scholarly journals Modeling and Simulation of a Control Algorithm for Home Energy Management System

2019 ◽  
Vol 8 (4S2) ◽  
pp. 396-399
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Distribution Systems ◽  
Fuzzy Logic Controller ◽  
Energy Resources ◽  
Energy Management System ◽  
Battery Energy Storage ◽  
Home Energy Management ◽  
Battery Energy

Microgrids are handy units for a utility since their units such as distributed energy resources (DER) and loads can able to control the power ingestion or production. Moreover, it is used to assimilate renewable energy resources (RES) to small distribution systems. Battery energy storage systems (BESSs) are employed to recompense the sporadic output of RES. Similarly, DC microgrid for a home can be excellently controlled by an energy management system (EMS) using fuzzy logic controller (FLC) of 25-rules alone to control the power flow. The system has photovoltaic (PV), Fuel Cell (FC) and battery energy storage (BES). This study aims to introduce firefly algorithm (FA) to optimize FLC in order to increase the system energy saving efficiency and to reduce the cost.

scholarly journals An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1457 ◽  
Author(s):  
Shehab Al-Sakkaf ◽  
Mahmoud Kassas ◽  
Muhammad Khalid ◽  
Mohammad A. Abido
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Fuel Cell ◽  
Wind Turbine ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Economic Dispatch ◽  
Energy Management System ◽  
Battery Energy Storage ◽  
Battery Energy

This work presents the operation of an autonomous direct current (DC) DC microgrid for residential house controlled by an energy management system based on low complexity fuzzy logic controller of only 25-rules to manage the power flow that supply house load demand. The microgrid consists of photovoltaic (PV), wind turbine, fuel cell, battery energy storage and diesel generator. The size of the battery energy storage is determined based on the battery sizing algorithm depending on the generation of renewables during all seasons of the year in the eastern region of Saudi Arabia. Two scenarios are considered in this work. In the first scenario: the microgrid consists of solar PV, wind turbine, battery energy storage and fuel cell. The fuzzy logic controller is optimized using an artificial bee colony technique in order to increase the system energy saving efficiency and to reduce the cost. In the second scenario: wind turbine is replaced by a diesel generator, also the rated power of the fuel cell is reduced. In this scenario, a new method is proposed to reduce the generation cost of the dispatchable sources in the microgrid by considering economic dispatch within the optimized fuzzy logic energy management system. To obtain the most suitable technique for solving the economic dispatch problem, three optimization techniques were used which are particle swarm optimization, genetic algorithm and artificial bee colony based on real environmental data and real house load demand. A comparison in terms of energy saving between the two scenarios and a comparison in terms of cost reduction between conventional economic dispatch method and the proposed method are presented.

scholarly journals Integration of Electric Vehicles and Energy Storage System in Home Energy Management System with Home to Grid Capability

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8557
Author(s):  
Arshad Mohammad ◽  
Mohd Zuhaib ◽  
Imtiaz Ashraf ◽  
Marwan Alsultan ◽  
Shafiq Ahmad ◽  
...  
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Energy Cost ◽  
Management System ◽  
Economic Benefits ◽  
Binary Particle Swarm Optimization ◽  
Energy Management System ◽  
Multi Objective ◽  
Home Energy Management ◽  
Home Energy Management System

In this paper, we proposed a home energy management system (HEMS) that includes photovoltaic (PV), electric vehicle (EV), and energy storage systems (ESS). The proposed HEMS fully utilizes the PV power in operating domestic appliances and charging EV/ESS. The surplus power is fed back to the grid to achieve economic benefits. A novel charging and discharging scheme of EV/ESS is presented to minimize the energy cost, control the maximum load demand, increase the battery life, and satisfy the user’s-traveling needs. The EV/ESS charges during low pricing periods and discharges in high pricing periods. In the proposed method, a multi-objective problem is formulated, which simultaneously minimizes the energy cost, peak to average ratio (PAR), and customer dissatisfaction. The multi-objective optimization is solved using binary particle swarm optimization (BPSO). The results clearly show that it minimizes the operating cost from 402.89 cents to 191.46 cents, so that a reduction of 52.47% is obtained. Moreover, it reduces the PAR and discomfort index by 15.11% and 16.67%, respectively, in a 24 h time span. Furthermore, the home has home to grid (H2G) capability as it sells the surplus energy, and the total cost is further reduced by 29.41%.

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