Advanced Economic Control of Electricity-based Space Heating Systems in Domestic Coalitions with Shared Intermittent Energy Resources

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Title: Advanced Economic Control of Electricity-based Space Heating Systems in Domestic Coalitions with Shared Intermittent Energy Resources
Author(s): Jennings, N
PANAGOPOULOS,, AA
MALEKI,, S
Rogers, A
VENANZI,, M
Item Type: Journal Article
Abstract: Over the past few years, domestic heating automation systems (DHASs) that optimize the domestic space heating con- trol process with minimum user-input, utilizing appropriate occupancy prediction technology, have emerged as commercial products (e.g, the smart thermostats from Nest and Honeywell). At the same time, many houses are being equipped with, potentially grid-connected, intermittent energy resources (IERs), such as rooftop photovoltaic systems and /or small wind turbine generators. Now, in many regions of the world, such houses can sell energy to the grid but at a lower price than the price of buying it. In this context, and given the anticipated increase in electrification of heating, the next generation DHASs need to incorporate advanced economic control (AEC). Such AEC can exploit the energy buffer that heat in gloads provide,in order to shift the consumption of electricity-based heating systems to follow the intermittent energy generation of the house. By so doing, the energy imported from the grid can be minimized and considerable monetary gains for the household can be achieved, without affecting the occupants’ schedule. These benefits can be amplified still further in domestic coalitions, where a number of houses come together and share their IER generation to minimize their cumulative grid energy import. Given the above, in this work we extend a state-of-the-art DHAS, to propose AdaHeat+, a practical DHAS, that, for the first time, incorporates AEC. Our work is applicable to both individual houses and domestic coalitions and comes complete with an allocation mechanism to share the coalition gains. Importantly, we propose an effective heuristic heating schedule planning approach for collective AEC which: (i) has a complexity that scales in a linear and parallelizable manner with the coalition size,and (ii) enables AdaHeat+ to handle the distinct preferences, in balancing heating cost and thermal discomfort, of the households. Our approach relies on stochastic IER power output predictions. In this context, we propose a simple and effective formulation for the site-specific calibration of such predictions based on adaptive Gaussian process modeling. Finally, we demonstrate the effectiveness of AdaHeat+ through real data evaluation, to show that collective AEC can improve heating cost-efficiency by up to 60%, compared to independent AEC (and even more when compared to no-AEC).
Date of Acceptance: 10-Nov-2016
URI: http://hdl.handle.net/10044/1/42508
ISSN: 2157-6912
Publisher: Association for Computing Machinery (ACM)
Journal / Book Title: ACM Transactions on Intelligent Systems and Technology
Copyright Statement: This paper is embargoed until publication.
Publication Status: Accepted
Embargo Date: publication subject to indefinite embargo
Appears in Collections:Faculty of Engineering
Faculty of Natural Sciences



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