scholarly journals A Metaheuristic Harris Hawk Optimization Approach for Coordinated Control of Energy Management in Distributed Generation Based Microgrids

2021 ◽  
Vol 11 (9) ◽  
pp. 4085
Author(s):  
Mahmoud Abdelsalam ◽  
Hatem Y. Diab ◽  
A. A. El-Bary
Keyword(s):  
Energy Management ◽  
Cost Management ◽  
Minimum Cost ◽  
Energy Resources ◽  
Superior Performance ◽  
Optimization Approach ◽  
Energy Prices ◽  
Load Demand ◽  
Smart Energy Management ◽  
The Cost

Cost management of microgrids represents a real challenge since the power generation of microgrids is usually composed of different renewable and non-renewable sources. Additionally, it is always desired to make a connection between the microgrid and national grid to secure the load demand and to fit the regulations of liberated energy markets. Because of all these reasons, it is essential to develop a smart energy management unit to control different energy resources within the microgrid to achieve minimum operation costs. This paper presents a proposal for a smart unit for the cost management and operation of multi-source based microgrids. The proposed unit utilizes the Harris hawk optimization (HHO) algorithm which is used to optimize the cost of operation based on current load demand, energy prices and generation capacities. The proposed unit is tested on a microgrid with different energy resources using MATLAB while applying different operation scenarios. All simulation results show that the proposed unit succeeds in operating the microgrid at minimum cost. Obtained results are compared with other optimization algorithms and the proposed Harris hawk algorithm gives superior performance.

scholarly journals Optimal cost and feasible design for grid-connected microgrid on campus area using the robust-intelligence method

Clean Energy ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 823-840
Author(s):  
Mohamad Almas Prakasa ◽  
Subiyanto Subiyanto
Keyword(s):  
Genetic Algorithm ◽  
Energy Management ◽  
Energy Supply ◽  
Minimum Cost ◽  
Energy Utilization ◽  
Energy Management System ◽  
Energy Profile ◽  
Swarm Optimization ◽  
Conventional Methods ◽  
The Cost

Abstract In this paper, a robust optimization and sustainable investigation are undertaken to find a feasible design for a microgrid in a campus area at minimum cost. The campus microgrid needs to be optimized with further investigation, especially to reduce the cost while considering feasibility in ensuring the continuity of energy supply. A modified combination of genetic algorithm and particle swarm optimization (MGAPSO) is applied to minimize the cost while considering the feasibility of a grid-connected photovoltaic/battery/diesel system. Then, a sustainable energy-management system is also defined to analyse the characteristics of the microgrid. The optimization results show that the MGAPSO method produces a better solution with better convergence and lower costs than conventional methods. The MGAPSO optimization reduces the system cost by up to 11.99% compared with the conventional methods. In the rest of the paper, the components that have been optimized are adjusted in a realistic scheme to discuss the energy profile and allocation characteristics. Further investigation has shown that MGAPSO can optimize the campus microgrid to be self-sustained by enhancing renewable-energy utilization.

Efficient Energy Management System Based on GA and Classical Boolean Approach

2016 ◽  
Vol 15 (03) ◽  
pp. 1650012
Author(s):  
Musbah Abdulgader ◽  
Cheng Yang ◽  
Devinder Kaur
Keyword(s):  
Cost Saving ◽  
Energy Management ◽  
Cost Savings ◽  
Department Of Energy ◽  
Time Data ◽  
Storage Unit ◽  
Energy Storage Unit ◽  
Load Demand ◽  
The Cost ◽  
The Impact

In this paper, two intelligent strategies for energy management unit for a home integrated with smart grid are proposed. The strategies are based on classical Boolean and genetic algorithm (GA). The objective is to optimize the cost saving for the end consumer. The price of energy varies by the hour depending on the load on the grid. The two strategies predict when and by how much the storage unit installed in the house should charge and release for 24 h of the day, satisfying the constraint that the load demand of the house at any particular hour should always be met. The strategies were tested by real time data collected by the Department of Energy for a typical house in the Chicago, Illinois region for the year 2013. Both the strategies achieve cost savings; however, it has been found that GA-based strategy results in higher cost saving. The impact of the capacity of the energy storage unit (ESU) on the cost saving has been analyzed for a GA strategy and cost saving obtained when the capacity of ESU is 1.5 times and 2 times the house hold load at any given hour is presented.

scholarly journals A cuckoo load scheduling optimization approach for smart energy management

2021 ◽  
Vol 7 ◽  
pp. 4705-4721
Author(s):  
Ahmed Shaban ◽  
Hagag Maher ◽  
Mahmoud Elbayoumi ◽  
Suzan Abdelhady
Keyword(s):  
Energy Management ◽  
Optimization Approach ◽  
Scheduling Optimization ◽  
Load Scheduling ◽  
Smart Energy Management

FINANCING AUSTRALIAN ENERGY DEVELOPMENT AN INTERNATIONAL VIEW

1981 ◽  
Vol 21 (1) ◽  
pp. 48
Author(s):  
J. G. Stabback ◽  
D. G. Waddingham
Keyword(s):  
Large Scale ◽  
Energy Resources ◽  
Energy Prices ◽  
Project Financing ◽  
International Firms ◽  
Available Energy ◽  
Internal Cash Flow ◽  
Oil And Natural Gas ◽  
The Cost ◽  
International View

In an energy-short world, escalating inflation and rising energy prices, the development of Australia's abundant natural resources will not only propel the economy forward through the 1980's, but will also significantly add to the world's available energy resources and lessen the upward pressure on oil prices.Enormous resources of coal and uranium are available in Australia together with modest reserves of crude oil and natural gas. The cost of developing these resources could well exceed $50 billion over the next decade. Because of the large scale and higher cost of developing these resources, increasing use of overseas funding will be needed unless taxation policies are altered in Australia to provide more internal cash flow. Joint ventures with international firms and project financing methods will be used more extensively in future to develop Australia's energy resources.

A Top-Down Concept Selection Integrating Analytical and Optimization Approaches

2009 ◽  
Author(s):  
Shun Takai ◽  
Vivek K. Jikar ◽  
Kenneth M. Ragsdell
Keyword(s):  
Optimization Algorithm ◽  
Analytical Approach ◽  
Minimum Cost ◽  
Design Matrix ◽  
Optimization Approach ◽  
Concept Selection ◽  
Top Down ◽  
Product Concept ◽  
Range Part ◽  
The Cost

This paper proposes a top-down approach for product concept selection. The proposed approach integrates an analytical approach to define an acceptable part specification range (part range), and an optimization approach to find optimum tolerances of part specifications. In the analytical part of the procedure, an inverse of design matrix is used to identify a part range. In the optimization part of the procedure, a product cost is defined as a function of part specification tolerances, and optimization algorithm is used to find optimum part specification tolerances that minimize the cost of the concept. The concept with the minimum cost is selected as the optimum concept. The usefulness of the proposed approach is demonstrated using an illustrative example.

scholarly journals Smart Energy Management for Unlocking Demand Response in the Residential Sector

Proceedings ◽  
2018 ◽  
Vol 2 (15) ◽  
pp. 1136 ◽  
Author(s):  
Xiangping Chen ◽  
Kui Weng ◽  
Fanlin Meng ◽  
Monjur Mourshed
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Demand ◽  
Residential Sector ◽  
Cost Of Energy ◽  
Smart Energy Management ◽  
Electrical Demand ◽  
The Uk ◽  
The Cost ◽  
Pv Generation

This paper presents a smart energy management system for unlocking demand response in the UK residential sector. The approach comprises the estimation of one-hour energy demand and PV generation (supply) for scheduling the 24-h ahead demand profiles by shifting potential flexible loads. Real-time electrical demand is met by combining power supplies from PV, grid and batteries while minimizing consumer’s cost of energy. The results show that the peak-to-average ratio is reduced by 22.9% with the cost saving of 34.6% for the selected day.

The Research of Smart Energy Management System

2013 ◽  
Vol 341-342 ◽  
pp. 1219-1222
Author(s):  
Qing Dong Feng
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Resources ◽  
Automation System ◽  
Energy Management System ◽  
Building Automation ◽  
Renewable Energy Resources ◽  
Building Automation System ◽  
Smart Energy Management ◽  
Dynamic Energy Management

The article introduces the global research background and research achievements of the renewable energy resources micro grid dynamic energy management system (dynamic EMS).it will also describe the important effects of information technology used in smart grid. Furthermore, the building automation system are introduced and analyzed.

scholarly journals Smart Energy Management System of Environmentally Friendly Microgrid Based on Grasshopper Optimization Technique

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5000 ◽  
Author(s):  
Yehia Gad ◽  
Hatem Diab ◽  
Mahmoud Abdelsalam ◽  
Yasser Galal
Keyword(s):  
Energy Management ◽  
Management System ◽  
Optimization Technique ◽  
Minimum Cost ◽  
Energy Resources ◽  
Energy Management System ◽  
Renewable Energy Resources ◽  
Grasshopper Optimization Algorithm ◽  
Generation Cost ◽  
Grasshopper Optimization

A microgrid is a group of distributed energy resources and interconnected loads that may be operated either in isolated mode or connected mode with the main utility within electrical boundaries. Microgrids may consist of different types of renewable energy resources such as photovoltaic panels, wind turbines, fuel cells, micro turbines, and storage units. It is highly recommended to manage the dependency on these resources by implementing an energy management unit to optimize the energy exchange so that the minimum cost is achieved. In this paper, an energy management system based on the grasshopper optimization algorithm (GOA) is proposed to determine the optimal power generated by the distributed generators in the microgrid which is required to minimize the total generation cost. The proposed unit is applied to a microgrid that consists of five generating units feeding residential, commercial, and industrial loads, and results are compared to other available research in literature to validate the proposed algorithm.

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