + 푩R풔̇ (9) Rad 푭 = 푪R풇R + 푫R풔̇. (10) The dynamic matrices 푨R, 푩R, 푪R, 푫R are identified with the BEMIO code from WECSim and then manually reduced to the DoFs contained in the vector 풔. When we cast the problem into concatenated 푇 linear state space representation with state vector [풔 풔̇ 풇푅] we run into the issue that the resulting pair of dynamic matrix and input distribution matrix is not controllable and consequently we can’t apply the desired LQR algorithms directly.

Although the BEM solver gives us the hydrodynamic coefficient of each body and each DoF, the BEM solution does not take the constraints due to the connection between the bodies at the generators in the nacelle into account. To represent this constraint, we transform the initial state vector 풔 and express it in terms of the position of the pivot point P and the angles between the main body and arms, measured by the encoders in the generators, as illustrated in Figure 12.

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Figure 12. WEC body graphic of the center of gravities and the pivot point

The resulting vector is 푥P 푥1 − 푟1 sin(휃1)

푧P 푧 + 푟 cos(휃 ) 1 1 1 휃 풑 = 1 = 휃1 . (11) 휃2 휃2 [휃3 ] [ 휃3 ] The trigonometric relations between the different coordinates make the transformation nonlinear, however, we assume that while the stabilizing control is acting the angles are small and consequently use the small-angle approximation sin(x) = x, cos(x) = 1 to linearize the transformation. Hence,

풑 = 푻2풔 + 푲2, and 풑̇ = 푻2풔̇. (12) 9×5 Note that 푻2 ∈ ℝ is not a square matrix and the back transformation is not it’s transposed, but a matrix we can easily determine in the same fashion, namely 풔 = 푻1풑 + 푲ퟏ. Let us furthermore neglect the radiation forces between the bodies to further simplify the problem and recast the dynamics into state space form ퟎ7×2 1 1

풑̇ ퟎ5×5 푰5×5 풑 퐼1 퐼1 [ ] = [ ] [ ] + 1 흉 + 푻 푴−ퟏ푯푲 + 푻 푴−ퟏ푭Ex (13) 풑̈ ⏟푻 푴 − ퟏ 푯 푻 푻 푴 − ퟏ 푵 푻 풑̇ − 0 PTO ퟐ ∞ ퟏ ퟐ ∞ ퟐ ∞ ퟏ ퟐ ∞ ퟏ 퐼2 푨̅ 1 0 − ⏟[ 퐼 3] 푩̅ The constant part and excitation force are regarded as disturbances to the system dynamics. The resulting transformed system still has uncontrollable modes, but the pitch motion of the WEC, which we identified to be the most important for the sensor performance is indeed controllable. Now, we use the MATLAB command ctrbf to obtain the controllable subspace of the pair 푨̅, 푩̅. This method has the disadvantage that the intuitive physical meaning of the states gets lost, since the new states 풑푪 are a linear combination of the old states p, however from the new transformation matrix and the output distribution matrix we can read which new state corresponds to which entry of p to design the penalties/weights for the LQR controller.

LQR Control Design

We chose the LQR method since it reduces the amount of control action required, based on the optimization of the quadratic cost function in terms of the system states and the control inputs.

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First, we only penalize the velocity of the pitch motion with the numeric value 1 and let the other gains of the Q matrix be zero, hence Q is positive semidefinite. Second, we neglect a cost relation between states and inputs. Lastly, we equally weigh the two control inputs, thus 푹 = 푰2×2 With MATLAB we obtain the gain matrix 푲lqr as output from the lqr() command executed on the controllable subspace. Finally, when the system needs stabilization the generators/motor torques should 푪 be, 흉PTO = −푲lqr풑 . Although, in theory, this method should work, we could not stabilize the WEC-Sim simulation. For debugging we tried to design decoupled PID controllers for the pitch velocity, again without success. We cannot yet tell where the issue originates from. It might be the integration of our artificially generated control torques into the rotational joint constraints in WECSim, the fact that the nonlinear buoyancy of the floats is not taken into account, or we might have mistakes in our derivation.

Incorporation of Environmental and Sustainability Factors

The Lightning design has been through several iterations of a new DOE-funded “Blue Economy Quiz” in development by researchers at Oregon State University. This quiz has helped our design consider many end-users, adjacent users of the ocean space, and the environmental impacts of the device. For the moored case, the mooring follows standard designs for moored buoys that limit the danger of entanglement for marine life. The Lightning WEC size is comparable to typical oceanographic buoys in height and width. The distance between the spars is 2.65m to minimize any marine entrapment. Cables between the battery and sensors are tightly secured to the spars, also to minimize marine entrapment.

Lightning is designed for a sustainable end life or re-life. Upon failure, the device will be retrieved and assessed for maintenance work, part reuse, or part recycle. Tracking sensors on the device would allow for retrieval in the case of a mooring failure as well. Unlike other oceanographic buoys that are left to add to ocean trash, we would retrieve our device and work to fix it or reuse the parts.

The PacWave site off the Oregon coast has acted as a case study for device analysis. At this location, the wave resource is high compared to much of the world’s oceans. To survive these high-energy sea states, the Lightning WEC is designed to have a safety mode to avoid failure. In the case of extreme states, the forward and aft floats can rotate completely about the nacelle without damaging any parts or connections. For example, if a large wave hits the device, the forward float can safely rotate over the top of the nacelle and rest within the aft float. When the extreme state has passed and the WEC has enough power, the motors can actuate and return the forward float to its intended position.

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