Why Energy Development Needs Search
If you are in the business of clean energy development, you have a lot on your plate. HST understands this. The company was founded by former solar developers who are intimately familiar with the process of PPAs, site selection, interconnection, permitting, solar PV design, and solar PV Engineering, Procurement, and Construction (EPC). They also hired executives and staff from Tesla (TSLA), Sunpower (SPWR), Jinko (JKS), Trina Solar (TSL), and EPCs, among others, to contribute to the mission of adding more clean energy to the grid. This multidisciplinary experience is reflected in the company’s approach to clean energy software. It’s also reflected in the services it provides developers, corporate energy buyers, insurance companies, utilities, and more.
The core of every HST software service is a search engine that identifies the financially optimal project to be built on the grid. This post explains some of the applications for clean energy buyers and developers.
Search Technology to Advance Clean Energy
Search-Enhanced Development
For any given plot of land, there are up to 180 billion configuration possibilities for a clean energy facility (namely, a solar or solar + storage facility). These myriad possibilities arise from the various options a project developer or EPC has for solar modules, inverters, trackers or racks, various skews, project system sizes, DC: AC ratios, and so on. Human evaluation of billions of possibilities to find the lowest cost of energy (or the highest return) configuration would take 100s of years of manpower to perform. A search engine makes this process manageable, flexible, and customizable to generate results optimized for business goals.
An Algorithmic Shortcut to Lowest LCOE
View’s search engine looks at a developer’s site boundaries, provides an initial combination of module, inverter, design parameters and other user inputs to calculate its revenue, energy, and cost in relation to the project IRR and Levelized Cost of Energy (LCOE). Then it intelligently finds the next lowest LCOE combination, and checks to see if that’s a local or global minima (more details are provided in the View Search Engine Whitepaper). Ultimately, it provides the user all of the details behind that optimal configuration (IRR, LCOE, equipment, financials, 8760, BOM) etc. This process can take 180 billion possibilities and narrow them down to, say, 1,500 or 2,500 possibilities that are worth secondary evaluation to determine the very best combination of equipment, project layout, project site boundaries and so on. Like a detective using pattern recognition software to accelerate the process of narrowing-down avenues to solve a case, the View search algorithm exponentially accelerates the development process by quickly finding the lowest LCOE project configuration(s).
Search-Enhanced Procurement
How does this search engine help companies find and procure better energy? Companies that want to explore ways to reduce their Scope 2 emissions by becoming Energy Buyers ask us that all the time. By transitioning from fossil fuel-based retail energy use to clean energy purchasing, these companies strengthen their financial positions and ESG practices, boosting investor ratings and public perception. To find credible sources of clean energy, their energy/sustainability teams need to engage internal departments, energy sourcing advisors, brokers, consultants, or a combination of these procurement experts to determine where and how they can buy the zero-carbon energy required to power their facilities.
By employing an energy transition software provider like HST, with or without a broker alongside, these companies can sign PPAs directly with clean energy projects. Using its Cue software, HST tailors an accelerated search based on a few simple energy usage and building location inputs from the Energy Buyer. HST identifies a curated shortlist of PPAs with optimized projects on the network, saving the Energy Buyer both time and money.
The Marketplace
So how does HST tie this all together? Think corporate pre-ordering of Tesla Roadster rides on Uber Black meets customized Teslas, all for less than the price of ordering rides from a gasoline vehicle. What do we mean by that analogy? Simple: companies that pre-order Tesla Roadster rides on Uber Black are using a digital marketplace platform to provide an advance commitment to a service from a high performance, zero-emission asset. In HST’s case, that service from the high-performance asset (the clean energy project) is both software-customized and cheaper than the service from the older, polluting technology.
Algorithm-driven marketplaces are currently seen in many industries (e.g Airbnb, Expedia, Doordash, Uber) to connect clients with services. HST’s marketplace enables businesses to send developers demand signals to have them build new, customized clean energy projects. This is important because many of today’s businesses want “additionality” when they purchase energy from clean energy projects– that is, they want the ability to show that they were the reason that additional clean energy was added to the grid. Businesses want to be the key catalyst for the next wave of clean energy projects that transition the energy grid, and HST’s marketplace is a key pathway for this.
Synchronized Development and Procurement
In practice, the beauty of the HST network lies in its ability to synchronize information across platforms. Buyers get the energy price, location, timing, etc. that they want, and developers get the price, data analysis, and contract volume that they want. Developers use View to run optimization searches to find the best equipment, project layout, energy volumes, and shapes for a tailored, yet-to-be-built clean energy project that best matches needs that the Energy Buyer provides. They take a site, upload a Google Earth .kml file that has been pre-vetted for wetlands, land use, and interconnection, and run the View search. The View search will crawl through the 180 billion possibilities and compare resulting variations to see which projects will yield the most cost-effective energy for the buyer. One possibility, for example, could be a Hanwha 400W solar module, an SMA 2MW inverter, a Nextracker tracker, a 1.2 DC:AC ratio, a 49.9MW ac system size, a 20 ft row spacing, etc., while another possibility could be a Trina 600W solar module, a Power Electronics 2MW inverter, a Nextracker tracker, a 1.4 DC:AC ratio, a 49.9MW ac system size, a 15 ft row spacing, etc. Once the searches have completed, the developer sees the most effective configuration to use its land to meet the energy buyer’s needs.
Not only has the developer saved time and increased its pipeline value, but the energy buyer has the best possible set of projects to buy cost-effective, optimized electrons from so that they can meet their carbon reduction goals.