Abstract
Ensuring reliable and high-quality electricity service is critical for consumers and Distribution System Operators (DSO). The DSO's Plan for Development and Investment in the Distribution Network (PDIDN) plays a pivotal role in enhancing network reliability and resilience while balancing technical and financial aspects. This study proposes a novel probabilistic approach for quality-of-service (QoS) estimation in distribution systems, addressing the limitations of traditional deterministic methods. Leveraging Bayesian regression, specifically the Spike and Slab technique, the model incorporates prior knowledge to improve the prediction of key QoS indicators such as SAIDI, SAIFI, and TIEPI. Using historical network data, the model demonstrates superior predictive accuracy and robustness, offering realistic confidence intervals for strategic planning. This method enables informed investments, enhances regulatory compliance, and supports renewable integration. The findings underline the potential of probabilistic modeling in advancing QoS forecasting, encouraging its application in other areas of electric network management.

Abstract
This article explores the optimization of Battery Energy Storage Systems (BESS) in energy markets, emphasizing their role in decarbonization by storing excess renewable energy and mitigating grid constraints. BESS enables energy transition by facilitating energy arbitrage, frequency regulation, and grid stabilization, essential for integrating variable renewable sources. Focusing on the UK energy market, the study highlights the favorable policies and investments driving BESS deployment. It examines revenue streams, including Day-Ahead and Intraday markets, ancillary services, and balancing mechanisms, particularly dynamic services like frequency regulation. Challenges such as gas market volatility and regulatory hurdles are also discussed. The proposed market optimization model simulates BESS operations, revealing consistent revenue potential influenced by market conditions and regulatory frameworks. The study underscores BESSs critical role in stabilizing grids, supporting renewables, and enhancing energy security while calling for further research on equipment degradation and broader impacts on energy systems and pricing.

Abstract
Motivated by initiatives such as the UN Sustainable Development Goals (SDG), particularly SDG 1-Poverty Eradication and SDG 7-Clean and Accessible Energy, the search for solutions aiming to mitigate poverty has been recurrent in several studies. This paper main objective is to evaluate the dynamics of global research on the use of photovoltaic projects for poverty alleviation (PVPA) from 2003 to 2022. We use a bibliometric analysis to identify publication patterns and consequently list research trends and gaps of the area. A total of 336 publications from Scopus database are identified and complemented by a state-of-the-art study, where the articles are investigated and classified according to: Business model and financing and evaluation of PVPA results. The results show that PA is often associated with PV power and its application in rural areas. “Biomass” and “application in developing countries” have become a trend. Urban areas application, aiming to reduce poverty, and the need for a synergetic integration of energy and urban planning, to mitigate the risks associated with energy flow and efficiency, are the most relevant gaps identified. Most of the publications focus on macropolicies effects involving PV technology; papers on projects construction and ex-post are not identified.

Abstract
This article presents a methodology to estimate the evolution of QoS indices, based on investments and maintenance costs carried out in the DN. The indices were estimated at various disaggregated levels, including the global index, 3 different QoS zones (urban, semi-urban and rural) and 278 municipalities, thereby facilitating the mitigation of QoS asymmetries by allocating investments and maintenance actions to specific regions. To achieve this objective, an optimization problem was formulated to allocate investments and maintenance costs to municipalities with higher improvement benefit-cost ratios, potentially exhibiting lower levels of QoS. This methodology was adopted by the Portuguese DSO to establish the future investments plan from 2023 to 2027. The results demonstrate estimations of good performance, considering the stochastic nature of the phenomena affecting QoS (e.g. atmospheric conditions), which are included in this study, thus developing confidence levels for the global indices.

Abstract
This article proposes a methodology for high loss detection in LV network, based on a very small set of commonly available data/metadata from networks connected to an MV/LV substation. The approach is based on a combination of predictors from several distinct categories, including network data, metadata, and measured smart meter data. Several independent groups of unranked real networks were simulated, and it was possible to find the top ten networks with the highest level of losses with a very satisfactory success rate (76% to 98%), depending on selected groupings folds. Due to the impracticability of analyzing all LV networks, the identification of the highest loss ones is essential for the definition of loss reduction planning since, with this list filtering, it is possible to determine with a good degree of certainty which networks require maintenance or upgrade.