Overview of Types of Relevant Knowledge
Most knowledge among generation is in the form of business and operational “know-how” rather than traceable forms of knowledge such as patents or published papers. At its heart, electric generation is a commodity business, even if the commodity is incredibly complex. As a result, generators are dependent on deep levels of insider knowledge about how the electric system as a whole works, the dynamics of their fuel supply markets (if relevant), how the value of their output own is valued, and how that value changes over time. Generators, of course, must build up expertise in the capability and limitations of how their generation assets actually work.
Areas of Generator Knowledge
When and where to build a facility? What facility should be shut down or repowered? What technology or fuel source should be used? These sorts of planning-level decisions are driven by knowledge about the electric system into which the generator will inject power, the geography of the area, expected load growth, competitor generators, environmental concerns, and policy milieu. Much of the information to build this knowledge is available publicly, but requires significant effort to synthesize into understanding. ISO/RTO’s information systems can provide detailed historical prices as well as anonymized quantity awards. The dockets of PUCs and ISO/RTO stakeholder processes provide insight into future policy and market rule changes, respectively. Actually attending meetings and participating in stakeholder processes also provides useful knowledge in this area.
What types of contracts should be entered into? How much should we hedge? How much of our output or capacity should we reserve for the spot market, if any? These types of questions can be answered by personnel who understand complex financial consideration and also have a deep understanding of the relevant markets (power, fuel). Some of knowledge about the expected future prices can be obtained from the results of forward markets (NYMEX, Henry Hub) as well as from firms that specialize in making such predictions. Some generators undoubtable generate their own or make use of commercially developed mathematical models (spark spread, option pricing, etc) to develop their own outlook on important prices.
Technical knowledge about their physical assets. How do they work? How are they maintained? How do you get the most output from them for least cost? How do dispatch changes drive wear and tear? When will the machine require overhaul or replacement? Much of this knowledge comes from the manufacturer of the machine, in the form of training and documentation.
Generators may also rely on various optimize models to make sure they are getting the most value from their fleet of resources. Much such knowledge comes from the discipline of operations research.
Though much knowledge in this sector will be in the form of know-how, there are exceptions. To name a few examples:
- in the wind and solar industries, there are specialty companies developing models for wind prediction. [https://meteodyn.com/en/wind-power-forecasting/, https://www.sciencedirect.com/science/book/9780081005040. https://www.nrel.gov/docs/fy15osti/63175.pdf,
- Specialty companies also develop pricing prediction models that are useful for generation operators. [http://www.eccointl.com/our-services/price-forecasting.html. https://www.sciencedirect.com/science/article/pii/S0169207014001083]
- Operations research specialists develop models of optimal dispatch [https://etap.com/product/economic-dispatch-software. https://w3.usa.siemens.com/smartgrid/us/en/generation-grid-applications/pages/security-constrained-unit-commitment.aspx]
It’s worth noting that these examples are of firms that “supply” knowledge to the generation industry. We have no easy way of knowing what generators also have their own in-house capabilities in these areas, or how sophisticated they are, but it seems fair to presume they exist.
Knowledge Spillover and Diffusion
Because so much knowledge in this area takes the form of expertise, experience, and know-how, diffusion probably takes place mostly through personnel moving between firms. Knowledge and information are also exchanged between parties doing business, between personnel participating conferences and regulatory stakeholder processes, and through comments filed in regulatory proceedings.
Some of this knowledge may diffuse horizontally among other generations firms, but also vertically, between LSE’s, market operators, and generators, as many of the areas of interest (structure and behavior of the power market, for example) are the same among vertical participants of the value chain. Someone analyzing power market at a generator, then, could go to work on the “load side” or for the ISO/RTO, the PUC, etc.