Abstract

Abstract
With the increased penetration of renewables, energy storage has become a critical issue in microgrid and small household applications. Accordingly, this paper undertakes a feasability study the varying limitations from conventional batteries in residential buildings, such as capacity-loss over time and aging, as well as the alternative application and challenges of hydrogen-based storage for the domestic sector. The paper considers a test case study where an analysis is performed on the practicality of hydrogen-based storage, in addition to lithium-ion battery storage. Various scenarios are considered based on solar installation sizes, self-consumption, battery capacity, autonomy rates and grid extraction. A detailed analysis is carried out on both thermal and electrical demands of a residential household, which also includes the energy performance and applications of heat pumps. While the obtained results from various scenarios are compared and analysed, these anticipate that the potential integration of hydrogen can improve the autonomy rate of residential buildings, The cost of hydrogen storage is expected to reduce significantly, opening opportunities for hydrogen application.

Abstract
This paper proposes a novel real option (RO)-based network investment assessment method to quantify the flexibility value of battery energy storage systems (BESS) in distribution network planning (DNP). It applied geometric Brownian motion (GBM) to simulate the long-term load growth uncertainty. Compared with commonly used stochastic models (e.g. normal probability model) that assume a constant variance, it reflects the fact that from the point of prediction, uncertainty would increase as time elapses. Hence, it avoids the bias of traditional net present value (NPV) frameworks towards lumpy investments that cannot provide strategic flexibility relative to more flexible alternatives. It is for the first time to adopt the option pricing method to evaluate the flexibility value of distribution network planning strategies. To optimize the planning scheme, this paper compares the static NPVs and flexibility values of different investment strategies. A 33-bus system is used to verify the effectiveness of the formulated model. Results indicate that flexibility values of BESS are of utmost importance to DNP under demand growth uncertainties. It provides an analytical tool to quantify the flexibility of planning measures and evaluate the well-timed investment of BESS, thus supporting network operators to facilitate flexibility services and hedge risks from the negative impact of long-term uncertainty.

Abstract
The present work aims to compare several load disaggregation methods. While the supervised alternative was found to be the most competent, the semi-supervised is proved to be close in terms of potential, while the unsupervised alternative seems insufficient. By the same token, the tests with long-lasting data prove beneficial to confirm the long-term performance since no significant loss of performance is noticed with the scalar of the time-horizon. Finally, the patchwork of new parametrization and methodology fine-tuning also proves interesting for improving global performance in several methods.

Abstract
In Europe, clean distributed generation, DG, is perceived as a crucial instrument to build the path towards carbon emission neutrality. DG already reached a large share in the generation mix of several countries and the reduction of technical losses is one of its most mentioned advantages. In this scope, this paper discusses the weaknesses of this postulation using real networks. The adopted methodology involves the power flow simulation of a collection of real networks, using 15 min real measurements of loads and generations for a whole year. The clustering of similar cases allows identifying the situations that cause higher losses. A complementary objective of this research was to define an approach to mitigate this problem in terms of identifying the branches that, if reinforced, most contribute to losses reduction. The results obtained confirm the rationality of the proposed methodology.

Abstract
The financial planning of distribution systems usually includes the prediction of annual mandatory investments, concerning the resources that the DSO is compelled to allocate as a result of new network connections, required by new consumers or new energy producers. This paper presents a methodology to estimate the mandatory investments that the DSO should do in the distribution network. These estimations are based on historical data, load growth expectations and various socioeconomic indices. However, the available database contains very few annual investment examples (one aggregated value per year since 2002) compared to the large number of variables (potential inputs), which is a factor of regression overfitting. Thus, the applicable regression techniques are restrained to simple but efficient models. This paper describes a new methodology to identify the most suitable estimation models. The implemented application automatically builds, selects, and tests estimation models resulting from combinations of input variables. The final forecast is provided by a committee of models. Results obtained so far confirm the feasibility of the adopted methodology.