پویایی های قیمت در بازارهای لحظه ای برق ایالات متحده
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7924||2006||21 صفحه PDF||سفارش دهید||10885 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Economics, Volume 28, Issue 1, January 2006, Pages 81–101
Combining recent advances in causal flows with time series analysis, relationships among 11 U.S. spot market electricity prices are examined. Results suggest that the relationships among the markets vary by time frame. In contemporaneous time, the western markets are separated from the eastern markets and the Electricity Reliability Council of Texas. At longer time frames these separations disappear, even though electricity transmission between the regions is limited. It appears the relationships among markets are not only a function of physical assets (such as transmissions lines among markets), but by similar and dissimilar institutional arrangements among the markets.
Spot markets within the wholesale electricity industry are characterized by both price volatility and interdependencies among neighboring markets partially because of limited storability and transmission (Lucia and Schwartz, 2002). Limited storability may make the interdependencies of the electricity spot markets a factor in electricity price formulation and price volatility. Transmission constraints may make electricity contracts and prices highly local, because such constraints make it uneconomical to transmit electricity between certain regions (Lucia and Schwartz, 2002). Volatility and interdependency of wholesale electricity spot markets also results from highly interconnected transmission system, temporal demand–supply imbalance, and transmission congestion. Accordingly, electricity prices may behave unlike any other commodity market (Weron and Przybylowicz, 2000). With utility retail sales amounting to more than 3% of the U.S. gross domestic product (White, 1996), the electric power industry is vital to the economy. Historically, one of the most highly regulated sectors of the U.S. economy, the electric power industry has undergone many structural changes, such as restructuring and deregulation over the past decade. As a result, a more competitive market environment is developing. These market changes imply that price determination is more likely to be placed in the hands of the market than regulators. Analyzing spot market price discovery is important for decision and policy makers because of the structural change the industry is undergoing and the importance of the industry. The objective of this study is to characterize the dynamic relationships among 11 major electricity spot markets in the U.S. and to examine each individual market's role in price discovery. This study, therefore, focuses on spot prices rather than the factors affecting the prices. Providing information on the dynamics of electricity prices allows a better understanding of how price innovations in one spot market affect the other markets and their interaction. In addition, this study addresses the following questions. Do certain markets have more influence on price than others? What markets play the role of price leadership? This study is the first attempt to describe the dynamic relationships at the national level among the U.S. electricity spot markets. To this end, this study presents empirical findings on the contemporaneous and short-run interdependencies using a vector autoregressive model, causal flows based on directed acyclic graphs, and innovation accounting analysis. To our knowledge, no study to date has examined electricity price interdependencies at the U.S. national level. Further, no study has examined electricity price interdependencies over such an expansive geographical area. The U.S. includes three main power grids, ten different electric reliability councils, and hundreds, if not thousands, of entities involved in generation, transmission, and distribution.
نتیجه گیری انگلیسی
This study adds additional evidence that electricity prices have a mean reversion characteristic, indicating the price series of electricity are stationary. As suggested by other studies, electricity market may behave differently than other commodity markets. In contemporaneous time, causal flow in the electricity markets as given by directed acyclic graphs reflects the three major power grids of U.S., Eastern Interconnected System, Western Interconnected System, and the Texas Interconnected System. Directed acyclic graphs suggest the Western Interconnect is separated from the other two grids. ERCOT in the Texas Interconnected System connects with the Eastern Interconnected System only through ENT. In the Western Interconnected System, PV appears to be driving force for the other western markets for electricity price. ERCOT in Texas Interconnected System and NEPL in the Eastern Interconnected System appear to be exogenous driving forces for electricity price through ENT and ECAR. The information flows from the directed graph analysis indicate that most of information flows occur between physically adjacent spot markets. This result is similar to findings by DeVany and Walls (1999b). It should be noted that the instantaneous price transmission pattern of western area in this study is not identical to the pattern given in Jerko et al. (2004, Fig. 3). In contrast to the final directed acyclic graph (Fig. 5), Jerko, Mjelde, and Bessler suggest that FC influences PV and they show no edge between MIDC and PV in summer. In addition, there is undirected edge between MIDC and FC and between PV and FC in winter in their analysis. The dissimilarity is caused by including only three markets in this area in the current study instead of six markets used in their study, a different time frame, and they present both summer and winter models. In contrast to the directed graph analysis, forecast error variance decomposition and impulse response functions allow for analysis of dynamic information flows over time. For the western markets, PV explains the price uncertainty in MIDC and FC. Further, PV appears to be exogenous at short run. Unlike DeVany and Walls (1999b) and Jerko et al. (2004), PV appears to be an important market in the western U.S. According to their studies, California-Oregon border (DeVany and Walls, 1999b) and South and North Path spot markets in California (Jerko et al., 2004) are the driving forces for the electricity prices in western U.S. This dissimilarity is partially caused by differences in the time frame markets included in the studies. COB and South and North Path spot markets in California are not included in this study because of data limitation. However, noting that PV is the spot market closest to California, the importance of PV in western region is not inconsistent with previous studies. SPP accounts for the large amount of forecast error variance at the longer periods in PJM, ECAR, MAIN, MAPP, ENT, and ERCOT. SPP is a dominant market in Eastern Interconnected System. Support for this result also comes from the impulse response functions. Innovations in SPP cause relatively large responses in non-western markets. Why SPP appears to be a dominant market is not entirely clear. One possible explanation is that the region within SPP relies more on natural gas as an energy source than the other markets. In states associated with SPP, the percentage of natural gas as the primary energy source for generating electricity averages more than 28%. In contrast, the percentage for the entire U.S. is less than 18% (U.S. Department of Energy, 2001). Natural gas is usually the energy source on the margin for peak power generation. Variation in natural gas prices may influence SPP first. The effects of gas price variations are then spread to the other markets. The smaller influence of SPP in NEPL and the western markets may be because of the importance of hydroelectric generation in these regions. The above explanation is not the full explanation. Although ERCOT and ENT highly depend on natural gas to generate electricity, they are not behaving as dominant markets. Reasons why ERCOT and ENT may not behave as dominant markets are as follows. First, most outgoing transmission lines from ERCOT are through ENT, therefore ERCOT may have limited influence on the other markets when compared to SPP. Second, ERCOT and ENT do not rely as heavily as SPP on coal as an energy source. MAPP, MAIN, ECAR, and PJM markets may be influenced by SPP because they depend more on coal than the other markets. Accordingly, similarities between the higher dependency on coal in the SPP, MAPP, MAIN, ECAR, and PJM markets may provide another possible answer for the dominance of SPP. Although there appears to be little contemporaneous time information flows between the western and non-western markets, PJM, SPP, NEPL, and ERCOT help explain the price uncertainty in the western markets at longer horizons. Impulse response functions suggest that shocks in PJM and NEPL cause relatively large and long lasting responses in the western markets. Supporting these findings are the results that the coefficients of NEPL and PJM are statistically significant at 10% level in MIDC, PV, and FC markets, implying NEPL and PJM “Granger cause” MIDC, PV, and FC. Such dynamic behavior cannot be explained by physical transmission connections because of the considerable distance between the two regions. There must be other factors that cause this dynamic relationship between the two regions. Although beyond the VAR analysis, several aspects of the regions may explain the dynamic behavior. First, PJM is the largest and oldest well-organized spot market in the U.S. (Deng and Jiang, 2002). PJM may be providing price discovery information through real-time price data. The western markets can obtain price information from the PJM market because of time zone differences between the two regions. Second, NEPL, PJM, and western markets are considerably more deregulated than the other markets (U.S. Department of Energy and Energy Information Agency, 2003a and U.S. Department of Energy and Energy Information Agency, 2003b). Further, PJM and California spot markets have a common three-tiered trading structure consisting of day-ahead, hour-ahead, and real-time markets. Finally for MIDC, PV, and PJM, there were future's markets during the study period (U.S. Department of Energy, 2002). The relationship between PJM, NEPL, and the western markets may be explained not by physical assets, such as the transmission network, but by institutional arrangements such as the degree of deregulation, trading structure, and existence of future markets. Impulse response functions also shows the innovations in SPP and ERCOT have relatively long lasting positive influence on western markets. Non-western markets generally have larger and quicker responses, but they dampen toward zero. The different responses between western and non-western markets to the shocks in SPP and ERCOT also appear to be due to different institutional arrangements between the western and non-western markets. As expected, the innovations in MIDC, PV, and FC have very little influence on almost every non-western markets, while they have long lasting influence on the western markets. This result is somewhat different than the results presented in DeVany and Walls (1999b) and Jerko et al. (2004). According to their studies, the responses of western markets with respect to the shock of western markets are not as long lasting as found here. This dissimilarity also seems to be caused by the data sets covering different time period. Results from the three studies may indicate markets are evolving in the western U.S. In contrast, the innovations in NEPL, PJM, ECAR, MAIN, MAPP, and ENT have a relatively short influence on non-western markets. The different responses between western markets and non-western markets to its own innovations also indicate there may be certain different institutional aspects between two regions such as the degree of deregulation, the existence of future markets, and market structure. There are some practical questions suggested by the results that are not addressed explicitly but are important issues in the electricity industry. How is the price affected by the different market rules? What is the impact of deregulation on prices? These questions should be topics of further study. In addition, temperature was only exogenous factor considered in the VAR model. Different factors such as variations in demand, congestion on the transmission system, and outages should be considered as factors affecting price in future studies.