Regulated and unregulated Nordic retail prices

Nordic residential electricity consumers can now choose among a number of contracts and suppliers. A large number of households have continued to purchase electricity from the incumbent supplier at default contract terms. In this paper, we compare the situation for such passive customers. Danish default prices are regulated whereas default prices in the other countries are unregulated. Systematic price differences exist among the Nordic countries. However, as wholesale prices sometimes differ the gross margin is a more relevant indicator. Regulated gross margins are lower in Denmark than in Sweden but higher than in Norway and Finland. Because of market design Norwegian default contracts are competitive whereas Swedish contracts provide the retailer with some market power. We interpret the low Finnish margins as a result of municipal retailers continuing traditional pricing from the monopoly period. Danish margins are higher than the competitive Norwegian margins but are earned from a much lower level of consumption. The annually margins earned per consumer are very close in the two countries, which indicates that the Danish regulation is achieving its objective of approaching competitive prices.     

Trends in prices to commercial energy consumers in the competitive Texas electricity market

To date, the price of electricity to commercial or business energy consumers has generally increased at greater rates in the areas of Texas where retail competition has been introduced than in areas that do not enjoy competition. Trends in commercial competitive prices have largely mirrored trends in residential prices. Market restructuring has tended to increase the sensitivity of retail electricity prices to changes in the price of natural gas, the marginal fuel used for generation in Texas. Consequently, the rapid increases in the commodity price of natural gas following restructuring led to increases in competitive electric rates which exceeded the increases in areas not exposed to restructuring, where the fuel component of electric rates tend to reflect a weighted average of the utilities’ fuel costs. There is some evidence that pricing behavior by competitive retailers changed when the retailers affiliated with the incumbent utilities were permitted some pricing flexibility, resulting in a reduction in prices.     

The British Model in Britain: Failing slowly

In 1990, Britain reorganised its electricity industry to run on competitive lines. The British reforms are widely regarded as successful and the model used provides the basis for reforms of electricity industries worldwide. The main reason for this perception of success is major reductions in the real price of electricity with no reduction in service quality. This paper examines whether the reputation of the British reforms is justified. It concludes that the reputation is not justified and that serious fundamental problems are beginning to emerge. The central question is: have the British reforms resulted in the creation of efficient wholesale and retail markets? On this criterion, the reforms have failed. The wholesale market is dominated by obscure long-term contracts, privileged access to the market and self-dealing within integrated generator/retailers, leaving the spot markets with minimal liquidity and unreliable prices. The failure to develop an efficient wholesale market places the onus on consumers to impose competitive forces on electricity companies by switching regularly. Small consumers will not do this and they are paying too much for their power. For the future, there is a serious risk that the electricity industry will become a weakly regulated oligopoly with a veneer of competition.     

Hedging local volume risk using forward markets: Nordic case

With focus on the Nordic electricity market, this paper develops hedging strategies for an electricity distributor who manages price and volume risk from fixed price agreements on stochastic electricity load. Whereas the distributor trades in the spot market at area prices, the financial contracts used for hedging are settled against the system price. Area and system prices are correlated with electricity load, as are price differences. In practice, however, this is often disregarded. Here, we develop a joint model for the area price, the system price and the load, accounting for correlations, and we suggest various strategies for hedging in the presence of local volume risk. We benchmark against a strategy that ignores correlation and hedges at expected load, as is common practice in the industry. Using data from 2013 and 2014 for two Danish bidding areas, we show that our best hedging strategy reduces gross loss by 5.8% and 13.6% and increases gross profit by 3.8% and 9.5%, respectively. Although this is partly due to the inclusion of correlation, we show that performance improvement is mainly driven by the choice of risk measure.     

Futures pricing in electricity markets based on stable CARMA spot models

We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary independent increment process for the low-frequency dynamics, and model the large fluctuations by a non-Gaussian stable CARMA process. The model allows for analytic futures prices, and we apply these to model and estimate the whole market consistently. Besides standard parameter estimation, an estimation procedure is suggested, where we fit the non-stationary trend using futures data with long time until delivery, and a robust L¹-filter to find the states of the CARMA process. The procedure also involves the empirical and theoretical risk premia which – as a by-product – are also estimated. We apply this procedure to data from the German electricity exchange EEX, where we split the empirical analysis into base load and peak load prices. We find an overall negative risk premium for the base load futures contracts, except for contracts close to delivery, where a small positive risk premium is detected. Peak load contracts, on the other hand, show a clear positive risk premium, when they are close to delivery, while contracts in the longer end also have a negative premium.     

Electricity markets volatility: estimates,regularities and risk management applications

The recent deregulation of the market for electric power in many parts of the US and Canada has expanded the set of potential tools for managing the types of risks faced by both generators and consumers of electric power. In particular manufacturing and other firms whose operations are powered by electricity now face, on a continuing basis, the engineering management decisions concerning whether they should buy or produce electricity, and if they are to buy or sell electricity, what types of contracts are optimum. These types of risk management decisions typically involve futures, forwards, options and other financial derivatives. The price and volatility of electric power are known to play an essential role in determining which of these instruments should be used. However, electricity as a commodity possesses certain special features not shared by other commodities and hence its risk properties are not yet well understood. In this paper we consider and test certain hypotheses about the properties of electricity price using recent market data. We find that electricity prices possess certain volatility and other systematic properties that can be characterized by the type and method of delivery of electricity. These properties can be used by firms in formulating their optimal demand and supply schedules of electric power.     

The overnight risk premium in electricity forward contracts

We analyze the risk premium on electricity forward contracts traded for the Nordic and German/Austrian electricity markets. We argue that finding risk premiums by analyzing overnight returns is more relevant than the frequently used ex post approach. The derivatives in these markets can be characterized as trading products and hedging products. Each contract shows a clear increase in trading volume and liquidity when approaching maturity. We link this to a testable hypothesis where financial traders are compensated for holding price risk, and where the sign and magnitude of the risk premium changes depending on the hedging pattern of producers and retailers. Incorporating this in regressions we find that there are higher risk premiums in the period before the forwards become front products, compared to the risk premiums in the front period. Quarterly and monthly contracts show the most significant results.     

Price formation in electricity forward markets and the relevance of systematic forecast errors

Since the liberalisation of the European electricity sector, forward and futures contracts have gained significant interest of market participants due to risk management reasons. For pricing of these contracts an important fact concerns the non-storability of electricity. In this case, according to economic theory, forward prices are related to the expected spot prices which are built on fundamental market expectations. In the following article the crucial impact parameters of forward electricity prices and the relationship between forward and future spot prices will be assessed by an empirical analysis of electricity prices at the European Energy Exchange and the Nord Pool Power Exchange. In fact, price formation in the considered markets is influenced by historic spot market prices yielding a biased forecasting power of long-term contracts. Although market and risk assessment measures of market participants and supply and demand shocks can partly explain the futures-spot bias inefficiencies in the analysed forward markets cannot be ruled out.     

A bilevel model for electricity retailers' participation in a demand response market environment

Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility.     

Impact of wind farm integration on electricity market prices

Wind generation is considered one of the most rapidly increasing resources among other distributed generation technologies. Recently, wind farms with considerable output power rating are installed. The variability of the wind output power, and the forecast inaccuracy could have an impact on electricity market prices. These issues have been addressed by developing a single auction market model to determine the close to real-time electricity market prices. The market-clearing price was determined by formulating an optimal power flow problem while considering different operational strategies. Inaccurate power prediction can result in either underestimated or overestimated market prices, which would lead to either savings to customers or additional revenue for generator suppliers.     

Two-stage stochastic-based scheduling of multi-energy microgrids with electric and hydrogen vehicles charging stations,considering transactions through pool market and bilateral contracts

In order to mitigate greenhouse gas emissions and improve energy efficiency, sustainable energy systems such as multi-energy microgrids (MEMGs) with the high penetration of renewable energy resources (RES) and satisfying different energy needs of consumers have received significant attention in recent years. MEMGs, by relying on renewable resources and energy storage systems along with energy conversion systems, play an essential role in sustainability of energy supply. However, renewable energies are uncertain due to the intermittent nature of solar and wind energy sources. Thus, optimal operation of the MEMGs with the consideration of the uncertainties of RES is necessary to achieve sustainability. In this paper, risk constrained scheduling of a MEMG is carried out with the presence of the PV, wind, biomass, electric vehicles (EVs) and hydrogen vehicles (HVs) charging stations, combined heat and power (CHP), boiler, hydrogen electrolyzer (HE), cryptocurrency miners (CMs), electrical, thermal and hydrogen storage systems, responsive demands. From the trading and business model side, the proposed MEMG optimized operation relies on bilateral contracts between producers and consumers and pool electricity markets. A two-stage stochastic programming method is used for considering the uncertainties of electrical, thermal and hydrogen demands, EV and HV charging stations load, CM load, PV and wind power, and the price of electricity purchased from the pool market. The proposed mixed integer linear programming (MILP) model is solved using the CPLEX solver in GAMS which guarantees to achieve a globally optimal solution. The results show that due to the certain prices of bilateral contracts, the possibility of transaction by bilateral contracts decreases the risk metric CVaR by 50.42%. The simulation results demonstrate that risk of high operation costs while considering flexibility sources, such as storages and demand response (DR) programs, is decreased by 5.45% and 4.6%, respectively. As far as operation costs are concerned, results reveal that using renewable resources decreases operation costs by 34.47%. Moreover, the operation cost is reduced by 5.94% and 4.57% in the presence of storage units and DR programs, respectively. In the same way, storages and DR programs decrease cost of purchased electricity by 13.47% and 14.46%, respectively.     

Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae

We consider the problem of modelling and forecasting the distribution of a vector of prices from interconnected electricity markets using a flexible class of drawable vine copula models, where we allow the dependence parameters of the constituting bivariate copulae to be time-varying. We undertake in-sample and out-of-sample tests using daily electricity prices, and evidence that our model provides accurate forecasts of the underlying distribution and outperforms a set of competing models in their abilities to forecast one-day-ahead conditional quantiles of a portfolio of electricity prices. Our study is conducted in the Australian National Electricity Market (NEM), which is the most efficient power auction in the world. Electricity prices exhibit highly stylised features such as extreme price spikes, price dependency between regional markets, correlation asymmetry and non-linear dependency. The developed approach can be used as a risk management tool in the electricity retail industry, which plays an integral role in the apparatus of modern energy markets. Electricity retailers are responsible for the efficient distribution of electricity, while being exposed to market risk with extreme magnitudes.     

Option value of electricity demand response

As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand–response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand–response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution—specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets.     

Electricity procurement for large consumers based on Information Gap Decision Theory

In the competitive electricity market, consumers seek strategies to meet their electricity needs at minimum cost and risk. This paper provides a technique based on Information Gap Decision Theory (IGDT) to assess different procurement strategies for large consumers. Supply sources include bilateral contracts, a limited self-generating facility, and the pool. It is considered that the pool price is uncertain and its volatility around the estimated value is modeled using an IGDT model. The proposed method does not minimize the procurement cost but assesses the risk aversion or risk-taking nature of some procurement strategies with regard to the minimum cost. Using this method, the robustness of experiencing costs higher than the expected one is optimized and the related strategy is determined. The proposed method deals with optimizing the opportunities to take advantage of low procurement costs or low pool prices. A case study is used to illustrate the proposed technique.     

Contract market power and its impact on the efficiency of the electricity sector

This paper analyzes the pro-competitive effects of financial long-term contracts in oligopolistic electricity markets. This is done in a model that incorporates the main features of the industry: non-storable production, time-varying price-elastic demand, and sequential investment and production decisions. The paper considers contracts for difference that have as reference price the average spot price. Assuming that the spot market coordinator sets competitive prices, the paper shows that installed capacity increases with the quantity of energy contracted, reaching the welfare-maximizing capacity when energy contracted equals this same level. Next, the paper studies the case where the quantity of energy contracted is endogenous and contracts are traded before capacity decisions are taken. Regarding purchasers of contracts, two polar cases are considered: either they are price-taker speculators or they are an aggregation of consumers that auctions a long (buy) contract for a given energy quantity. In the former case the strike price equals the reference price, i.e., arbitrage is perfect, and the quantity of energy contracted falls short of the efficient level. In turn, in the latter case, the strike price equals the average efficient spot price. Moreover, an aggregation of all consumers would choose to auction the social optimum quantity.     

Using renewables to hedge against future electricity industry uncertainties—An Australian case study

A generation portfolio modelling was employed to assess the expected costs, cost risk and emissions of different generation portfolios in the Australian National Electricity Market (NEM) under highly uncertain gas prices, carbon pricing policy and electricity demand. Outcomes were modelled for 396 possible generation portfolios, each with 10,000 simulations of possible fuel and carbon prices and electricity demands. In 2030, the lowest expected cost generation portfolio includes 60% renewable energy. Increasing the renewable proportion to 75% slightly increased expected cost (by $0.2/MWh), but significantly decreased the standard deviation of cost (representing the cost risk). Increasing the renewable proportion from the present 15% to 75% by 2030 is found to decrease expected wholesale electricity costs by $17/MWh. Fossil-fuel intensive portfolios have substantial cost risk associated with high uncertainty in future gas and carbon prices. Renewables can effectively mitigate cost risk associated with gas and carbon price uncertainty. This is found to be robust to a wide range of carbon pricing assumptions. This modelling suggests that policy mechanisms to promote an increase in renewable generation towards a level of 75% by 2030 would minimise costs to consumers, and mitigate the risk of extreme electricity prices due to uncertain gas and carbon prices.     

Financial optimization in the Turkish electricity market: Markowitz's mean-variance approach

Electricity constitutes the input into many products that produced by industry and used by people. Hence, it can be considered as a product or service that has vital importance in human life and economy. Since it has such special properties of instantaneous production and consumption obligation and unfeasible storage, electricity market is not like other markets. In a competitive electricity market, generation company faces price risks and delivery risks. So that risk management is an important part of a generation company and can deeply effect companies’ profitability. This paper focuses on electricity generation asset allocation between bilateral contracts, such as forward contracts, and daily spot market, considering constraints of generating units and spot price risks. The problem is to find the optimal portfolio based on known electricity generation total costs, bilateral contract prices, it employed Turkish historical balanced market hourly system marginal and day-ahead hourly market prices between of 2006 and 2011. There are limited studies about portfolio optimization in electricity markets in literature and this paper should be considered frontier study taking spot market's hourly prices separately as risky assets. Markowitz mean-variance optimization which is claimed to be the beginning of modern portfolio theory in financial sector is used to demonstrate this approach. Mean-variance optimization has been successfully applied to all cases that modeled for electricity market. Some suggestions for future work are also listed in this paper.     

Reallocating risks and returns to scale up adoption of distributed electricity resources

Deployment of distributed electricity resources requires bringing together assets that belong to diverse and geographically diffuse owners. Using the example of distributed solar PV, we analyze the schemes used to encourage/induce owners of distributed assets to make them available for electricity generation. The dominant model in the U.S. is long term power purchase agreements (PPA) offered to owners/consumers by solar developers. We show that these agreements (mis)allocate the electricity price risk to owners/consumers and impose limitations on the scale up of distributed solar. By proper use of financial markets it is possible to shift the electricity price risk from owners/consumers to parties that are better positioned to manage it. The proposed contracts simplify the adoption decision for owners/consumers and can lead to a wider adoption. Removing barriers to scale up requires (i) eliminating the tight coupling between consumers and owners and (ii) rewarding the owners unambiguously for the assets they provide. These necessitate the transformation of the current intermediary firms into full-fledged distributed generators. We discuss the implications of such a transformation and argue that the broad outline of our analysis can be used to assess scale up schemes in other domains of distributed electricity resources as well.     

The progressive inefficiency of replacing renewable obligation certificates with contracts-for-differences in the UK electricity market

This paper looks at the emerging risk/return profile for new renewable assets as a conventional wholesale electricity market progressively decarbonises. Using a detailed fundamental model of price formation risks, under increasing replacement of fossil fuel facilities with onshore and offshore wind, we show that the risk return profile becomes less attractive over time, and may therefore need sustained and possibly increasing policy support. Furthermore, we show that green certificate trading may become progressively more attractive as a supplementary support to wholesale prices, compared to fixed feed-in-tariffs. This is because the increasingly negative correlation between renewable output and wholesale prices reduces its revenue risk compared to fixed feed-in tariffs, if other factors remain constant, and thereby improves conventional financial performance risk metrics. In particular, this suggests that the recent energy policy change in Britain to move away from green certificates and into contracts-for-differences may have been ill-founded.