Towards the Handling Demand Response Optimization Model for Home Appliances

Veras, Jaclason Machado; Silva, Igor Rafael S.; Pinheiro, Plácido Rogério; Rabêlo, Ricardo A. L.

doi:10.3390/su10030616

Cited by 18 publications

(21 citation statements)

References 27 publications

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“…By the same token, Jaclason M. Veras, Igor Rafael S. Silva, Plácido R. Pinheiro and Ricardo A. L. Rabêlo, examine the question of consumers' energy consumption profiles in view of minimizing the electricity costs for the final consumers [16]. In their paper titled 'Towards the Handling Demand Response Optimization Model for Home Appliances", the authors suggest that decrease in the electricity cost is possible.…”

Section: How To Maintain and Promote Environmental Sustainability In mentioning

confidence: 99%

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

2018

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Abstract:Research on smart cities matures and new interdisciplinary approaches to the study of smart cities are proposed. At the same time, problems pertinent to communities inhabiting rural areas tend to be addressed, as if by the way, i.e., as a part of discussions in neighboring fields of research, be it environmental studies, sociology, or agriculture. Arguably, the concept of 'the village' has been largely absent in the academic debate, even if rural areas and countryside communities have been a subject of concern for robust policy frameworks, such as the European Union's Cohesion Policy and Common Agricultural Policy. As a result, when advances in sophisticated information and communication technology (ICT) led to the emergence of a rich body of research on smart cities, the application and usability of ICT in the context of a village remained underdiscussed in the literature. Through this Special Issue, and the Editors' earlier research on this topic, the Editors hope that the idea of the 'smart village' will be introduced into the debate. Against this backdrop, the objective of this opening review is three-fold: (i) to outline the conceptual boundaries of the term smart village, (ii) to highlight the thrust of the challenge inherent in smart villages research, and (iii) to shed light on the smart village research agenda as it unfolds. The relevance and validity of these claims are supported by references to research submitted to the Special Issue titled "Sustainable Smart Cities and Smart Villages Research".

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Section: How To Maintain and Promote Environmental Sustainability In mentioning

confidence: 99%

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

2018

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“…Pricing mechanism is a solution for on-peak load management; however, the scheduling mechanism is required to shift load in a suitable manner. To achieve this, works in [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39] present different load controlling techniques and strategies. For instance, the work in [20] proposes a Distributed Energy Storage Planning (DESP) for PAR minimization.…”

Section: Related Workmentioning

confidence: 99%

“…A nonlinear programming model is proposed by [25]. In this work, the real-time DR model is presented to minimize the electricity cost associated with consumption through appliance scheduling while ignoring consumer comfort.…”

Section: Related Workmentioning

confidence: 99%

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Enhanced Time-of-Use Electricity Price Rate Using Game Theory

et al. 2019

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The emergence of the Demand Response (DR) program optimizes the energy consumption pattern of customers and improves the efficacy of energy supply. The pricing infra-structure of the DR program is dynamic (time-based). It has rather complex features including marginal costs, demand and seasonal parameters. There is variation in DR price rate. Sometime prices go high (peak load) if the demand of electricity is more than the generation capacity. The main objective of DR is to encourage the consumer to shift the peak load and gets incentives in terms of cost reduction. However, prices remain the same for all the users even if they shift the peak load or not. In this work, Game Theory (GT)-based Time-of-Use (ToU) pricing model is presented to define the rates for on-peak and shoulder-peak hours. The price is defined for each user according to the utilize load. At first, the proposed model is examined using the ToU pricing scheme. Afterward, it is evaluated using existing day-ahead real-time pricing scheme. Moreover, shifting load from on-peak hours to off-peak hours may cause rebound peak in off-peak hours. To avert this issue, we analysis the impact of Salp Swam Algorithm (SSA) and Rainfall Algorithm (RFA) on user electricity bill and PAR after scheduling. The experimental results show the effectiveness of the proposed GT-based ToU pricing scheme. Furthermore, the RFA outperformed SSA.

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“…The authors in [ 29 ] proposed a DR optimization model that takes into account a set of energy-related constraints to determine the optimal operation schedule for home appliances. The objective is to minimize the cost associated with energy consumption, taking into account the satisfaction and comfort of final consumers and the various constraints associated with the consumption of electric energy.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Objective Demand Response Optimization Model for Scheduling Loads in a Home Energy Management System

Veras

Silva

Pinheiro

et al. 2018

Sensors

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Demand Response (DR) aims to motivate end consumers to change their energy consumption patterns in response to changes in electricity prices or when the reliability of the electrical power system (EPS) is compromised. Most of the proposals found in the literature only aim at reducing the cost for end consumers. However, this article proposes a home energy management system (HEMS) that aims to schedule the use of each home appliance based on the price of electricity in real-time (RTP) and on the consumer satisfaction/comfort level in order to guarantee the stability and the safety of the EPS. Thus, this paper presents a multi-objective DR optimization model which was formulated as a multi-objective nonlinear programming problem subjected to a set of constraints and was solved using the Non-Dominated Sorted Genetic Algorithm (NSGA-II), in order to determine the scheduling of home appliances for the time horizon. The multi-objective DR optimization model not only to minimize the cost of electricity consumption but also to reduce the level of inconvenience for residential consumers. Moreover, a priori, it is expected to obtain a more uniform demand with fewer peaks in the system and, potentially, achieving a more reliable and safer EPS operation. Thus, the energy management controller (EMC) within the HEMS determines an optimized schedule for each home appliance through the multi-objective DR model presented in this article, and ensures a more economic scenario for end consumers. In this paper, a performance evaluation of HEMS in 15 Brazilian families between 1 January and 31 December 2016 is presented with different electric energy consumption patterns in the cities of Belém—PA, Teresina—PI, Cuiabá—MT, Florianópolis—SC and São Paulo—SP, with three families per city, located in the regions north, northeast, central west, south and the southeast of Brazil, respectively. In addition, a total of 425 home appliances were used in the simulations. The results show that the HEMS achieved reductions in the cost of electricity for all the Scenarios used while minimally affecting the satisfaction/comfort of the end consumers as well as taking into account all the restrictions. The largest reduction in the total cost of electricity occurred for the couple without children, resident in the city of Teresina—PI; with a drop from US$ 99.31 to US$ 90.72 totaling 8.65% savings in the electricity bill. Therefore, the results confirm that the proposed HEMS effectively improves the operating efficiency of home appliances and reduces electricity costs for end consumers.

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Towards the Handling Demand Response Optimization Model for Home Appliances

Cited by 18 publications

References 27 publications

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

Enhanced Time-of-Use Electricity Price Rate Using Game Theory

A Multi-Objective Demand Response Optimization Model for Scheduling Loads in a Home Energy Management System

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