27 May 2011
This post is part of a series describing the Threephase project.
In a new state, players will see immediately that their power grid is not meeting customer demand. This is critical in power systems, much more so than any other commodity market. Unlike typical consumer product supply and demand, a lack of supply of electricity doesn’t generate consumer buzz like a gadget shortage. The system experiences instability and outages fails if demand and generation don’t match exactly.
Thanks to the way players authenticate with Threephase (with their existing Twitter or Facebook account, using the OAuth protocol), the server can optionally communicate to players out-of-band when such emergency situations arise. Imagine a tweet or Facebook message from Threephase when generation dips dangerous close to or below the level of demand.
The first solution to not meeting demand, of course, is to build more generators. Not all is perfect, however, as demand is not static. The load of each City (and overall that of the State) changes based on the time of day. Each City has a predefined load profile function, which determines how that City’s demand changes during the day. Generally, demand is higher in the afternoon and early evening than late at night. A player’s system may be sufficient at 8am, but insufficient later in the day.
The current load profile function is static, and simply scales linearly with the number of customers in a City. In the future, each City could have a more intelligent, varying load profile function. The current function (found by visual approximation) is:
-.1 ∗ ((.42 ∗ Hour - 5)4 ) + 100) ∗ Customers/Constant)
In addition to changes in demand, components in the system can also fail due to equipment malfunction, natural disasters or union strikes. The system must have enough capacity to withstand the loss of its largest component - this is known as an n - 1 reliability constraint. As mentioned earlier, the GeneratorType determines the relative frequency and severity of failures. The Country can also enforce stricter reliability constraints (e.g. n - 2) for experimentation.
The parameters for describing these failures - technical reliability (i.e. mean time between failure) and technical complexity (i.e. mean time to repair) - are not the same descriptors used by the electricity industry, but they are more familiar to laypeople and describe similar concepts to the system-wide metrics used by experts (e.g. the system average interruption duration index, or SAIDI). These two attributes determine the frequency at which failures are triggered.
Players of the game have two basic motives:
The requirement to transmit power changes the reality of the operating strategy quite a bit. The ideal system, where generators are operated in order of their marginal cost, becomes impossible when the physical location of generators and customers is considered. The line constraint feature was removed from the list of initial features of Threephase, but it is the next big logical step for simulating reality.
The physical location of load on the grid can make the ideal, cost-minimizing generation scenario impossible. In this example, Titusville has 150MW of demand and no generator, but the only transmission line into the City has a maximum capacity of 50MW. It is impossible to transmit enough electricity to meet demand.
The true root motive of any utility operator is profit. The ability to make a profit on the system is critical to re-investment in new technology, system upgrades, and investor satisfaction (in the case of investor-owned utilities). This greatly depends on the economic regulatory environment, both in the real world and Threephase. The current implementation supports rate of return and marginal cost bidding regulation.
In all of the regulatory environments, the actual cost of operations depends on the operating levels of each generator. In the current implementation, this is set based on the ideal strategy - generators are enabled in order of their marginal or average cost. Transmission line constraints must be completed before a more realistic scenario can be demonstrated.
Rate of return regulation is the simplest to calculate and understand. The customers payments are simply the total cost of operating the system at the level demanded multiplied by a regulated rate of return (e.g. 8%). This type of regulation is highly desirable for utilities, as players of the game will quickly realize. A guaranteed return on investment is great encouragement for expanding the system to levels beyond what is actually required. The cost of capital in this system is also lowered, as the risk to banks loaning money is low if the debtor is guaranteed a return on their investment by the government.
In real-world rate of return regulation, there is a possibility that investment decisions made by the utility will not be approved by the regulator. In the future, Threephase could add intelligence to its regulating algorithm to reject extraneous investment and equipment purchases.
In the current implementation, approval is always granted.
The next type of regulation is marginal cost, or average cost bidding. This type calculates the average cost curve each day, and the generators “bid in” at their marginal or average cost (a bid price enforced by the regulators). The market price of electricity for the day is set at the intersection of demand that curve. Generators at the intersection price will break even, generators above it will potentially make a profit and those below are operating below their marginal cost and are thus guaranteed to lose money.
In both rate of return and marginal cost bidding, the generator’s operating levels are set automatically each day by the server. An optional operating level override is planned for future versions, to allow players to experiment with and view the effects of market manipulation.
The next regulation type to be implemented in Threephase will be locational marginal pricing.
This regulation type depends on determining generator operating levels that respect transmission line constraints. Each City in the State (more generally each node) has a local price, which is affected by the system-wide transmission capacity, cost of local generation and the local demand.
In this example, Titusville has a marginal price of $80 because of its isolation from high capacity transmission lines, relatively high demand and (not pictured) an expensive local generator to make up the difference.
Continue to the next section on in-game time.