Psychological barriers in the electric market: study applied to the Nord Pool market

PurposeThis article aims to verify if there are detectable barriers in price levels that are understood to be psychologically important (psychological barriers) in a set of hourly electricity prices. These barriers manifest themselves when the market struggles with a difficulty in crossing the barrier to a different level. Psychological barriers focus on directional price movements around regions of the barrier, thus the importance of understanding investor behavior. The authors intend to contribute empirically to the scarce literature on psychological influences in individuals trading in the energy market, hereby enhancing the knowledge concerning the behavior of investors in this market.Design/methodology/approachThe present work aims to test psychological barriers in the Nord Pool electricity market. Through a sample of hourly data on the Elspot day-ahead market, from 2013 to 2017, three groups of tests were made, following the M-values methodology: (1) uniformity tests, which clearly rejected the uniformity in hourly prices; (2) barrier tests, which included the barrier proximity and barrier hump tests, evidencing psychological barriers and (3) conditional effects tests, which allowed us to conclude in favor of effects of positive returns after approaching a barrier on an upward movement, i.e. the barrier breaches due to the fact that increasing prices tend to lead to further price increases, on average.FindingsUniformity tests, rejected the uniformity in hourly prices; barrier tests, included the barrier proximity and barrier hump tests, evidencing psychological barriers and conditional effects tests, allowed us to conclude in favor of effects of positive returns after approaching a barrier on an upward movement, i.e. the barrier breaches due to the fact that increasing prices tend to lead to further price increases, on average. Another relevant conclusion is that the period from midnight to 9 a.m. is very sensitive, since there is evidence of return and variance effects simultaneously. The implications of these results are potentially relevant, since changes on the variance are usually perceived as a proxy for risk, with changes on the return. It was also concluded that with the increase of the time span from 5 to 10 days on the conditional effects difference tests, there were significant changes on the results, the variance effect is stronger, while the return effect weakens.Research limitations/implicationsHowever, this research presents some limitations that result in representing opportunities for future research. The fact that there are reduced data available for other markets end up limiting the study of the global electricity market. Although Nord Pool is Europe's leading energy market and is seen as one of the most successful energy markets in the world, it would be interesting to do a study with more than one electricity market to make comparative considerations. Although the spot market is the main arena for energy trade, while the intraday market works as a compliment, it would be equally interesting to do a similar study for the intraday market and then compare conclusions. Moreover, in the present study, it was used standard methods in the literature on psychological barriers, but other methods could have been used–for example, those that assume that prices follow the Benford's distribution (Lu and Giles, 2010), which also present a path for future research and opportunity for confirming the robustness of the present results.Practical implicationsWhen the presence of psychological barriers is detected it means that the risk-return relationship becomes weaker around the psychological barrier (round numbers, meaning that electricity traders anchor). Identification of psychological barriers supports the claim that technical analysis strategies based on price support and resistance can be profitable. Therefore, more profitable strategies can be built by traders, but no reconciliation with the efficient market hypothesis (EMH) (provided that in inefficient markets prices should not exhibit any particular pattern). The finding of significant psychological barriers in specific hourly time intervals implies the need to address its practical implications in electricity markets, being so specific, namely, the possibility to earn extraordinarily profits exploiting this anomaly and who wins.Originality/valueThe electricity sector is a determinant sector in economic growth and a factor of development. Herein lies the importance of studying this market, which until now has not occurred in this subject, as far as it was possible to gauge. Are there barriers in the electricity market and should such a presence be taken into account? Investigating the existence of psychological barriers in the electric market becomes relevant, because knowing that investors are psychologically affected by a psychological barrier, can become a useful tool in negotiation, as it can function as another variable in the “equation” which is to trade in a complex market like this. Proving the potential presence of a psychological barrier may lead investors to believe in the idea of levels of resistance or levels of support, affecting their decision-making and price dynamics.

Application of a new constraint handling method for economic dispatch considering electric market

In this paper, optimal load dispatch problem under competitive electric market (OLDCEM) is solved by the combination of cuckoo search algorithm (CSA) and a new constraint handling approach, called modified cuckoo search algorithm (MCSA). In addition, we also employ the constraint handling method for salp swarm algorithm (SSA) and particle swarm optimization algorithm (PSO) to form modified SSA (MSSA) and modified PSO (MPSO). The three methods have been tested on 3-unit system and 10-unit system under the consideration of payment model for power reserve allocated, and constraints of system and generators. Result comparisons among MCSA and CSA indicate that the proposed constraint handling method is very useful for metaheuristic algorithms when solving OLDCEM problem. As compared to MSSA, MPSO as well as other previous methods, MCSA is more effective by finding higher total benefit for the two systems with faster manner and lower oscillations. Consequently, MCSA method is a very effective technique for OLDCEM problem in power systems.

Improved particle swarm optimization algorithms for economic load dispatch considering electric market

Economic load dispatch problem under the competitive electric market (ELDCEM) is becoming a hot problem that receives a big interest from researchers. A lot of measures are proposed to deal with the problem. In this paper, three versions of PSO method such as conventional particle swarm optimization (PSO), PSO with inertia weight (IWPSO) and PSO with constriction factor (CFPSO) are applied for handling ELDCEM problem. The core duty of the PSO methods is to determine the most optimal power output of generators to obtain total profit as much as possible for generation companies without violation of constraints. These methods are tested on three and ten-unit systems considering payment model for power delivered and different constraints. Results obtained from the PSO methods are compared with each other to evaluate the effectiveness and robustness. As results, IWPSO method is superior to other methods. Besides, comparing the PSO methods with other reported methods also gives a conclusion that IWPSO method is a very strong tool for solving ELDCEM problem because it can obtain the highest profit, fast converge speed and simulation time.

Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization

In the paper, a proposed particle swarm optimization (PPSO) is implemented for dealing with an economic load dispatch (ELD) problem considering the competitive electric market. The main task of the problem is to determine optimal power generation and optimal reserve generation of available thermal generation units so that total profit of all the units is maximized. In addition, constraints, such as generation limit and reserve limit of each unit, power demand and reserve demand, must be exactly satisfied. PPSO is an improved version of conventional particle swarm optimization (PSO) by combining pseudo gradient method, constriction factor and a newly proposed position update method. On the other hand, in order to support PPSO to reach good results for the considered problem, a new constraint handling method (NCHM) is also proposed for determining maximum reserve generation and correcting reserve generation. Three test systems with 3, 10 and 20 units are employed to evaluate the real performance of PPSO. In addition to the comparisons with previous methods, salp swarm optimization (SSA), modified differential evolution (MDE) and eight other PSO methods are also implemented for comparisons. Through the result comparisons, two main contributions of the study are as follows: (1) NCHM is very effective for PSO methods to reach a high success rate and higher solution quality, (2) PPSO is more effective than other methods. Consequently, NCHM and PPSO are the useful combination for the considered problem.