Abstract
Distribution networks are more active due to demand response programs which causes flexible behavior of end-users. This paper proposes an iterative algorithm to transact electricity based on interplay between aggregators and the Distribution Company (DisCo) considering the amount which the bottom-layer of a distribution system can provide from the aggregated end-users. The performance of the proposed trading algorithm was tested on a 33-bus test system for a distribution network. Similations for different scenarios were made to analyze the impact of different flexibility constraints on sustainability of the system and expected cost on distribution grid's player.

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Abstract

Abstract
Recent studies highlight the ability of inductive architectures to deliver therapeutic magnetic stimuli to target tissues and to be embedded into small-scale intracorporeal medical devices. However, to date, current micro-scale biomagnetic devices require very high electric current excitations (usually exceeding 1 A) to ensure the delivery of efficient magnetic flux densities. This is a critical problem as advanced implantable devices demand self-powering, stand-alone and long-term operation. This work provides, for the first time, a novel small-scale magnetic stimulation system that requires up to 50-fold lower electric current excitations than required by relevant biomagnetic technology recently proposed. Computational models were developed to analyse the magnetic stimuli distributions and densities delivered to cellular tissues during in vitro experiments, such that the feasibility of this novel stimulator can be firstly evaluated on cell culture tests. The results demonstrate that this new stimulative technology is able to deliver osteogenic stimuli (0.1-7 mT range) by current excitations in the 0.06-4.3 mA range. Moreover, it allows coil designs with heights lower than 1 mm without significant loss of magnetic stimuli capability. Finally, suitable core diameters and stimulator-stimulator distances allow to define heterogeneity or quasi-homogeneity stimuli distributions. These results support the design of high-sophisticated biomagnetic devices for a wide range of therapeutic applications.

Abstract
Demand response services and energy communities are set to be vital in bringing citizens to the core of the energy transition. The success of load flexibility integration in the electricity market, provided by demand response services, will depend on a redesign or adaptation of the current regulatory framework, which so far only reaches large industrial electricity users. However, due to the high contribution of the residential sector to electricity consumption, there is huge potential when considering the aggregated load flexibility of this sector. Nevertheless, challenges remain in load flexibility estimation and attaining data integrity while respecting consumer privacy. This study presents a methodology to estimate such flexibility by integrating a non-intrusive load monitoring approach to load disaggregation algorithms in order to train a machine-learning model. We then apply a categorization of loads and develop flexibility criteria, targeting each load flexibility amplitude with a corresponding time. Two datasets, Residential Energy Disaggregation Dataset (REDD) and Refit, are used to simulate the flexibility for a specific household, applying it to a grid balancing event request. Two algorithms are used for load disaggregation, Combinatorial Optimization, and a Factorial Hidden Markov model, and the U.K. demand response Short Term Operating Reserve (STOR) program is used for market integration. Results show a maximum flexibility power of 200–245 W and 180–500 W for the REDD and Refit datasets, respectively. The accuracy metrics of the flexibility models are presented, and results are discussed considering market barriers.

Abstract
Integration of renewable generation in distribution systems aims to reduce consumption of energy from conventional sources such as coal and oil in order to minimize the negative impacts of the human ecological footprint. Massive incorporation of renewables can produce reverse power flow at distribution substations, which is against the operating philosophy and design of energy systems. To deal with this problem, the installation of a battery energy storage system (BESS) is proposed in this work. Incorporation of BESS at distribution substations can manage the excess of renewable power generation flowing in reverse, adding flexibility to the power system and allowing increased distributed generation capacity to be installed. Optimal sizing of vanadium redox flow batteries (VRFBs) is carried out by using golden section search algorithm considering capital costs as well as operating and maintenance costs over the project lifetime. The effectiveness of the proposed technique is evaluated through the analysis of a case study. A significant reduction of both reverse flow and the power to be supplied by the substation has been observed.