## 3 Research Objectives and Methodology  
### Research Objectives  
The primary objective of this manuscript is to examine and quantify the evolution of wholesale electricity price volatility in the context of the increasing integration of renewable energy sources (RES), with particular attention to its temporal, seasonal, and inter-annual patterns. Previous research in this area has shown that, although the increasing share of RES generally leads to a decrease in the average market price of electricity, it also causes an increase in its short-term volatility, mainly due to the natural variability of generation from solar and wind sources. This increased volatility poses a significant challenge to the stability of energy markets, generation and distribution planning, as well as energy policy making.  
The manuscript focuses on a detailed assessment of electricity price volatility in the day-ahead market (DAM) at different time scales--from hourly to daily to monthly--in order to identify seasonal and structural changes in price behaviour. An important part of the research is also to assess the temporal correspondence between extreme price fluctuations (including negative prices) and the intensity of generation from RES, particularly from solar and wind power plants. The highest fluctuations are assumed to occur during periods of high production from these sources, which will be the subject of separate analytical attention.  
In addition to a basic analysis of volatility, the study aims to compare year-on-year trends and track how volatility has evolved over time, particularly in the period before and after the energy crisis of 2021-2022. In this way, it will be possible to address the question of whether this is a temporary phenomenon or a long-term structural change resulting from the increasing share of RES in the energy mix.  
The research also includes the development of user-friendly analytical tools that allow flexible data processing and interpretation without the need for complex statistical platforms. These tools provide the ability to dynamically select and aggregate input data by energy source type, time period, or desired temporal granularity (e.g., hourly, daily, monthly). Such an approach significantly enhances the practicality of the analyses in terms of routine operational practice, whether by regulators, transmission and distribution system operators, or market analysts dealing with electricity price developments.  
From a research perspective, the proposed analytical framework allows testing hypotheses about the relationships between renewable generation and price volatility over time. Thanks to the possibility of fast data aggregation and visualisation, seasonal effects, temporal patterns of extreme price fluctuations, or impacts of specific policies (e.g., flexibility support, capacity deployment mechanisms) can be efficiently identified. The tools can also be used to verify outputs from advanced models or as an entry point for further modelling (e.g., volatility prediction models, extreme price classification models).  
In the field of energy policy, this approach is a way to make complex analyses accessible to a wider range of actors such as regional regulators, municipalities, or organisations monitoring the implementation of climate commitments. This allows policy makers to better assess the effectiveness of measures taken, analyse the risks associated with shortfalls or overproduction of RES energy, and design targeted interventions for specific periods or regions based on real data.  
The potential for cross-border comparisons is also an important aspect. Thanks to the easy customisability of the input data, the tools can be applied to different countries or regions and compare how price volatility varies depending on the type of energy mix, the regulatory framework, or the degree of market interconnection. Such comparisons are particularly valuable in the design of harmonised European policies aimed at reducing price uncertainty in a period of increasing RES share.