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• An innovative slim decentralised plug-and-play tank is proposed for DHW production. • Model calibration is performed by experimental data in charge/discharge process. • Retrofit solution cuts required annual energy in half of which 82% is RES quota. • Optimised charging scheme reduces the total annual electrical energy by 5.2 %. • A degree increment in draw-off temperature increases annual CO 2 emission by 103 kg. The present study deals with a multi-objective analysis of an innovative decentralised system to produce and store domestic hot water (DHW), emphasising on the combined effects of the technological aspect, control strategy and user's behaviour. The proposed system, by relying on thermal energy storage, decouples energy production and demand while shaves peaks in the energy demand and, at the same time, provides more autonomy to users through local storages. To identify subtle interactions in components of DHW system, dynamic simulations are carried out by establishing a coupled TRNSYS-MATLAB code, calibrated and validated by experimental measurements. The energy analysis implies that the proposed system cuts the required annual electrical energy in half, of which up to 82% of needed primary energy is supplied from renewable sources, compared to previous electrical-decentralised system. The optimisation of the results through applying control strategies indicates that adopting a three-time charging scheme is advantageous in terms of providing a more stable temperature profile as well as a higher hot water temperature. Compared to an available-by-demand operation, this scheme reduces the required total annual electricity by 5.2 % and enhances total thermal loss from components up to 4.0%. Furthermore, a sensitivity analysis on the results emphasises the striking role of the user behaviour in electrical energy consumption either via draw-off temperature or adjusting the pre-defined temperature for activation of the built-in auxiliary heater. [ABSTRACT FROM AUTHOR]

The capability to dynamically plan, predict, and control indoor conditioning allows to adapt to individual preferences of inhabitants and enables demand side management. While former mainly improves thermal comfort of inhabitants so does latter unlock ecological and financial opportunities mostly for energy utilities. Commonly, dynamic indoor conditioning is based on piece-wise constant indoor temperature constraints. This paper's contribution is the presentation of additional constraints: in particular ones expressed relative to the nominal behavior of a hydronic heating system. This allows to simultaneously harness the relevant process variables in particular during the pre-loading and post-loading phases of a load reduction. The findings are based on data sets acquired on 10 inhabited, residential buildings in Stockholm over a whole year. One of the findings is that building models need to be adaptable if predictive control is applied in practice. This adaptability is assured by a novel concept, i.e. a so called model manager on which the control is relying for the selection of the most accurate model. Centralized optimal control of buildings connected to a district heating network is challenging in practice due to a high computational load. In order to reduce it, the herein presented method elaborates plans only every hour instead of at every control step for optimal control. Since these plans cannot be optimal due to the lack of regular update a hitherto unknown cascaded control logic has been developed that corrects planning errors and other disturbances. Capabilities are demonstrated and compared to conventional controllers in dynamic simulations of a multi-zoned building. The herein presented method is to our knowledge the first to provide all flexibility desired by energy utilities and inhabitants alike through harnessing the consequences of transitions. [ABSTRACT FROM AUTHOR]