ارزیابی ریسک استراتژی های قیمت گذاری جدید در بازار حرارت منطقه ای : یک مطالعه موردی در AB انرژی ساندسوال
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|22581||2010||8 صفحه PDF||سفارش دهید||5312 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Policy, Volume 38, Issue 5, May 2010, Pages 2171–2178
The price structure of district heating has been no major scientific issue for the last decades in energy-related research. However, today trends in district heating pricing tend to move towards a more customer-oriented approach with predetermined prices under a longer periods, leading to a more complex price structure. If a district heating supplier offers district heating with predetermined prices in order to compete with similar electricity offers, the financial risk of the new price structure is significantly higher than the risk of an ordinary variable cost offer based on short-run marginal cost. In contrary to an electricity seller, the district heating company cannot transfer all of the risk of predetermined prices to the financial market, instead the company is thrown upon its own ability to handle the risk by, e.g., hedging its own energy purchase. However, all uncertainties cannot be coped with in this manner. Thus, there is a need for a methodology that can be used to estimate the financial risk of different price structures and to value different opportunities to reduce the risk. In this article, we propose a methodology, implemented in prototype software, to evaluate the risk associated with new price structures in district heating.
The price structure of district heating has been no major scientific issue in energy-related research for the last decades. There is a general consensus that efficient price structure should reflect the short-run marginal cost and that the tariff could contain both fixed and variable fees (see e.g. Andersson and Bohman, 1985; Bohman and Andersson, 1987; Della Valle, 1988; Frederiksen and Werner, 1993; Sjödin and Henning, 2004). According to Frederiksen and Werner (1993), an effective price structure shall: • give correct price information to the costumer • be competitive • be understandable in terms of simplicity • give reasonable rate of return • be settled beforehand A price structure based on short-run marginal cost will give correct price information to the customer and hence stimulate to optimal balance of energy supply and energy efficiency measures in the buildings. (Sjödin and Henning, 2004; Gellings and Chamberlin, 1993) If district heating dominates the low temperature heat market in a specific area, the supplier has a good opportunity to define such a price structure. Normally, the price structure has one fixed component of an annual fee per installed kW or year and one variable component where the price per energy unit varies with the season. The variable fee is based on the short-run marginal production cost. This price structure is one traditional way of reducing price risks in the district heating business. For example, a winter that is colder than normal will cause increased production in boilers that are expensive to run. The increased production cost will be covered by the increased revenue as the winter price is based on the short-run marginal cost of that season. Today district heating pricing tend to move towards a more customer-oriented approach, leading to a more diversed pricing structure than the common two-tier price model with both fixed and variable price component described above. When the district heating company tries to expand its sale into new markets, especially into residential districts, other energy suppliers dominates the market and the district heating business will be a price taker instead of price setter, meaning that the company must respond to price-level and structure defined by its competitors. Besides, the company need to cope with the fact that this customer segment is very heterogeneous. One strategy is to offer the customers a variety of price structures (Mårtensson and Frederiksen, 2006). In Sweden, district heating is expanded into the new market segment of single-family houses, currently heated by oil or electricity. In this segment, there is a competition among district heating, electricity-based heating including heat-pumps, and bio-fuel, especially wood pellets boilers. The electricity price-level and structure has great influence on this market and some customers wish to buy district heating with a similar price structure as that of their electricity purchase. The Nordic electricity market is de-regulated. All customers are free to choose their power supplier. The price is settled on the Nordic spot market “Nord Pool” where power is traded on the spot market as well as futures and forwards on the financial market. The electricity customer can buy electricity with variable or predetermined price per kWh. Normally, the variable prices is revised every 3 months. The predetermined price period can be up to 5 years (http://www.elprisguiden.se). If a district heating supplier offers district heating with long-term predetermined prices in order to compete with similar electricity offers, the financial risk in heat-generation cost will increase compared to that of an ordinary variable price offer based on the short-run marginal cost. In contrary to an electricity seller, the district heating company cannot transfer all of the risk of predetermined price offers to the financial market; there is no district heating commodity exchange similar to, e.g. Nord Pool. The company is thrown upon its own ability to handle the risk by, e.g., hedging its own energy purchase. However, all uncertainties cannot be coped with in this manner. Thus, there is a need for a methodology that can be used to estimate the financial risk of different price structures and to value different opportunities to reduce the risk. In this article we propose a way to handle the risk associated to new district heating price structures.
نتیجه گیری انگلیسی
The proposed method yields an insight into how the uncertainty of the risk factors affects the final outcome. The demand of the input is quite reasonable, and despite that the imprecision of the input may be relatively high, the result is presented in a way that provides useful decision support, constituting valuable support when defining an appropriate level of the risk premium. It should, however, be emphasized that no input are definite, these can and should be modified in a manual sensitivity analysis and be continuously updated to actual conditions, meeting changes in the environment. The risk premium level can then be studied from a market perspective, since it must be accepted by the potential customers.