[en] In an electricity market, the retailer sets up contracts with the wholesale side for purchasing electricity and with the customers for its selling. This paper proposes a mathematical method based on mixed-integer stochastic programming to determine the optimal sale price of electricity to customers and the electricity procurement policy of a retailer for a specified period. The retailer has multiple choices for electricity procurement, such as spot market, forward contracts, call options and self-production. Risk is considered and modeled by conditional value-at-risk methodology. Also, the competition between retailers is modeled using a market share function. A case study is illustrated to demonstrate the capability of the proposed method. (author)

[en] In a competitive market scenario, consumers make payments for the consumption of electricity to retailers at fixed tariff. The retailers buy power at the Market Clearing Price (MCP) in spot market and/or through bilateral contract at agreed upon price. Due to these different modes at buying and selling ends, the retailers are faced with an involved task of estimating their payoffs along with the risk-quantification. The methodology presented in this paper gives a range of bilateral quantity and associated price for a retailer to ensure risk-constrained payoff. The exercise is carried out with a single retailer in the market as well as for a case of competition amongst two retailers. Risk is quantified using Risk Adjusted Recovery on Capital (RAROC). The problem is evaluated to get a range of bilateral quantity to be quoted for a particular bilateral price at fixed tariff of loyal load and fixed value of switching load. This summary combined with risk-averseness of the retailer leads him to make a judicial choice about bilateral transactions such that it leads to a risk-constrained payoff. (author)

No abstract available

[en] As market intermediaries, electricity retailers buy electricity from the wholesale market or self-generate for re(sale) on the retail market. Electricity retailers are uncertain about how much electricity their residential customers will use at any time of the day until they actually turn switches on. While demand uncertainty is a common feature of all commodity markets, retailers generally rely on storage to manage demand uncertainty. On electricity markets, retailers are exposed to joint quantity and price risk on an hourly basis given the physical singularity of electricity as a commodity. In the literature on electricity markets, few articles deals on intra-day hedging portfolios to manage joint price and quantity risk whereas electricity markets are hourly markets. The contributions of the article are twofold. First, we define through a VaR and CVaR model optimal portfolios for specific hours (3 a.m., 6 a.m.,...,12 p.m.) based on electricity market data from 2001 to 2011 for the French market. We prove that the optimal hedging strategy differs depending on the cluster hour. Secondly, we demonstrate the significantly superior efficiency of intra-day hedging portfolios over daily (therefore weekly and yearly) portfolios. Over a decade (2001-2011), our results clearly show that the losses of an optimal daily portfolio are at least nine times higher than the losses of optimal intra-day portfolios. (authors)

[en] This paper studies asymmetric price responses of individual firms, via daily retail prices of almost all gasoline stations in the Netherlands and suggested prices of the five largest oil companies over more than two years. I find that 38% of the stations respond asymmetrically to changes in the spot market price. Hence, asymmetric pricing is not a feature of the market as a whole, but of individual firms. For asymmetrically pricing stations, the asymmetry is substantial directly after a change but disappears after one or two days. I study station-specific characteristics and conclude that asymmetric pricing seems to be a phenomenon that is randomly distributed across stations. I also find that none of the five largest oil companies adjust their suggested prices asymmetrically.

[en] Industry structure: Over the last few years or so there has been a growing trend towards vertical reintegration between generators and retailers in the Australian electricity industry. By 2013, the three largest power companies (Origin Energy, AGL Energy and EnergyAustralia) jointly supplied over 75% of small electricity retail customers and controlled about 36% of the generation capacity in the NEM region. Vertical reintegration enables these companies to internally manage the risk of price volatility in the spot market and at the same time poses a potential barrier to entry and expansion for generators and retailers that are not vertically integrated. Since 2009, around 45% of the new generation capacities commissioned or committed in the NEM regions is owned by these three large companies. In contrast, investments in generation by entities that are not integrated have been negligible in the same period. Such reintegration has further reduced the scope for new market participants to become active in the energy futures markets to manage risks and secure future earnings. By 2011, low liquidity in the energy futures markets was observed, especially in South Australia where the electricity industry has the highest degree of vertical integration. Such a low liquidity has created a challenging operating environment that, it is argued, is likely to deter efficient investments by new entrants

[en] This study analyses original panel data from 86 countries between 1985 and 2006. Econometric methods were used to identify the effects of different policy devices of power sector reforms on performance indicators (installed capacity per capita, transmission and distribution loss) in the countries analyzed. The research findings suggest that reform variables such as the entry of independent power producers (IPPs), unbundling of generation and transmission, establishment of regulatory agencies, and the introduction of a wholesale spot market are the driving forces of increasing generation capacity, as well as reducing transmission and distribution loss in the respective regions. In this study, we can assume that, firstly, different electric industry's reform policies/measures have different impacts on geographically and economically diverse countries. Secondly, a country's state of economic development has a different impact on policy effects of reforms. Thirdly, coexistent with independent regulatory agencies, reform policy becomes more powerful in realizing sector performances. (author)

[en] A power trader benefits from accurate price predictions. Based on market analyses, KEMA Connect has developed - in cooperation with Essent Energy Trading - a market model, enhancing the insight into market operation and one's own actions and thus resulting in accurate price predictions

[en] In 'Retail competition in electricity markets' (Energy Policy, 37(2), February 2009, Pages 377-386) it is argued by Defeuilly that the introduction of retail competition into electricity markets gave rise to great expectations that it failed to meet, and that this was primarily the fault of Austrian economic thinking. The main purpose of this note is to explain why both of these propositions are incorrect. A few further comments challenge his subsequent suggestion that the competitive process in electricity is so constrained by the limitations of consumer decision-making and electricity technology as to cast doubt on the policy of opening the retail market to competition

No abstract available