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Under the Kyoto protocol, emissions trading was imposed upon the Nordic Nord Pool Spot market in 2005. The purpose of this paper is to identify and characterize an important side‐effect of emissions trading on electricity spot market price behavior by statistically comparing price behavior before and after emissions trading was introduced.

The analysis is based on an analysis of the skill of regression models in explaining price behavior before and after 2005.

It turns out that regression models based on background variables such as temperature, water reservoir levels, and even the price of emission rights themselves lose much of their skill from 2005 onwards. The histogram of the residual time series of an optimally calibrated regression model demonstrates a considerably more “fat‐tailed” behavior after 2005, with a much higher volatility and reduced amenability for regression by background variables.

The results point to an increased medium‐ and long‐term uncertainty in the Nordic electricity spot market, brought about by emissions trading as an unintended side‐effect. It seems emissions trading has introduced a stronger “psychological” component into price behavior, increasing its volatility and making it prone to more frequent price spikes. This has made the electricity market more difficult for market managers and regulators to manage.

The paper presents the first statistical attempt to quantify the way electricity spot price dynamics have changed in Europe after starting the Emissions Trading Scheme based on the Kyoto protocol.

The electric power industry has been moving from a regulated monopoly structure to a deregulated market structure in many countries. The purpose of this study is to comprehensively review the existing markets to study advantages, issues involved and lessons learnt to benefit emerging electricity markets.

The paper employs a comprehensive review of existing competitive electricity market models in USA (California), UK, Australia, Nordic Countries (Norway), and developing country (Chile) to analyze the similarities, differences, weaknesses, and strengths among these markets based on publically available data, literature review and information.

Ongoing or forthcoming electricity sector restructuring activities in some countries can be better designed based on lessons learnt from existing markets and incorporating their own political, technical and economical contexts. A template for design of successful electricity market has also been presented.

This study is limited to a comparative analysis of five markets and can be extended in the future for other existing and emerging electricity markets.

The discussed weaknesses and strengths of existing electricity markets in this study can be practically utilized to improve the electricity industry market structures leading to several social benefits including lower electricity cost.

The comprehensive review and analysis of five existing markets, physically located in different continents, may be used as an assistance or reference guide to benefit the emerging electricity markets in other countries.

The forward curve dynamics in the Nordic electricity market is examined. Six years of price data on futures and forward contracts traded in the Nordic electricity market are analysed. For the forward price function of electricity, we specify a multi‐factor term structure models in a Heath‐Jarrow‐Morton framework. Principal component analysis is used to reveal the volatility structure in the market. A two‐factor model explains 75 per cent of the price variation in our data, compared to approximately 95 per cent in most other markets. Further investigations show that correlation between short‐ and long‐term forward prices is lower than in other markets. We briefly discuss possible reasons why these special properties occur, and some consequences for hedging exposures in this market.

This study aims to investigate the effects of thermal–hydro interconnection on the revenues, market value and curtailment of variable renewable energy (VRE). The increasing market shares of VRE sources in the Northern European power system cause declining revenues for VRE producers, because of the merit-order effect. A sparsely studied flexibility measure for mitigating the drop in the VRE market value is increased interconnection between thermal- and hydropower-dominated regions.

A comprehensive partial equilibrium model with a high spatial and temporal resolution is applied for the analysis.

Model simulation results for 2030 show that thermal–hydro interconnection will cause exchange patterns that to a larger extent follow VRE production patterns, causing significantly reduced VRE curtailment. Wind value factors are found to decrease in the hydropower-dominated regions and increase in thermal power-dominated regions. Because of increased average electricity prices in most regions, the revenues are, however, found to increase for all VRE technologies. By only assuming the planned increases in transmission capacity, total VRE revenues are found to increase by 3.3 per cent and VRE electricity generation increases by 3.7 TWh.

The current study is, to the authors' knowledge, the first to analyze the effect of interconnection between thermal- and hydropower-dominated regions on the VRE market value, and the authors conclude that this is a promising flexibility measure for mitigating the value-drop of VRE caused by the merit-order effect. The study results demonstrate the importance of taking the whole power system into consideration when planning future transmission capacity expansions.

The purpose of this paper is to analyse how the regional effects of expansion can be managed under the constraints of voluntary cooperation. This paper studies international cooperation on electricity transmission expansions in a region of countries that shares a joint electricity infrastructure.

Cooperative game theory and the partition-function form were applied in combination with benefit–cost ratios to model and analyse the incentives to cooperate under different cost allocation rules. Empirical background was provided by a case study of a transmission investment agreement made on the Nordic electricity market.

Both cost sharing and the composition of expansion plans were identified as ways of reaching regional agreements. It was found that agreements based on proportional division of costs in relation to benefits were the best choice for voluntary cooperation.

The study did not analyse the effects or relevance of surplus sharing in addition to that implied by cost sharing, nor has it studied the regulatory and legal requirements for implementing side-payments between countries in grid expansions. These issues could benefit from more study.

The results are relevant for the development of international cooperation on grid expansions and as an input to regulations and policies aimed at promoting regional perspectives, in particular for the case of a single internal energy market in Europe.

The paper contributes with an analysis of incentives for transmission expansions in a multinational environment subject to voluntary provision and a lack of supranational authorities with decision power.

We consider the partial hedging of stochastic electricity load pattern with static forward strategies. We assume that the company under consideration maximizes the risk adjusted expected value of its electricity cash flows. First, we calculate an optimal hedge ratio and after that we use this hedge ratio to solve the optimal hedging time. Our results indicate, for instance that agents with high load volatility hedge later than agents that have low load volatility. Moreover, negative correlation between forwards and electricity load pattern postpones the hedging timing.

Empirical publications on the time series modeling and forecasting of electricity prices vary widely regarding the conditions, and the findings make it difficult to generalize results. Against this background, it is surprising that there is a lack of statistics-based literature reviews on the forecasting performance when comparing different models. The purpose of the present study is to fill this gap.

The authors conduct a comprehensive literature analysis from 2000 to 2015, covering 86 empirical studies on the time series modeling and forecasting of electricity spot prices. Various statistics are presented to characterize the empirical literature on electricity spot price modeling, and the forecasting performance of several model types and modifications is analyzed. The key issue of this study is to offer a comparison between different model types and modeling conditions regarding their forecasting performance, which is referred to as a quasi-meta-analysis, i.e. the analysis of analyses to achieve more general findings independent of the circumstances of single studies.

The authors find evidence that generalized autoregressive conditional heteroscedasticity models outperform their autoregressive–moving-average counterparts and that the consideration of explanatory variables improves forecasts.

To the best knowledge of the authors, this paper is the first to apply the methodology of meta-analyses in a literature review of the empirical forecasting literature on electricity spot markets.

This study aims to formulate a mechanism design in the derivatives market, summarizing a framework to set up the Brazilian electricity futures market.

This exploratory study formulates a mechanism design in the derivatives market, summarizing a framework to set up the Brazilian electricity futures market.

The results show a positive economic outcome for the creation of the Brazilian futures electricity market.

The main feature in this work is to summarize a framework to set up the Brazilian electricity futures market applying mechanism design, applicable in other countries. The features of the mechanism are the space of expected results (Z), the strategies to survey the environmental space (θ) and the mechanism design – messages space (M).

This paper aims to study the rationality of residential electricity customers' decision-making based on their behavior in liberalized electricity markets.

Finnish residential customers' saving opportunities from supplier switching are studied by using price data obtained from the Finnish Energy Market Authority. The saving opportunities are then compared with the switches accomplished. The paper also examines the dispersion of offer prices (the prices that are offered to customers who wish to switch away from the default contract) by comparing all the offers for one- and two-year contracts in the largest network area in Finland (2007-2010).

About 60-70 percent of residential customers are estimated to purchase electricity under a default contract from their local supplier. However, notable savings might be achieved by switching from default contracts to competitive contracts. The analysis shows that for the majority of customers, the offer prices were always cheaper than the default contract prices during the examined period. For customers with electric heating, the average saving opportunity (compared to the default price) was over 200 year in 2009 and 2010. The range of offer prices for contracts with similar terms has not decreased despite the regulator's efforts to facilitate supplier switching by providing a price comparison service. The discrepancy between saving opportunities and switching rates reflects the effects of the limits of consumer rationality in the retail electricity markets.

The paper presents a longitudinal study about the benefits of supplier switching and the development of offer price dispersion.

Several research papers related to electricity price forecasting have been reported in the leading journals in last 20 years. The purpose of this paper is to present a comprehensive survey and comparison of these techniques.

The present article provides an overview of the statistical short‐term price forecasting (STPF) models. The basic theory of these models, their further classification and their suitability to STPF has been discussed. Quantitative evaluation of the performance of these models in the framework of accuracy achieved and computation time taken has been performed. Some important observations of the literature survey and key issues regarding STPF methodologies are analyzed.

It has been observed that price forecasting accuracy of the reported models in day‐ahead markets is better as compared to that in real time markets. From a comparative analysis perspective, there is no hard evidence of out‐performance of one model over all other models on a consistent basis for a very long period. In some of the studies, linear models like dynamic regression and transfer function have shown superior performance as compared to non‐linear models like artificial neural networks (ANNs). On the other hand, recent variations in ANNs by employing wavelet transformation, fuzzy logic and genetic algorithm have shown considerable improvement in forecasting accuracy. However more complex models need further comparative analysis.

This paper is intended to supplement the recent survey papers, in which the researchers have restricted the scope to a bibliographical survey. Whereas, in this work, after providing detailed classification and chronological evolution of the STPF techniques, a comparative summary of various price‐forecasting techniques, across different electricity markets, is presented.