Tabla Generada por Tagger

Traditional Real-Time Pricing

Finally, the ultimate form of wholesale-retail market connection is the real-time pricing (RTP) tariff, according to which load consumption is charged on an hourly or half-hourly basis, thus directly exposing wholesale prices to the customers. RTP programs can incorporate day-ahead or day-of real-time prices and can be mandatory or voluntary with varying social welfare expec-tations [68, 3]. In the day-ahead RTP tariff, customers are informed 24 hours

in advance about the estimated prices so they are able to plan their next day electricity usage or, sometimes hedge these prices with other financial in-struments. In this case, the supplier transfers the larger portion of its risk to the customers, so only a small risk premium is charged. This premium reflects two major types of risks, the volumetric and the price risk. The former refers to the utility’s uncertainty for the actual aggregate load devi-ation from the predicted one, as this devidevi-ation will have to be exchanged in the expensive balancing market, whereas the latter refers to the uncertainty on the spot prices due to competition. RTP programs especially benefit flatter-load customers who are inevitably buying smaller electricity amounts at cheaper prices, in contrast to peaky customers who would inevitably pay more, although the corresponding risk premium is much lower [69]. It is important to note that, although RTP programs have been in place since mid-1980s for large industrial customers, it was only in 2003 when Common-wealth Edison utility with the help of Center for Neighborhood Technology (CNT) designed and started the first residential RTP program in the U.S., called the Energy-Smart Pricing Plan [70]. Holland and Mansur [71] have investigated the short-run benefits of RTP using a simulation of the PJM electricity market, and have shown that it can induce both consumer gains (2.5% of the monthly bill) and production cost decrease (59% for oil-fired generation), although average hourly load would increase along with the cor-responding N O_xand SO₂ emissions (but CO₂ emissions decrease). Although RTP programs have a great potential for bill savings, it is amazing that only few of them have managed to attract and maintain customer participation.

A recent study among 48 utilities in the U.S. shows that, although reductions of 12-33% were achieved, one third of the programs had no participants at all (see Figure 5.5 while 28% of the programs were about to be terminated [5].

Some of the reasons for that include poor marketing and customer support as well as program eligibility limitations that led to the attraction of the largest industrial customers. Severin Borenstein has conveyed a number of experi-ments to quantify the risk associated with RTP [72]. Bill volatilities are to be expected even in flat tariff settings due to the changing consumption habits, but it is true that RTP prices increase these values due to their stochastic nature (two to four times according to Borenstein). However, his results show that hedging can cover more than 80% of price volatility in customers’

bills. The amount of hedging is directly proportional to the customer’s load correlation with spot prices. More specifically, Borenstein has utilized data from real industrial and commercial customers as well as spot prices from

California power exchange during the period 2000-2003. He has then created artificial, revenue equivalent flat and TOU rates along with fixed, forward prices (using the actual average spot price for the observed period) and sets hedging volume equal to the customers’ CBLs. According to his findings over-hedging can further decrease price volatility.

Figure 5.4: Real time pricing tariff.

Two-Part Real-Time Pricing

The main problem with RTP is that clients are usually risk-averse and do not wish to see large deviations in their monthly bills. Additionally, free riders can exploit RTP benefits and obtain profit without altering their con-sumption habits [73]. Hence, an innovative RTP tariff that has been utilized in the industry is the two-part RTP tariff (Figure 5.6) also known as Block-and-Index Pricing, which was first introduced under revenue neutrality by Niagara Mohawk Power Co. in 1988, with a program called Hourly Inte-grated Pricing Pilot (HIPP) [74, 5, 75, 3] for industrial clients under the SC-3A option. According to this tariff, customers pay their previous stan-dard (usually TOU) rate for a fixed baseline load (which is usually their average historical demand before entering the program) and then, each hour per day, they are charged proportionally to their deviation from this baseline load at a price close to but higher than both the market and real-time tar-iffs. Hence, customers are able to hedge their risk for the majority of their load and then efficiently trade their deviations, inducing DR. In this case

Figure 5.5: Number of participants per RTP program [5].

it is extremely important to select the best suited historical baseline profile in a transparent way so that customers are not able to game utilities. In its first implementation, this tariff included two types of costs, namely the marginal cost of energy and the marginal outage cost (equal to the product of the value of lost load and the loss of load probability), and was combined with a fixed, pre-determined CBL, however a variety of issues arises when customers intentionally alter their load pattern before entering the program.

This is why, nowadays, a historical average of the previous ten non-event days is used most of the time and appropriate adjustments are made to the calculated baseline load so as to align it with the most recent consumption pattern. However, more sophisticated techniques are needed for high vari-ability customers [5, 50]. Suppliers are the intermediates between generators and customers, so retail risk management is also an essential part of their business. Common retail hedge contracts include price caps, that set a max-imum price threshold to protect customers from extremely high spot prices, as well as price collars that include both a minimum and maximum price to protect themselves from low wholesale prices. Additionally, customers can pay indexed prices on other fuel or production output as well as contracts for differences that give customers the possibility of exchanging real-time prices for fixed ones. Ins some cases, customers are offered contracts for buying and selling CBL amounts. Nevertheless, these hedges, called price protec-tion products (PPPs) are currently limited to industrial clients [76, 69, 5]. In other cases, customers are able to select the percentage of their CBL used for hedging. The latter type of pricing is called unbundled RTP with self-selected CBL or build-your-own (BYO) two-part tariff [69, 77, 66] and is equivalent to a standard forward contract. A summary of common hedging instruments used along with their corresponding risk levels are illustrated in Figure 5.7.

At this point we should note that Georgia Power which has been using this tariff for its industrial customers was the only utility to achieve significant customer participation in its program [78].

Time varying tariffs can be categorized based on two attributes, gran-ularity and timeliness [77]. The former refers to the rate of intra-day or intra-week price change whereas the second is linked to the time between price announcement and implementation. Hence, flat and minute-to-minute RTP rates can be seen as the two extreme points in the continuum of pos-sible tariffs. Both attributes contribute to the accuracy of the price signal to be sent. Ideally, a tariff should provide reasonable time for customers to respond to the signals and should be accurate enough to reflect marginal

Figure 5.6: Two-part real-time pricing tariff [6].

costs of production and delivery.