Sub-aggregator Business Models for Demand Response

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Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

Towards practical typology of energy communities : main differentiating elements and examples of promising implementations

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POWER QUALITY FACTORS IN EFFICIENCY BENCHMARKING

Abstrac

Outcome based definition of the anterior thalamic deep brain stimulation target in refractory epilepsy

AbstractBackgroundDeep brain stimulation of the anterior nucleus of the thalamus (ANT) is an emerging therapy for refractory focal epilepsy. However, the most optimal target for stimulation has not been unambiguously described.ObjectiveIn the present study, we investigated the correlation between the stimulation site and outcome in order to define the optimal target for deep brain stimulation in refractory epilepsy.MethodsThe locations of 62 contacts used in 30 treatment attempts in 15 prospectively followed patients during a 5 year period were assessed. Treatment attempts were classified into responding and non-responding trials using seizure reduction and side effect profile as criteria. The locations of active contacts were calculated with respect to mid-commissural point and visible borders of ANT in 3T MRI (ANT-normalized coordinate system) aiming to minimize the confounding effect of individual variation in the location and size of the ANT.ResultsContacts in successful treatment trials were located significantly more anterior and superior both in AC–PC and ANT-normalized coordinate systems. Favourable outcome was observed at 3T MRI based location of ANT but not at location predicted by Schaltenbrandt atlas sagittal data. Contacts used in successful trials were at anterior aspect of the ANT complex evidenced by the ANT-normalized coordinate system.ConclusionThe anti-epileptic effect of anterior thalamic DBS may be dependent on stimulation site especially in the anterior to posterior axis. Extensive anatomical variation confounds severely the targeting of ANT. Therefore, direct visualization of the desired target for stimulation is essential for favourable outcome in refractory epilepsy

Prosumer centric digital energy ecosystem framework

Climate change is putting pressure on governments, policy makers and international organizations to increase energy efficiency and move towards using renewable energy sources. To meet growing need for energy and at the same time comply with ecologic and economic demands, the energy market structure is slowly transitioning from a centralized system to more interactive and decentralized model based on Smart Grid technology in which also end users may play a role as prosumers i.e. as producers and consumers of energy. Different scenarios exist for the level of prosumer participation in the future flexible energy ecosystem. In this paper, we propose a framework for Prosumer centric Digital Energy Ecosystem based on Smart Grid technologies, decentralized energy production using renewable energy sources and complex network of new and incumbent actors, business models and processes.publishedVersionPeer reviewe