Cost effective energy consumption in a residential building by implementing demand side management in the presence of different classes of power loads

Hemanth, G. R.; Raja, S. Charles; Nesamalar, J. Jeslin Drusila; Kumar, J. Senthil

doi:10.1080/17512549.2020.1752799

Cited by 12 publications

(9 citation statements)

References 27 publications

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“…Consider a CSL load type 4 whose individual power demand was 287.09 kW. Without implementing RDSM strategy, this lighting load operated at (9,10,11,12,13,14,15,16,17,18,19,20) hours with 12 h being its period of operation. The RDSM-EBGWO controller shifted the load type 4 to (1,2,4,5,7,15,16,17,18,19,20,21).…”

Section: Case 1-implementation Of the Proposed Rdsm-ebgwomentioning

confidence: 99%

“…The shifting of temperature-controlled load types 6 and 7 is detailed in Figure 10. The three-phase AC shifted from (9,10,11,12,13) hours of operation to (14,15,16,17,18) hours that had lesser electricity pricing. Because of this reason, the temperature-controlled load types were categorized under CNSL.…”

Section: Case 3-temperature Controlled Classmentioning

confidence: 99%

“…Some of the load scheduling mechanisms in residential buildings have been reviewed. An intelligent universal load management scheduler (IULMS) can handle different power loads for a real-time residential apartment in India [12]. Exploring the possible demand response and load reduction opportunities under the smart grid for residential electricity load profile [13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort

Tamilarasu¹,

Sathiasamuel²,

Joseph

et al. 2021

Energies

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Soaring energy demand and the establishment of various trends in the energy market have paved the way for developing demand-side management (DSM) from the consumer side. This paper proposes a reinforced DSM (RDSM) approach that uses an enhanced binary gray wolf optimization algorithm (EBGWO) that benefits the consumer premises with load scheduling, and peak demand reduction. To date, DSM research has been carried out for residential, commercial and industrial loads, whereas DSM approaches for educational loads have been less studied. The institution load also consumes much utility energy during peak hours, making institutional consumers pay a high amount of cost for energy consumption during peak hours. The proposed objective is to reduce the total electricity cost and to improve the operating efficiency of the entire load profile at an educational institution. The proposed architecture integrates the solar PV (SPV) generation that supplies the user-comfort loads during peak operating hours. User comfort is determined with a metric termed the user comfort index (UCI). The novelty of the proposed work is highlighted by modeling a separate class of loads for temperature-controlled air conditioners (AC), supplying the user comfort loads from SPV generation and determining user comfort with percentage UCI. The improved transfer function used in the proposed EBGWO algorithm performs faster in optimizing nonlinear objective problems. The electricity price in the peak hours is high compared to the off-peak hours. The proposed EBGWO algorithm shift and schedules the loads from the peak hours to off-peak hours, and incorporating SPV in satisfying the user comfort loads aids in reducing the power consumption from the utility during peak hours. Thus, the proposed EBGWO algorithm greatly helps the consumer side decrease the peak-to-average ratio (PAR), improve user comfort significantly, reduce the peak demand, and save the institution’s electricity cost by USD 653.046.

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Section: Case 1-implementation Of the Proposed Rdsm-ebgwomentioning

confidence: 99%

Section: Case 3-temperature Controlled Classmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort

Tamilarasu¹,

Sathiasamuel²,

Joseph

et al. 2021

Energies

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show abstract

“…Aelenei et al [42] have investigated the potential of increasing the load-matching by means of battery energy systems for improving the grid interaction. Demand-side management could bring various benefits such as: reduction in electricity cost, reduction in peak demand, and improvement in load factor [43]. Monitoring data from a real case study investigated by Stasi et al [44] indicated that the energy performance gap concerning energy production on a yearly basis is equal to 9.1%, while on a monthly basis, the performance gap ranges from 3.5% to 27.1%.…”

Section: Introductionmentioning

confidence: 99%

Effect of HVAC’s Management on Indoor Thermo-Hygrometric Comfort and Energy Balance: In Situ Assessments on a Real nZEB

et al. 2021

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This paper proposes the analysis of real monitored data for evaluating the relationship between occupants’ comfort conditions and the energy balance inside an existing, nearly zero-energy building under different operational strategies for the heating, ventilation, and air-conditioning system. During the wintertime, the adaptive comfort approach is applied for choosing the temperature setpoint when an air-to-air heat pump provides both heating and ventilation. The results indicate that in very insulated buildings with high solar gains, the setpoint should be decided taking into consideration both the solar radiation and the outdoor temperature. Indeed, when the room has large glazed surfaces, the solar radiation can also guarantee acceptable indoor conditions when a low setpoint (e.g., 18.7 °C) is considered. The electricity consumption can be reduced from 17% to 43% compared to a conventional setpoint (e.g., 20 °C). For the summertime, the analysis suggests the adoption of a dynamic approach that should be based on the outdoor conditions and differentiated according to room characteristics. Considering the indoor comfort and the maximization of renewable integration, the direct expansion system has better performance than the heat pump; this last system should be integrated with a pre-handling unit to be energy convenient.

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“…Panagopoulos, Alam, Rogers, & Jennings, 2015). 1 That said, most intelligent energy management applications require reliable shortterm (of up to 12 hours ahead) predictions of the demand of the non-controllable loads (i.e., loads that are typically not scheduled in the context of demand side management schemes (Hemanth, Charles Raja, Jeslin Drusila Nesamalar, & Senthil Kumar, 2020;Ramchurn et al, 2012), such as lights and hair dryers.) to perform adequately (e.g., (A.…”

Section: Introductionmentioning

confidence: 99%

A low-complexity non-intrusive approach to predict the energy demand of buildings over short-term horizons

Panagopoulos

Christianos

Katsigiannis

et al. 2020

Advances in Building Energy Research

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Reliable, non-intrusive, short-term (of up to 12 hours ahead) prediction of a building's energy demand is a critical component of intelligent energy management applications. A number of such approaches have been proposed over time, utilizing various statistical and, more recently, machine learning techniques, such as decision trees, neural networks and support vector machines. Importantly, all of these works barely outperform simple seasonal auto-regressive integrated moving average models, while their complexity is significantly higher. In this work, we propose a novel low-complexity non-intrusive approach that improves the predictive accuracy of the state-of-the-art by up to ∼10%. The backbone of our approach is a K-nearest neighbours search method, that exploits the demand pattern of the most similar historical days, and incorporates appropriate time-series pre-processing and easing. In the context of this work, we evaluate our approach against state-of-the-art methods and provide insights on their performance.

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Cost effective energy consumption in a residential building by implementing demand side management in the presence of different classes of power loads

Cited by 12 publications

References 27 publications

Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort

Reinforced Demand Side Management for Educational Institution with Incorporation of User’s Comfort

Effect of HVAC’s Management on Indoor Thermo-Hygrometric Comfort and Energy Balance: In Situ Assessments on a Real nZEB

A low-complexity non-intrusive approach to predict the energy demand of buildings over short-term horizons

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