Application of Two-Phase Simplex Method (TPSM) for an Efficient Home Energy Management System to Reduce Peak Demand and Consumer Consumption Cost
TL;DR: In this paper, a simple home energy management using Two-Phase Simplex Method (TPSM) is proposed with an objective to reduce peak demand, reduce consumer consumption cost, and conserve consumer comfort level.
Abstract: Superabundant utilization of electricity in the residential sector is one of the major reasons for frequent peak demand. Hence, power sector necessitates an appropriate solution to control and monitor the peak demand. In this regard, implementation of an appropriate home energy management system becomes mandatory at customer premises to have an effective control over peak demand. Thus, in this research a simple home energy management using Two-Phase Simplex Method (TPSM) is proposed with an objective to (i) reduce peak demand, (ii) reduce consumer consumption cost, and (iii) conserve consumer comfort level. Further, the research proposes detailed investigations on the smart energy-home management model monitored by IoT. For simulations, different load scenarios are considered and the results are compared with the existing benchmarks available in the literature. On validations, the proposed TPSM method is found simple, reliable and efficient. More importantly, the multipurpose objectives has certainly given better results in consumer consumption cost that can give better control to peak demand. Furthermore, the usage of lucid simplex method has almost reduced the computational complexity to fasten the response time. In this regard, consumer comfort is served here is considered as a major accomplishment with the proposed work.
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20 Jan 2022TL;DR: A comparative analysis of the performance of a 3-phase induction motor by using Adaptive Neuro Fuzzy Inference System (ANFIS or Neuro-fuzzy) and Proportional-Integral-Derivative (PID) controllers is presented in this article .
Abstract: This paper presents a comparative analysis of the performance of a 3-Phase Induction motor by using Adaptive Neuro Fuzzy Inference System (ANFIS or Neuro-fuzzy) and Proportional-Integral-Derivative (PID) controllers. This study is mainly to show improved speed control of a scalar closed loop Induction motor with an ANFIS controller which also helps to keep the motor speed constant when the load varies. This comparative analysis done on some of the main properties on which the efficiency of an Induction motor depends on. DCT or Direct torque control scheme is one of major advanced methods to control the electromagnetic torque and flux of machines. In these drives the control of torque and speed for high performance applications demands a high robust adaptive controller. This is where ANFIS comes in which is a combination or a hybrid of ANN (Artificial Neural Network) and FLCC (Fuzzy Logic Control) which helps in the execution of direct torque control and overcome the difficulties in high performance machines ad drives. Using the fuzzy toolbox in MATLAB and SIMULINK, the graphical results of both the controllers are determined and why Neuro-fuzzy controller is a better option and can be used in Real-time comfortably is explained. The Neuro-fuzzy controller also shows enhanced performance and dynamics of the induction motor when compared to a normal PID controller.
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23 Feb 2022TL;DR: In this article , the authors suggest that reputation of gestures have continually been a means of bridging the gap between the physical world and the virtual world, and they show that cars can be managed with hand gestures along with hand movements and roles.
Abstract: This paper suggests that reputation of gestures have continually been a means of bridging the gap between the physical world and the virtual world. The Arduino centered car machine unable to manual control of the car. The paintings provided were made using microcontroller as well as Bluetooth. First, this work shows that cars can be managed with hand gestures along with hand movements and roles. Second, the engine offered is also extended to be managed through a mobile utility that is entirely Android-based and has special modes (e.g. touch button mode, reputation mode by voice). In addition, an automatic obstacle detector has been added to improve safeguards to keep out any danger. The proposed structures were designed to confirm the efficiency, accuracy, and affordability of the structure.
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20 Jan 2022TL;DR: In this article , the difference between a traditional engine vehicle and an electric powered vehicle, furthermore discussing about the advantages and disadvantages of electrical vehicles, is discussed, and the solar charging concept has been added to electric vehicles bring about renewable energy sources of charging.
Abstract: As the prices of fuel is sky rocketing and the problems of the normal gasoline engines are causing to the environment, the automobile industry is slowly moving into the electrically powered vehicles instead of the traditional old fuel combustion engines. This report shows the difference between a traditional engine vehicle and an electric powered vehicle, furthermore discussing about the advantages and disadvantages of electrical vehicles. In addition, the solar charging concept has been added to electric vehicles bring about renewable energy sources of charging. This method is not only used to save the environment but also to reduce daily running usage cost by using this electrical vehicle as an alternative.
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23 Feb 2022TL;DR: In this article , the authors proposed using solar energy for the DC Refrigeration in rural areas, which will provide sustainable and affordable solution for areas where there is interrupted electrical supply.
Abstract: Rural and remotes places in India, electricity is either unavailable or there is an irregular supply of electricity due to the lack of technological facilities. This leads to one of the main concerns, which is the storage of food materials, medicine, vaccines and other provisions. This might cause a major loss for the people who survive on a daily income basis, such as petty shop owners, pharmacists, farmers, which in-turn, would cause an economic crisis suffer a loss if there is no refrigeration for their condiments. Similarly, pharmacists find it hard to refrigerate medicines in areas where there is an interrupted or irregular supply of power. There are a few products which have to be maintained at a suitable temperature for further usage and to keep them effective. Food and Medical preservation needs sustainable refrigeration and hence help in maintaining the quality of the products. Therefore, using a renewable form of energy that is solar energy for the DC Refrigeration in rural areas will provide sustainable and affordable solution for areas where there is interrupted electrical supply. Therefore, this paper explains how rural electrification can be implemented by the use of a DC Refrigerator at low cost and less maintenance.
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TL;DR: In this paper , the authors proposed a reliable prosumer model with an inbuilt energy management system (EMS) simulator that considers the mentioned deficiencies for constructing resilient interconnected prosumer microgrids.
Abstract: Worldwide energy shortages and the green energy revolution have triggered an increase in the penetration of standalone microgrids. However, they have limited generation capacity and are wasteful when excess generated energy is curtailed. This presents an opportunity for the coordinated operation of multiple prosumer microgrids that absorb this waste to enhance their resiliency and reliability. This paper proposes a reliable prosumer model with an inbuilt energy management system (EMS) simulator that considers the mentioned deficiencies for constructing resilient interconnected prosumer microgrids. The EMS simulator operates in a real-time dynamic environment to coordinate the prosumer components and performs flexible switching for (1) prioritizing critical load by shedding the non-critical load and (2) meeting load demand locally or from other interconnected prosumers. The EMS simulator maintains energy balance by setting limits for the battery energy storage system (BESS) to preserve energy during low generation and performs real-time monitoring. The novelty of this model lies in its simplicity and flexibility, which allows interconnected prosumer microgrids to operate in cooperation without the need for communication. The proposed model is evaluated in a post-disaster off-grid scenario using a single-phase average value model that considers reasonable computation time. The simulation results of the proposed system indicate the preservation of stored energy while maintaining critical resources beyond three days of poor weather conditions.
1Â citations
References
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22 Mar 2010TL;DR: Simulation results confirm that the proposed distributed algorithm significantly reduces the peak-to-average-ratio (PAR) in load demand and the total cost in the system.
Abstract: In this paper, we consider deployment of energy consumption scheduling (ECS) devices in smart meters for autonomous demand side management within a neighborhood, where several buildings share an energy source. The ECS devices are assumed to be built inside smart meters and to be connected to not only the power grid, but also to a local area network which is essential for handling two-way communications in a smart grid infrastructure. They interact automatically by running a distributed algorithm to find the optimal energy consumption schedule for each subscriber, with an aim at reducing the total energy cost as well as the peak-to-average-ratio (PAR) in load demand in the system. Incentives are also provided for the subscribers to actually use the ECS devices via a novel pricing model, derived from a game-theoretic analysis. Simulation results confirm that our proposed distributed algorithm significantly reduces the PAR and the total cost in the system.
516Â citations
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01 Aug 2010TL;DR: A HEMS that can provide easy-to-access information on home energy consumption in real time, intelligent planning for controlling appliances, and optimization of power consumption at home is proposed.
Abstract: This paper describes a home energy management system (HEMS) based on power line communication. Smart metering and power line communication can provide detailed information of energy consumption patterns and intelligent controlling to appliances at home. We propose a HEMS that can provide easy-to-access information on home energy consumption in real time, intelligent planning for controlling appliances, and optimization of power consumption at home. The HEMS consists of three modules: an advanced power control planning engine, a device control module, and a power resource management server. Our prototype system reduces the cost of power consumption by about 10%.
255Â citations
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TL;DR: Simulation results show that the proposed evolutionary algorithms-based DSM model optimally schedules the appliances resulting in electricity bill and peaks reductions.
Abstract: Demand side management (DSM) will play a significant role in the future smart grid by managing loads in a smart way. DSM programs, realized via home energy management systems for smart cities, provide many benefits; consumers enjoy electricity price savings and utility operates at reduced peak demand. In this paper, evolutionary algorithms-based (binary particle swarm optimization, genetic algorithm, and cuckoo search) DSM model for scheduling the appliances of residential users is presented. The model is simulated in time of use pricing environment for three cases: 1) traditional homes; 2) smart homes; and 3) smart homes with renewable energy sources. Simulation results show that the proposed model optimally schedules the appliances resulting in electricity bill and peaks reductions.
141Â citations
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TL;DR: This paper proposes an electricity load scheduling algorithm that controls the operation time and energy consumption level of each appliance adapting to time-of-use pricing in order to maximize the overall net utility of the residence while satisfying its budget limit.
Abstract: In this paper, we study an electricity load scheduling problem in a residence. Compared with previous works in which only limited sets of appliances are considered, we classify various appliances into five sets considering their different energy consumption and operation characteristics, and provide mathematical models for them. With these appliance models, we propose an electricity load scheduling algorithm that controls the operation time and energy consumption level of each appliance adapting to time-of-use pricing in order to maximize the overall net utility of the residence while satisfying its budget limit. The optimization problem is formulated as a mixed integer nonlinear programming (MINLP) problem, which is in general, difficult to solve. In order to solve the problem, we use the generalized Benders decomposition approach with which we can solve the MINLP problem easily with low computational complexity. By solving the problem, we provide an algorithm to obtain the optimal electricity load scheduling of various appliances with different energy consumption and operation characteristics in a unified way.
133Â citations
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TL;DR: An optimization problem under various practical constraints is formed, which is shown to be a mixed integer programming problem that can be solved through a step-wise approach and a novel scheme based on Dijkstra algorithm is proposed, which results in the similar performance to that of the proposed optimal scheme while exhibiting much lower complexity.
Abstract: Smart grid with latest technologies provides solid foundation for the implementation of energy management systems at home premises. This paper proposes an autonomous energy management-based cost reduction solution for peak load times using a home energy management system (HEMS). Within a home environment, both the real time and the schedulable appliances are connected with smart meter through HEMS. We formulate an optimization problem under various practical constraints, which is shown to be a mixed integer programming problem that can be solved through a step-wise approach. A novel scheme based on Dijkstra algorithm is proposed, which results in the similar performance to that of the proposed optimal scheme while exhibiting much lower complexity. To further save the computational efforts, a low complexity scheme is also proposed, which produces considerably better results than the non-optimized scheme with the same complexity yet. Simulation results are presented at show the performance and complexity comparison of different proposed solutions and the existing methods.
107Â citations