• Energy Research
• 13. Climate action close

The ongoing transformation of the electricity market has reshaped the hydropower production paradigm for storage reservoir systems, with a shift from strategies oriented towards maximizing regional energy production to strategies aimed at the revenue maximization of individual systems. Indeed, hydropower producers bid their energy production scheduling 1 day in advance, attempting to align the operational plan with hours where the expected electricity prices are higher. As a result, the accuracy of 1-day ahead prices forecasts has started to play a key role in the short-term optimization of storage reservoir systems. This paper aims to contribute to the topic by presenting a comparative assessment of revenues provided by short-term optimizations driven by two econometric models. Both models are autoregressive time-adapting hourly forecasting models, which exploit the information provided by past values of electricity prices, with one model, referred to as Autoarimax, additionally considering exogenous variables related to electricity demand and production. The benefit of using the innovative Autoarimax model is exemplified in two selected hydropower systems with different storage capacities. The enhanced accuracy of electricity prices forecasting is not constant across the year due to the large uncertainties characterizing the electricity market. Our results also show that the adoption of Autoarimax leads to larger revenues with respect to the use of a standard model, increases that depend strongly on the hydropower system characteristics. Our results may be beneficial for hydropower companies to enhance the expected revenues from storage hydropower systems, especially those characterized by large storage capacity.

AbstractThere is a strong link between water and energy in municipal water systems then the Alliance to Save Energy coined the term “Watergy” [1].Each component of the integrated water system contributes differently to the energy balance. With regard to urban water distribution systems (WDS), the pumping energy cost represents the single largest part of the total operational cost, also magnified by every litre of water lost to leaks. Even a small increase in operational efficiency may result in significant cost savings to the water industries.Therefore the inefficient management of water distribution systems results not only into depletion of water resources but also into energy consumption that increase CO2 emissions related also to the treatment of water volumes greater than needed, with use of excessive chemical components and consequent higher environmental global impact.The research outlined in this contribution was born with the aim to develop appropriate methodologies and tools to support the optimization of the WDS performance, in terms of water saving and reduction of energy consumptions and consequently environmental impacts. The integration of advanced WDS hydraulic modelling with a material and energy flow analysis is proposed herein, where the output of the hydraulic simulations permits to get more accurate input for a metabolic analysis of the system. Next phases of this research will test the integrated model under different scenarios, aimed at quantifying the environmental impact of different WDS management solutions by means of selected indicators.

This paper examines the complex dependence between peak district heating demand and outdoor temperature. Our aim is to provide the probability law of heat demand given extreme weather conditions, and derive useful implications for the management and production of thermal energy. We propose a copula-based approach and consider the case of the city of Bozen-Bolzano. The analysed data concern daily maxima heat demand observed from January 2014 to November 2017 and the corresponding outdoor temperature. We model the univariate marginal behaviour of the time series of heat demand and temperature with autoregressive integrated moving average models. Next, we investigate the dependence between the residuals’ time series through several copula models. The selected copula exhibits heavy-tailed and symmetric dependence. When taking into account the conditional behaviour of heat demand given extreme climatic events, the latter strongly affects the former, and we find a high probability of thermal energy demand reaching its peak.

AbstractUnderwater soundscapes and their unique acoustic signatures are mainly generated through movement of streambed sediment, subsequent particle collisions, and turbulence created by water flowing over submerged obstructions such as rocks and woody debris. This study characterized river soundscapes in Alpine rivers of Trentino, (North East Italy) with the combined use of hydrophones and a new microelectricalmechanical systems based device (Hydroflown) that is capable of measuring particle velocity components of the sound field. Pool and riffle habitats affected and unaffected by hydropeaking were characterized in terms of their particle velocity and sound pressure levels across 10 octave bands (acoustic signature) to assess temporal variations in overall sound levels, changes in frequency composition, and relationship to hydromorphological habitat parameters. Data revealed that soundscapes affected by hydropeaking are highly homogenized, and sound pressure levels are strongly correlated with turbine discharge, which results in rapid, multiple‐fold spikes in low frequency amplitude levels within the typical hearing range of common teleost fish species. The outcomes of this study provide the basis for further examination of the resulting behavioural and physiological responses of organisms to anthropogenic changes in river soundscapes.

Sustainable urban energy planning depends on how renewable and local sources are integrated, how smart systems are implemented, and how synergies between regional and national policies are maximized. This study presents a methodology for the design of 100% renewable energy systems aiming to optimize the use of biomass and energy exchange with the national system while ensuring electricity import and export balance. The proposed procedure combines the robustness of the EnergyPLAN hourly energy system simulation model with the flexibility of multiple-criteria decision analysis. The result is a suitable methodology able to identify the best energy scenario based on a deep multi-parameter analysis from a technical point of view. A test case is proposed aiming at achieving 100% renewable energy for the Alpine city of Bozen-Bolzano in 2050.