scholarly journals Two-Stage Energy Management of Multi-Smart Homes With Distributed Generation and Storage

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 512 ◽  
Author(s):  
Efe Isa Tezde ◽  
Halil Ibrahim Okumus ◽  
Ibrahim Savran
Keyword(s):  
Energy Management ◽  
Distributed Generation ◽  
Management System ◽  
Distributed Storage ◽  
User Preferences ◽  
Total Power ◽  
Energy Management System ◽  
Two Stage ◽  
Electricity Cost ◽  
And Storage

This study presents a new two-stage hybrid optimization algorithm for scheduling the power consumption of households that have distributed energy generation and storage. In the first stage, non-identical home energy management systems (HEMSs) are modeled. HEMS may contain distributed generation systems (DGS) such as PV and wind turbines, distributed storage systems (DSS) such as electric vehicle (EV), and batteries. HEMS organizes the controllable appliances considering user preferences, amount of energy generated/stored and electricity price. A group of optimum consumption schedules for each HEMS is calculated by a Genetic Algorithm (GA). In the second stage, a neighborhood energy management system (NEMS) is established based on Bayesian Game (BG). In this game, HEMSs are players and their pre-determined optimal schedules are their actions. NEMS regulates the total power fluctuations by allowing the energy transfer among households. In the proposed algorithm, HEMS decreases the electricity cost of the users, while NEMS flats the load curve of the neighborhood to prevent overloading of the distribution transformer. The proposed HEMS and NEMS models are implemented from scratch. A survey of 250 participants was conducted to determine user habits. The results of the survey and the proposed system were compared. In conclusion, the proposed hybrid energy management system saves power by up to 25% and decreases cost by 8.7% on average.

scholarly journals An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory

2019 ◽  
Vol 11 (22) ◽  
pp. 6287 ◽  
Author(s):  
Aqib Jamil ◽  
Turki Ali Alghamdi ◽  
Zahoor Ali Khan ◽  
Sakeena Javaid ◽  
Abdul Haseeb ◽  
...  
Keyword(s):  
Game Theory ◽  
Energy Management ◽  
Waiting Time ◽  
Management System ◽  
Search Algorithm ◽  
Energy Management System ◽  
Hybrid Technique ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Home Energy Management System

The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.

Operation Scheduling of Household Load, EV and BESS Using Real Time Pricing, Incentive Based DR and Peak Power Limiting Strategy

2018 ◽  
Vol 20 (1) ◽  
Author(s):  
Sandeep Kakran ◽  
Saurabh Chanana
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Cost Reduction ◽  
Management System ◽  
Peak Power ◽  
Base Case ◽  
Energy Management System ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Home Energy Management System

Abstract Demand response (DR) programs have become powerful tools of the smart grids, which provide opportunities for the end-use consumers to participate actively in the energy management programs. This paper investigates impact of different DR strategies in a home-energy management system having consumer with regular load, electric vehicle (EV) and battery-energy storage system (BESS) in the home. The EV is considered as a special type of load, which can also work as an electricity generation source by discharging the power in vehicle-to-home mode during high price time. BESS and a small renewable energy source in form of rooftop photovoltaic panels give a significant contribution in the energy management of the system. As the main contribution to the literature, a mixed integer linear programming based model of home energy management system is formulated to minimize the daily cost of electricity consumption under the effect of different DR programs; such as real time price based DR program, incentive based DR program and peak power limiting DR program. Finally, total electricity prices are analysed in the case studies by including different preferences of the household consumer under mentioned DR programs. A total of 26.93 % electricity cost reduction is noticed with respect to base case, without peak limiting DR and 19.93 % electricity cost reduction is noticed with respect to base case, with peak limiting DR.

scholarly journals Energy Optimization in Smart Urban Buildings Using Bio-Inspired Ant Colony Optimization

2021 ◽  
Author(s):  
Fakhri Alam Khan ◽  
Kifayat Ullah ◽  
Atta ur Rahman ◽  
Sajid Anwar
Keyword(s):  
Ant Colony Optimization ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Ant Colony ◽  
Consumption Pattern ◽  
Energy Management System ◽  
Electricity Cost ◽  
Home Appliances ◽  
Home Energy Management

Abstract Instead of planting new electricity generation units, there is a need to design an efficient energy management system to achieve a normalized trend of power consumption. Smart grid has been evolved as a solution, where Demand Response (DR) strategy is used to modify the nature of demand of consumer. In return, utility pay incentives to the consumer. The increasing load demand in residential area and irregular electricity load profile have encouraged us to propose an efficient Home Energy Management System (HEMS) for optimal scheduling of home appliances. In order to meet the electricity demand of the consumers, the energy consumption pattern of a consumer is maintained through scheduling the appliances in day-ahead and real-time bases. In this paper we propose a hybrid algorithm Bacterial foraging Ant colony optimization is proposed (HB-ACO) which contain both BFA and ACO properties. Primary objectives of scheduling is to shift load from On-peak hour to Off-peak hours to reduce electricity cost and peak to average ratio. A comparison of these algorithms is also presented in terms of performance parameters electricity cost, reduction of PAR and user comfort in term of waiting time. The proposed techniques are evaluated using two pricing scheme time of use and critical peak pricing. The HB-ACO shows better performance as compared to ACO and BFA which is evident from the simulation results Moreover the concept of coordination among home appliances is presented for real time scheduling. We consider this is knapsack problem and solve it through Ant colony optimization algorithm.

scholarly journals INTELLIGENT ENERGY MANAGEMENT SYSTEM FOR RESIDENTIAL BUILDINGS BASED ON ZIGBEE TECHNOLOGY

2013 ◽  
pp. 181-186
Author(s):  
SANGEETA MODI ◽  
RITU NAIYA ◽  
SHAIK SHABANA
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Sensor Technology ◽  
Energy Management System ◽  
Present Scheme ◽  
Electricity Cost ◽  
Zigbee Technology

Energy consumption in residential buildings account for 20 to 40 per cent of total energy consumed in a country and therefore represents a significant and potential source of energy savings. An Intelligent Energy Management System can contribute to major reductions of energy use in hundreds of millions of buildings. This paper gives an overview of sensor technology and wireless networks in the development of an intelligent energy management system for residential buildings (IEMSRB). This technology has ample potential to change the way we live and work. In this paper ZigBee is used as a communication medium in building intelligent energy management system. From the prototype setup, it is shown that ZigBee is a suitable technology to be adopted as the communication infrastructure in energy management system for residential buildings .The performance analysis discussed in this paper verifies the effectiveness of using ZigBee in energy management system. The novelty of the present scheme is its ability to save the energy and improve the performance as it learns and gains more experience in real-time operations. Results also demonstrate that the proposed scheme can achieve the minimum electricity cost for residential customers. The proposed system can be installed and maintained in residential environments with ease.

scholarly journals Comparative Study on Optimization Solvers for Implementation of a Two-Stage Economic Dispatch Strategy in a Microgrid Energy Management System

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1096 ◽  
Author(s):  
Gi-Ho Lee ◽  
Jae-Young Park ◽  
Seung-Jun Ham ◽  
Young-Jin Kim
Keyword(s):  
Comparative Study ◽  
Energy Management ◽  
Management System ◽  
Economic Dispatch ◽  
Optimal Schedule ◽  
Mixed Integer ◽  
Energy Management System ◽  
Two Stage ◽  
Microgrid Energy Management ◽  
Optimization Solvers

A microgrid energy management system (MEMS) optimally schedules the operation of dispatchable distributed energy resources to minimize the operation costs of microgrids (MGs) via an economic dispatch (ED). Actual ED implementation in the MEMS relies on an optimization software package called an optimization solver. This paper presents a comparative study of optimization solvers to investigate their suitability for ED implementation in the MEMS. Four optimization solvers, including commercial as well as open-source-based ones, were compared in terms of their computational capability and optimization results for ED. Two-stage scheduling was applied for the ED strategy, whereby a mixed-integer programming problem was solved to yield the optimal operation schedule of battery-based energy storage systems. In the first stage, the optimal schedule is identified one day before the operating day; in the second stage, the optimal schedule is updated every 5 min during actual operation to compensate for operational uncertainties. A modularized programming strategy was also introduced to allow for a comparison between the optimization solvers and efficient writing of codes. Comparative simulation case studies were conducted on three test-bed MGs to evaluate the optimization results and computation times of the compared optimization solvers.

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