arXiv subjects

Tomasz Weron

Publications and source records attributed to Tomasz Weron.

6 recordsLinked to original sources

arXiv2026

From electricity prices to profits: multidimensional probabilistic forecasting for BESS trading

This article examines various methods of constructingmultidimensional probabilistic forecasts of electricity prices. Building on the Multiple Split (MS) method, it incorporates forecast averaging across estimation windows of different lengths and compares its performance with that of other, well-established methods. The research demonstrates that the ensemble representation of the price distribution is particularly useful in battery energy storage system (BESS) management. It enables the direct construction of probabilistic forecasts of daily profits. These forecasts can be used to determine optimal charging and discharging hours, as well as to support risk management decisions. The methods are evaluated using data from the German and Spanish day-ahead electricity markets from 2021-2024. The results indicate that theMS method with averaging (MS-ave) generally outperforms the other considered approaches in terms of Prediction Interval Coverage Probability (PICP), the Continuous Ranked Probability Score (CRPS) and the Energy Score (ES). Moreover, it is superior in supporting BESS trading strategies, particularly in case of non-zero operational costs.

q-fin.ST↗

arXiv2025

Multi-layer diffusion model of photovoltaic installations

Nowadays, harmful effects of climate change are becoming increasingly apparent. A vital issue that must be addressed is the generation of energy from non-renewable and often polluting sources. For this reason, the development of renewable energy sources is of great importance. Unfortunately, too rapid spread of renewables can disrupt stability of the power system and lead to energy blackouts. One should not simply support it, without ensuring sustainability and understanding of the diffusion process. In this research, we propose a new agent-based model of diffusion of photovoltaic panels. It is an extension of the q-voter model that utilizes a multi-layer network structure. The novelty is that both opinion dynamics and diffusion of innovation are studied simultaneously on a multidimensional structure. The model is analyzed using Monte Carlo simulations and the mean-field approximation. The impact of parameters and specifications on the basic properties of the model is discussed. Firstly, we show that for a certain range of parameters, innovation always succeeds, regardless of the initial conditions. Secondly, that the mean-field approximation gives qualitatively the same results as computer simulations, even though it does not utilize knowledge of the network structure.

cs.CE↗

arXiv2019

Impact of independence on polarization of opinions

Polarization of societies is getting more and more attention from researchers working at the intersection of many fields, because it seems to be a defining feature of many public domains. In this paper, we are going to investigate how the unwillingness to yield to the group pressure, also known as independence, influences this phenomenon. In particular, we would like to answer the question whether independent choices of people could alter the dynamics of a system that otherwise would become polarized. A modified version of the $q$-voter model will be used for that purpose. From our findings it follows that the impact of independence is at least two-fold. At low independence levels the consensus-polarization transition between two antagonistic groups sets in quicker than in the absence of independence. Higher levels induce additional transition in the system, from a polarized state to a disordered one.

physics.soc-ph↗

arXiv2017

Conformity, anticonformity and polarization of opinions: insights from a mathematical model of opinion dynamics

Understanding and quantifying polarization in social systems is important because of many reasons. It could for instance help to avoid segregation and conflicts in the society or to control polarized debates and predict their outcomes. In this paper we present a version of the $q$-voter model of opinion dynamics with two types of response to social influence: conformity (like in original $q$-voter model) and anticonformity. We put the model on a social network with the double-clique topology in order to check how the interplay between those responses impacts the opinion dynamics in a population divided into two antagonistic segments. The model is analyzed analytically, numerically and by means of Monte Carlo simulations. Our results show that the systems undergoes two bifurcations as the number of cross-links between cliques changes. Below the first critical point consensus in the entire system is possible. Thus two antagonistic cliques may share the same opinion only if they are loosely connected. Above that point the system ends up in a polarized state.

physics.soc-ph↗

arXiv2016

The interplay between conformity and anticonformity and its polarizing effect on society

Simmering debates leading to polarization are observed in many domains. Although empirical findings show a strong correlation between this phenomenon and modularity of a social network, still little is known about the actual mechanisms driving communities to conflicting opinions. In this paper, we used an agent-based model to check if the polarization may be induced by a competition between two types of social response: conformity and anticonformity. The proposed model builds on the q-voter model (Castellano et al. 2009b) and uses a double-clique topology in order to capture segmentation of a community. Our results indicate that the interplay between intra-clique conformity and inter-clique anticonformity may indeed lead to a polarized state of the entire system. We have found a dynamic phase transition controlled by the fraction $L$ of cross-links between cliques. In the regime of small values of $L$ system is able to reach the total positive consensus. If the values of $L$ are large enough, anticonformity takes over and the system always ends up in a polarized stated. Putting it the other way around, the segmentation of the network is not a sufficient condition for the polarization to appear. A suitable level of antagonistic interactions between segments is namely required to arrive at a polarized steady state within our model.

physics.soc-ph↗

arXiv2013

Rewiring the network. What helps an innovation to diffuse?

A fundamental question related to innovation diffusion is how the social network structure influences the process. Empirical evidence regarding real-world influence networks is very limited. On the other hand, agent-based modeling literature reports different and at times seemingly contradictory results. In this paper we study innovation diffusion processes for a range of Watts-Strogatz networks in an attempt to shed more light on this problem. Using the so-called Sznajd model as the backbone of opinion dynamics, we find that the published results are in fact consistent and allow to predict the role of network topology in various situations. In particular, the diffusion of innovation is easier on more regular graphs, i.e. with a higher clustering coefficient. Moreover, in the case of uncertainty - which is particularly high for innovations connected to public health programs or ecological campaigns - a more clustered network will help the diffusion. On the other hand, when social influence is less important (i.e. in the case of perfect information), a shorter path will help the innovation to spread in the society and - as a result - the diffusion will be easiest on a random graph.

physics.soc-ph↗