Intelligent energy system refers to the use of intelligent control strategies with the energy system, which can help minimise energy waste and loss, optimise load control, increase and improve energy efficiency and/or maximise the benefits of renewable energy. Renewable energy and intelligent controls are interlinked and correlated with each other. Without intelligent controls, the full benefits of renewable energy technologies may not be achievable, specifically the Ground Source Heat Pump (GSHP) technologies. This was observed, especially by the University of Central Lancashire (UCLan) that had incorporated a GSHP to one of its building. The GSHP is under performing due to the inefficient controls implemented with the GSHP. This paper proposes an intelligent multiagent building management system (MAS BMS) that aims to tackle this issue. Intelligence is provided by an ARTMAP, a type of artificial neural network that provides incremental learning inspired by how human process memory. Simulation results show the proposed intelligent MAS BMS is able to maximise the use of the GSHP effectively by profiling, predicting and coordinating its usage with other energy resources. The proposed method has performed better than the existing control strategies for the GSHP.
This paper considers proportional-integral-plus (PIP) control of non-linear systems defined by state-dependent parameter models, with particular emphasis on three practical demonstrators: a microclimate test chamber, a 1/5th-scale laboratory representation of an intelligent excavator, and a full-scale (commercial) vibrolance system used for ground improvement on a construction site. In each case, the system is represented using a quasi-linear state-dependent parameter (SDP) model structure, in which the parameters are functionally dependent on other variables in the system. The approach yields novel SDP-PIP control algorithms with improved performance and robustness in comparison with conventional linear PIP control. In particular, the new approach better handles the large disturbances and other non-linearities typical in the application areas considered. modelled using a quasi-linear structure in which the parameters vary as functions of the state variables, LA1 4YR, UK. email: c.taylor@lancaster.ac.uk JSCE366
This review, summarises the pertinent literature on drag reduction (DR) in laminar and turbulent flow in coiled tubes. Due to their compact design, ease of manufacture and superior fluid mixing properties, helically coiled tubes are widely used in numerous industries. However, flow through coiled tubes yields enhanced frictional pressure drops and thus, drag reduction is desirable as it can: decrease the system energy consumption, increase the flow rate and reduce the pipe and pump size. The main findings and correlations for the friction factor are summarised for drag reduction with the: injection of air bubbles and addition of surfactant and polymer additives. The purpose of this study is to provide researchers in academia and industry with a concise and practical summary of the relevant correlations and supporting theory for the calculation of the frictional pressure drop with drag reducing additives in coiled tubes. A significant scope for future research has also been identified in the fields of: air bubble and polymer drag reduction techniques.
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