Abstract
The Energy-efficiency of demand management technologies and customer’s experience have emerged as important issues as consumers began to heavily adopt these technologies. In this context, where the electrical load imposed on the smart grid by residential users needs to be optimized, it can be better managed when customer’s comfort parameters are used, such as thermal comfort and preferred appliance usage time interval. In this paper a multi-layer architecture is proposed that uses a multi-objective optimization model at the energy consumption level to take consumer comfort and experience into consideration. The paper shows how our proposed Clustered Sequential Management (CSM) approach could improve consumer comfort via appliance use scheduling. To quantify thermal comfort, we use thermodynamic solutions for a Heating Ventilation and Air Conditioner (HVAC) system and then apply our scheduling model to find the best time slot for such thermal loads, linking consumer experience to power consumption. In addition to thermal loads, we also include non-thermal loads in the cost minimization and the enhanced consumer experience. In this hierarchal algorithm, we classified appliances by their load profile including degrees of freedom for consumer appliance prioritization. Finally, we scheduled consumption within a Time of Use (ToU) pricing model. In this model, we used Mixed Integer Linear Programming (MILP) and Linear Programming (LP) optimization for different categories with different constraints for various loads. We eliminate the customer’s inconvenience on thermal load considering ASHRAE standard, increase the satisfaction on EV optimal chagrining constrained by minimum cost and achieve the preferred usage time for the non-interruptible deferrable loads. The results show that our model is typically able to achieve cost minimization almost equal to 13% and Peak-to-Average Ratios (PAR) reduction with almost 45%.
Highlights
Residential demand management, despite the vast research efforts on the recent years and the wide literature, persists as an open issue
We eliminate the customer’s inconvenience on thermal load considering ASHRAE standard, increase the satisfaction on EV optimal chagrining constrained by minimum cost and achieve the preferred usage time for the non-interruptible deferrable loads
The results show that our model is typically able to achieve cost minimization almost equal to 13% and Peak-to-Average Ratios (PAR) reduction with almost 45%
Summary
Residential demand management, despite the vast research efforts on the recent years and the wide literature, persists as an open issue. Customer comfort has been less considered where it could be associated with appliance usage performance, delays in responding to utility demand response requests, room temperature and so forth. To address this gap, we present a demand management approach that considers customer comfort in our multi-objective optimization model. Most of the research on Demand Side Management (DSM), or in other words residential level load control, aims to reduce either the customer’s cost or the grid operators’ PAR [6]. In another article [8], the authors focus on scalability and acceptability where they categorized appliances, ordered their consumptions and defined boundaries for appliance usage time slots to bound the consumption and to make the consumption diagram smooth. In [9], the authors have clustered loads based on their priorities within a Neighborhood-Area
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