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3Rs for Power And Demand
Dynamic monitoring and decision systems maximize energy resources.
to under-utilization and inefficiency.
2. Customers could and should contribute to making utilization of clean renewable power feasible, but need to be compensated for this. On the other hand, they would be required to provide the information to their load-serving entities about their short- and long-term needs and willingness to respond to system conditions and the price at which they would do this. It’s a misconception that only real-time price response is key to the efficient utilization. Instead, good information about longer time-of-use patterns is essential for long-term efficient and reliable investments at the price customers are willing to pay.
3. Today’s automatic generation control (AGC) is implemented because it’s impossible to predict system load deviations in between the times when the dispatch is done. The same will remain true with the new resources. Assuming that the deviations are poorly predicted, the need for AGC reserve and voltage support-related reserve would escalate and the price in this market would become very high. This cost must be borne by those creating the deviations, and the technologies capable of participating in this market would begin to recover their costs at the value they bring to the system based on the charges from those who create the need for these technologies.
4. Load serving entities (LSEs) will play a major role in creating such portfolios of customers and users, including the addition of storage, PHEVs, wind power, and other resources.
5. These are fundamentally different from the forward prices posted by the financial bilateral trading now required in FERC 719. System operators remain key to clearing these long-term bilateral contracts given the physical power grid constraints—congestion in particular.
6. Social welfare is the sum of customer benefits minus the cost borne by the suppliers, subject to transmission congestion constraints.
7. It’s assumed here that demand is fully responsive. Any other response can be used. Generally, results will depend on the relative rates of response of different power plants and the responsive demand.
8. Demand elasticity is the ratio of percentage change demand quantity and percentage change of unit price.
9. In case some resources aren’t capable of providing their self-commitments with very high confidence, they should be required to provide bounds within which they are likely to deviate. This information will be essential for committing resources to so-called ancillary services and will result in higher charges to the system users. The design of such an ancillary market is technologically possible as well ( see Reference 8 ) but, since it requires very fast-responding technologies, to manage it should have much higher clearing prices than the forward energy market prices, if done right. It will be very difficult to justify expensive storage for balancing predictable changes. Their main value comes from managing hard-to-predict deviations from self-commitments and their cost should be recoverable to a large extent by participating in the ancillary services where their value is the highest. It’s important to keep in mind that aggregators play a major role in packaging highly volatile resources as one better predictable bid.
10. At present in the United