Load Factor and Usage Profile

The load factor is one of the most significant elements of a customer usage profile and of a utility's operating profile. For the utility system, it is the measurement of actual energy output over a period versus potential output over that period, based on the full capacity of the system. If, for example, an electric utility has 10,000 megawatt (MW) of total capacity and generates 120,000 MWh over a 24 hour period, its load factor is 50% [120,000 MWh/(10,000 MW x 24 hours)]. If this utility had a 100% load factor, it could generate the same 120,000 MWh over 24 hours with only 5,000 MW of capacity. Hence, an incremental load with a 100% load factor will produce a significantly lower revenue recovery requirement than one with a 50% load factor because the capital cost associated with the additional 5,000 MW of capacity is eliminated.

If, for example, a gas LDC has a maximum daily distribution capacity of 100,000 Mcf per day (Mcfd) and 100% annual load factor, it would distribute 36.5 million Mcf (100,000 Mcfd x 365 days) per year. If, in actuality, it distributed only 14.6 million Mcf per year, the annual distribution system load factor would be 40% (14.6 million Mcf/36.5 million Mcf).

A load factor of 100% is the theoretical ideal operating state for utilities. In this ideal state, the utility's investment in capacity is spread over the maximum amount of potential output, and the revenue requirement per unit (kWh or Mcf) sold is minimized. In reality, however, a 100% load factor is not an attainable goal. Some margin of excess supply, transmission, and distribution capacity is necessary for maintenance and emergency backup. It is also not possible to balance consumer loads perfectly.

There are, however, some conditions that produce utility load profiles approaching a 100% load factor. Electric utilities, for example, that operate as part of regional power pools and/or have sufficiently low operating costs to allow for export of all excess capacity can approach a 100% load factor. Utilities that are capacity constrained may also need to operate all of their plants at 100% load factor, and purchase power to meet the rest of their load requirements. Gas utilities that predominantly serve heavy industrial loads, for instance, may have a high load factor.

In order to improve system load factor, utilities often seek to market electricity or gas in low-load periods at a relatively low cost. They may also provide incentives, through various conservation and load management programs, to promote elimination or shifting of peak loads.

The utility considers load factor both on a discrete minute-by-minute basis and an hourly, daily, weekly, monthly, and yearly basis. Other common measurement periods are seasons, normal workdays, workweeks, and weekends. Sophisticated dispatch modeling is used to determine when to bring additional capacity (i.e., electric generation plants or gas storage) on- and off-line in response to load fluctuations.

Electric utility systems (or regional power pools) have a dispatch stack order. Generating stations are arranged in the order in which they will be brought on- and off-line in response to changing load requirements. Typically, plants in the stack are classified as baseload, intermediate, and peak-load plants. Baseload plants are generally the most cost-efficient to operate, or have the lowest operating cost, including fuel costs per unit output. Intermediate (or swing-load) plants run much of the time, often under varying loads. Peak-load or peaking plants are typically the least costly plants to construct, but also the least cost-efficient to operate. LDCs also have a type of dispatch order. Supply sources, including storage reserves and liquid natural gas facilities, are arranged in the order in which they will be used.

Load factor is one of the most important determinants of the cost to serve a given facility. Consider two electric utility customers that have the same monthly load of 72,000 kWh. One of the customers uses 100 kWh every hour of the month (720 hours). Under a typical demand/commodity type rate, this customer would have a peak demand of 100 kW and a monthly load factor of 100%. The other customer uses 75 kWh every hour of the month, except for one hour every day, when a certain process requires 600 kWh. This customer would have a peak demand of 600 kW and a monthly load factor of 17% [72,000 kWh/(600 kW x 720 hours)]. While, in this example, the monthly usage is exactly the same for both customers, the cost to serve the customer with the 17% load factor would likely be several times that of the customer with the 100% load factor. To serve the customer with the 17% load factor, the utility would have to reserve 600 kW in generation, transmission, and distribution capacity as opposed to 100 kW for the other customer. If both customers paid the same amount for electricity on a per kWh basis, much of the charges paid by the customer with the 100% load factor would be to support the investment required to serve the other customer.

Now consider a third customer that uses 72,000 kWh per month. This customer operates a night and weekend shift factory that uses 200 kWh every hour for half of the hours every month (360 hours). Therefore, this customer has a maximum demand requirement of 200 kW and a monthly load factor of 50% [72,000 kWh/(200 kW x 720 hours)]. In this case, since all of the load occurs in the utility's off-peak period when load requirements are low, the utility does not require any additional capacity to serve this customer, except for the local wires and transformers connected directly to the facility. Additionally, this customer's loads can be served by the utility's most efficient generation plant. When the power is required by the customer (i.e., the specific usage profile), in this example, it is even less costly to serve the off-peak customer with the 50% load factor than it is to serve the customer with the 100% load factor.

A parallel example can be drawn with three gas utility customers that all consume the same amount of gas on an annual basis. The first customer has a 17% load factor based on a winter heating load requirement. The second customer has a 100% load factor based on a continuous industrial process requirement. The third customer has a 50% load factor, based on a continuous non-winter month gas-fired cooling load requirement. Similar to the three electric utility customers, in this hypothetical example, the customer with the 17% load factor will likely be the most costly to serve and the customer with the 50% load factor will likely be the least costly to serve, with the 100% load factor customer falling somewhere in the middle.

The conclusion that can be drawn from these examples of customers with the same exact daily, monthly, or annual usage is that the load factor and, even more importantly, the specific load profile are key determinants of the actual cost of service. The main reason is the impact of the load profile on fixed cost requirements and how fixed costs are recovered with respect to overall usage requirements.

In addition to load profile, the magnitude of overall load is an important cost factor. There is an economy of scale in serving customers that requires large amounts of energy. Costs of running lines or pipes to a facility, installing service and meters, billing every month, and providing other goods and services are less when averaged over a large, rather than a small, volume.

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