Search Results (90)

In the Italian intra-day electricity market (MI-XBID), where energy positions can be adjusted up to one hour before delivery, imbalance charges due to forecast errors from non-programmable renewable sources represent a critical issue. This work focuses on photovoltaic (PV) systems, whose production variability makes them particularly sensitive to forecast accuracy. To address these challenges, a comprehensive methodology for assessing and mitigating imbalance penalties by integrating a short-term PV forecasting model with a battery energy storage system is proposed. Unlike conventional approaches that focus exclusively on improving statistical accuracy, this study emphasizes the economic and regulatory impact of forecast errors under the current Italian imbalance settlement framework. A hybrid physical-artificial neural network is developed to forecast PV power one hour in advance, combining historical production data and clear-sky irradiance estimates. The resulting imbalances are analyzed using regulatory tolerance thresholds. Simulation results show that, by adopting a control strategy aimed at maintaining the battery’s state of charge around 50%, imbalance penalties can be completely eliminated using a storage system sized for just over 2 equivalent hours of storage capacity. The methodology provides a practical tool for market participants to quantify the benefits of storage integration and can be generalized to other electricity markets where tolerance bands for imbalances are applied. Full article

Recent European regulations promote distributed energy resources as alternatives to centralized generation. This study compares utility-scale and distributed photovoltaic (PV) systems coupled with Battery Energy-Storage Systems (BESSs) in the Italian electricity market, analyzing different battery sizes. A multistage stochastic mixed-integer linear programming model, using Monte Carlo PV production scenarios, optimizes day-ahead and intra-day market offers while incorporating PV forecast updates. In real time, battery flexibility reduces imbalances. Here we show that, to ensure dispatchability—defined as keeping annual imbalances below 5% of PV output—a 1 MW PV system requires 220 kWh of storage for utility-scale and 50 kWh for distributed systems, increasing the levelized cost of electricity by +13.1% and +1.94%, respectively. Net present value is negative for BESSs performing imbalance netting only. Therefore, a multiple service strategy, including imbalance netting and energy arbitrage, is introduced. Performing arbitrage while keeping dispatchability reaches an economic optimum with a 1.7 MWh BESS for utility-scale systems and 1.1 MWh BESS for distributed systems. These results show lower PV firming costs than previous studies, and highlight that under a multiple-service strategy, better economic outcomes are obtained with larger storage capacities. Full article

Battery energy storage systems (BESS) rely on accurate electricity price forecasts to maximize arbitrage profits in day-ahead markets. We examined whether specific forecasting models, ranging from statistical benchmarks to machine learning methods, consistently deliver superior financial outcomes for storage operators. Using real market data from the Italian day-ahead electricity market over 2020–2024, we compared univariate singular spectrum analysis (SSA), ARIMA, SARIMA, random forests, and a 30-day simple moving average under a unified trading framework. All models were evaluated based on their ability to generate arbitrage profits. Univariate SSA clearly outperformed all alternatives, achieving on average 98% of the theoretical maximum profit while maintaining the lowest forecast error. Among the other models, simpler approaches performed surprisingly well: they achieved comparable, if not superior, profit performance to more complex, hour-specific, or computationally intensive configurations. These results were robust to plausible variations in battery parameters and retraining schedules, suggesting that univariate SSA offers a uniquely effective forecasting solution for battery arbitrage and that simplicity can often be more effective than complexity in operational revenue terms. Full article

This paper presents an overall concept developed by ENEA (the Italian National Agency for New Technologies, Energy and Sustainable Economic Development) in the Italian framework of renewable energy communities (RECs). The proposed work is driven by the idea that RECs are part of a long-term vision aimed at achieving the broader concept of smart communities (SCs) through smart energy communities (SECs). SECs are, therefore, the evolution of RECs toward SCs, where ICT (information and communications technology) and digitalization play a pivotal role in fostering and boosting the energy transition and addressing societal challenge goals by 2050. In this scenario, the proposed approach is based on three dimensions, as follows: digital tools, use cases, and the observatory. Digital tools can be utilized at different stages of the creation of RECs, ranging from the design and engagement phase to evaluation, analysis, and the token economy. The second dimension refers to some selected different business cases that are used to test and demonstrate the proposed tools and provide support to specific RECs in the different phases of their creation. Lastly, the EC observatory was created by ENEA to provide necessary support to the market and stakeholders on different aspects, such as data management, economics, legal issues, communication, and regional governance. Full article

The transition to energy-efficient buildings is a priority of the European EPBD (Energy Performance Building Directive) and requires deep retrofits to reduce consumption and emissions. However, their financial viability remains underexplored. This research assesses the financial feasibility of deep retrofit interventions through innovative business models, focusing on the Managed Energy Services Agreement (MESA), which is considered the most effective for residential buildings. Additionally, we integrate off-site production from the Energiesprong model, which optimizes costs and time through long-term contracts and industrialized retrofit technologies. The analysis targets two investment profiles—owner/tenant and developer/entrepreneur—in Italian urban contexts with different market dynamics. A static analysis evaluates retrofits based on existing costs and technologies, while a dynamic analysis considers future profitability improvements because of cost reductions enabled by off-site production. The results indicate that, under current conditions, residential retrofitting is not financially sustainable without public subsidies. However, cost reductions driven by off-site technologies improve profitability, making large-scale retrofits feasible. Moreover, real estate market characteristics affect financial sustainability: in smaller cities, deeper cost reductions are necessary for retrofit interventions to become viable. Full article

Household food waste accounts for a significant share of total food waste. In 2022, around 1.05 billion tons of food waste were generated—60% of which came from households. In the EU, households generate 54% of the total food waste. In Italy, according to a former diary study, avoidable household food waste accounts for 529.9 g per capita per week. Building on this data, this study assesses the monetary value of food waste at the household level in 6 provinces across the country, considering the prices of food items recorded by the Italian Observatory of market prices. Moreover, the environmental impacts of household food waste (greenhouse gas emissions, water consumed, and land used) were investigated based on existing data from well-grounded scientific literature. The results show that the monetary value of food waste ranges from EUR 357.43 to EUR 404.62 per household per year, corresponding to 5–7% of the average household expenditure for food. The environmental impacts per household per year account for 149 kgCO₂eq, which contributes to climate change. In addition, household food waste is responsible for 303,498 L of water consumed and 1426 m² of land used. The results of this study can be integrated into National Energy and Climate Plans (NECPs), to integrate food waste reduction into energy savings and greenhouse gas mitigation strategies. Full article

The increasing integration of renewable energy sources (RESs) into the Italian electricity market has heightened inter-zonal congestion challenges as power flows vary across importing and exporting zones. Utilizing a Multinomial Logistic Regression model as an empirical approach, this study investigates the key factors driving inter-zonal congestion between zonal pairs from 2021 to 2023, focusing on how local and neighboring zones’ RES generation (wind, solar, and hydropower) and demand dynamics impact congestion probabilities. The findings reveal that increased local RES generation generally reduces the likelihood of congestion for importing regions but increases it for exporting zones. Specifically, higher wind and solar production in importing zones like CNOR and CSUD alleviates congestion by reducing the need for imports, while in exporting zones, such as NORD and CALA, increased RES generation can exacerbate congestion due to higher export volumes. Hydropower production shows similar trends, with local production mitigating congestion in importing zones but increasing it in exporting zones. In addition to the effects of local generation and demand within each zonal pair, the generation and demand from neighboring zones also have a notable and statistically significant impact. Although their marginal effects tend to be smaller, the contributions from neighboring zones are essential for comprehending the overall congestion dynamics. These insights underscore the need for strategic RES placement to enhance market efficiency and minimize congestion risks across the Italian zonal electricity market. Full article

Resource consumption in the construction industry is expected to increase globally in the coming years. Additionally, construction and demolition waste (CDW) remains a significant priority within numerous global policies due to its vast volume and the inefficiencies in its management. This situation results in substantial environmental repercussions, primarily due to the low rates of material recovery in the manufacturing processes for new building materials. In response, the concept of the circular economy (CE) emerges as a promising solution across various sectors. CE promotes more resource- and energy-efficient practices, reducing waste generation and mitigating the environmental impacts associated with product life cycles while also unlocking potential economic opportunities. The primary aim of this study is to identify and assess the design practices influencing the adoption of CE principles within the Italian architectural, engineering, and construction (AEC) sector. The study’s main contribution lies in a survey of 77 Italian designers to explore the core strategies driving the development of comprehensive circular approaches. This investigation seeks to understand the constraints and opportunities for CE implementation. The findings will assist in decision-making, inform policy, promote literacy around the CE topic, enable new quality standards, and serve as a baseline reference for businesses regarding sustainability investment indexes and markets. Full article

Long-term transmission expansion planning has to face the energy transition in a restructured electricity market environment. Increased transmission capacity within and between Member States is likely to play an essential role in maintaining the secure and economic operation of the whole European power system and ensuring the integration of growing renewable generation. This paper proposes a novel iterative methodology aimed at assessing an optimal level of interconnection between relevant bidding zones, simultaneously investigating different potential alternatives. Starting from a reference grid, a multi-criteria analysis is adopted to select the additional transmission capacities to be tested in each iteration via network and market simulations in order to confirm that transmission expansion benefits outweigh the estimated realization costs. The proposed approach is applied to the Italian case in two contrasting energy scenarios for the mid-term 2030 and very-long-term 2040 horizons: different development strategies are derived, and the least regret criterion is applied to define the most cost-effective as the target development strategy for the Transmission System Operator (TSO). Furthermore, sensitivity analyses on relevant input data variation are performed to test the robustness of the results obtained. Full article

Improper configuration of bidding zones can lead to market efficiency losses, hinder the integration of renewable energy sources (RESs), and reduce grid security. To evaluate the impact of different bidding zone configurations on market performance, we developed a multi-dimensional evaluation framework containing a series of indicators covering aspects of market efficiency, grid security, and sustainability. These indicators facilitate the comparisons among different market dispatch mechanisms. To validate the proposed framework, the reconfiguration of the Italian bidding zones has been applied to a simplified Italian grid model to compare the market performance under different bidding zone configurations. The simulation results indicate that the implemented reconfiguration has led to enhanced market efficiency and security in the Italian power system. However, the reconfiguration shows a comparatively lower reduction in greenhouse gas (GHG) emissions, suggesting a weaker sustainable performance. Full article

Integrating a grid-connected battery into a renewable energy community amplifies the collective self-consumption of photovoltaic energy and facilitates energy arbitrage in the electricity markets. However, how much can energy independence really increase? Is it a cost-effective investment? The answer to these questions represents a novelty in the literature due to the innovative nature of the asset under consideration and the market and regulatory framework in which it is evaluated. Employing a net present value assessment, our analysis incorporated aging effects and conducts sensitivity analyses across various parameters: the number of community customers, electricity market prices, battery cost and size, and the decision to engage in energy arbitrage. Each scenario underwent a 20-year hourly simulation using an aging-aware rolling-horizon 24 h-looking-ahead scheduling, optimized with mixed-integer linear programming. Simulations conducted on the Italian market indicate that dedicating a battery solely to collective self-consumption is the most efficient solution for promoting a community’s energy independence, but it lacks economic appeal. However, integrating energy arbitrage, despite slight compromises in self-sufficiency and battery longevity, halves the payback period and enhances the attractiveness of larger battery investments. The net present value is contingent upon the battery size, customer number, and market prices. Nevertheless, if the battery cost does not exceed 200 EUR/kWh, the investment becomes cost-effective across all scenarios. Full article

The carbon–financial nexus helps firms evaluate susceptibility to carbon risk more effectively. This is the first research article to model the short- and long-run co-integrating association between European financial markets, the CBOE oil price volatility index (OVZ) and the European carbon emission trading system (EU-ETS) by using the daily returns from 1 October 2013 to 1 October 2023. We utilize co-integration test followed by the ARDL framework with an error correction mechanism (ECM). Moreover, we utilize the DCC-GARCH-t copula framework to estimate the hedge ratio and to select an optimal portfolio weight for carbon risk hedging. Overall, the findings suggested that EU-ETS (OVZ) has a consistent positive (negative) short-term influence on all the equity returns of Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Netherlands, Spain and the stock indices of the whole Eurozone. However, in the long term, EU-ETS has a positive (negative) effect on the stock returns of France and the Eurozone (Belgium and Spain). Belgian and Spanish companies could implement long-term carbon reduction policies. Belgian and Spanish firms should focus on the utilization of green energy resources and the internalization of carbon emission-free mechanical processes as this may offer a safeguard against the additional pressure arising from escalating carbon prices. Finally, an optimal portfolio weight selection strategy based upon the DCC-GARCH-t copula approach aims for higher hedging effectiveness (HE) than the hedge ratio strategy when adopting short-term positions in Italian and Danish equity markets to reduce the risk of long-term EU-ETS volatility. Full article

The mass introduction of renewable energy sources (RESs) presents numerous challenges for transmission system operators (TSOs). The Italian TSO, Terna S.p.A., aims to assess the impact of inverter-based generation on system inertia, primary regulating energy and short-circuit power for the year 2030, characterized by a large penetration of these sources. The initial working point of the Italian transmission network has to be defined through load flow (LF) calculations before starting dynamical analyses and simulations of the power system. Terna 2030 development plan projections enable the estimation of active power generation and load for each hour of that year in each Italian market zone, as well as cross-zonal active power flows; this dataset differs from conventional LF assignments. Therefore, in order to set up a LF analysis for the characterization of the working point of the Italian transmission network, LF assignments have to be derived from the input dataset provided by Terna. For this purpose, this paper presents two methods for determining canonical LF assignments for each network bus, aligning with the available data. The methodologies are applied to a simplified model of the Italian network, but they are also valid for other transmission networks with similar topology and meet the future needs of TSOs. The methods are tested at selected hours, revealing that both approaches yield satisfactory results in terms of compliance with the hourly data provided. Full article

Efficient management of renewable energy resources is imperative for promoting environmental sustainability and optimizing the utilization of clean energy sources. This paper presents a pioneering European-scale study on energy management within renewable energy communities (RECs). With a primary focus on enhancing the social welfare of the community, we introduce a reinforcement learning (RL) controller designed to strategically manage Battery Energy Storage Systems (BESSs) and orchestrate energy flows. This research transcends geographical boundaries by conducting an extended analysis of various energy communities and diverse energy markets across Europe, encompassing different regions of Italy. Our methodology involves the implementation of an RL controller, leveraging optimal control theory for training and utilizing only real-time data available at the current time step during the test phase. Through simulations conducted in diverse contexts, we demonstrate the superior performance of our RL agent compared to a state-of-the-art rule-based controller. The agent exhibits remarkable adaptability to various scenarios, consistently surpassing existing rule-based controllers. Notably, we illustrate that our approach aligns with the intricate patterns observed in both Italian and European energy markets, achieving performance levels comparable to an optimal controller assuming perfect theoretical knowledge of future data. Full article

In recent years, numerous studies have explored how energy and environmental performance impact property values. Superior energy efficiency is the basis for value disparities in real estate markets. However, measurements of these variations vary significantly. This research aims to investigate the relationship between market size and vitality and market value differences. This has significant implications for the nature of the energy transition, potentially determining fairness or inequality. The study considers the real estate market in six Italian cities: three metropolitan (Milan, Turin, and Florence) and three medium-sized cities (Padua, Mestre, and Bergamo). The sample includes 2935 properties. In metropolitan cities, hedonic pricing models confirm the relevance of energy performance in market value formation, highlighting a potential depreciation in property values by up to 30% between properties belonging to the highest energy class (A) compared to the lowest (G), and 14% between class D and G. Such premium gaps are halved in medium-sized cities. Conclusions foresee a scenario of socially and economically unjust transition that must be considered in policies aimed at improving the energy efficiency of existing buildings, with a specific concern for the nature and characteristics of the real estate markets involved. Full article