Abstract
Electricity generation from wind energy is one of the main drivers of decarbonization in energy systems. However, installing wind farm facilities may have beneficial and harmful impacts on the habitat of living beings. This study reviews the literature based on economic analysis to identify the main externalities related to the installation of wind farms and the economic methodologies used to assess these externalities, filling an existent literature gap. A systematic literature review followed the Preferred Reporting Items on Systematic Reviews and Meta-analysis standards. A total of 33 studies were identified, most of them carried out in Europe. The studies cover 24 years, between 1998 and 2022. The externalities associated with wind electricity generation are classified into three categories: the impact on well-being, the impact of wind turbines, and the impacts of avoided externalities. Most studies (24 out of 33) determine economic values by stated preference methods through choice experiments, discrete choice experiments, and contingent valuation. Revealed preference methods were identified in 5 studies using hedonic pricing and travel cost techniques. The challenges and limitations of this analysis in terms of externalities identification and their assessment are also discussed, concluding that additional updated review studies are needed since the latest ones were published in 2016 and 2017. Moreover, it gives insights to policymakers and academics on a more complete approach they can use to evaluate the impacts of decarbonization, which, apart from the technological view, also considers and estimates the socio-economic and environmental perspectives.

Abstract

Abstract
Hydrogen is currently getting more and more attention in the European climate strategy as a promising enabling technology to decarbonize industry, transport sector and to provide a long-term, high-capacity energy storage solution. However, to truly contribute to the reduction of CO2 emissions, hydrogen must be produced respecting a principle of additionality, to ensure that it is produced using renewable energy sources and that its production does not decrease the green energy supplied to other loads. This study tracks the share of renewables generation in the energy mix used to produce hydrogen by applying a power flow tracing technique integrated with an optimal power flow analysis. This method allows the minimization of the system operation costs, while maximizing the green hydrogen production and considering the additionality principle. The system cost function is also modified to include the sizing and allocation of conventional batteries in the grid, and assess their ability to further increase the share of green energy in hydrogen production.

Abstract
Energy allocation rules are one of the core aspects of collective self-consumption (CSC) regulations. It allows final consumers to share their surplus generation with other CSC members, while keeping their full rights as consumers, i.e., maintaining a supply contract with the retailers of their choice. Some European Union member states regulations use allocation coefficients so that local allocations are integrated with wholesale settlement and directly affect the retailers' billing. Several AC methods have been proposed so far, each one adapted to distribution system operators' settlement procedures with specific rules that can impact the benefits that each CSC member obtain. This paper analyses, assesses and compares two relevant AC methods, namely pre-delivery fixed AC and post-delivery dynamic AC, by developing a settlement formulation for a community with members with flexible assets and different opportunity costs. AC policy recommendations based on findings are provided.

Abstract
The integration of renewable generation requires new sources of flexibility, including the flexibility from distributed resources that can be unlocked via local flexibility markets (LFMs). In these markets, aggregators (AGGs) offer the flexibility from their portfolios to the flexibility requesting parties (FRP), i.e. system operators or other balancing requesting parties. To bid in LFMs and manage market uncertainty, AGGs must compute the flexibility they are willing to offer at each possible flexibility market price, by optimizing their portfolios. This paper proposes a 2-stage methodology to compute the flexibility bidding curve that an energy community can send to a LFM when behaving as an AGG of its members resources. At stage 1, the energy community (EC) manager computes the optimal EC operation without flexibility provision, minimizing the EC energy bill, and serving as the baseline to verify the flexibility provision. Then, at stage 2, for each possible flexibility price, the EC manager computes the optimal flexibility to be offered, minimizing the EC energy bill but including the flexibility provision incomes, to build the flexibility bidding curve.