Next Article in Journal
Social Landscape Optimization of Towns and Villages at the County Level by Developing a Compound Ecological Capital System
Next Article in Special Issue
Smart Grid R&D Planning Based on Patent Analysis
Previous Article in Journal
Decision Support Systems for Smarter and Sustainable Logistics of Construction Sites
Previous Article in Special Issue
Three-Phase Unbalanced Optimal Power Flow Using Holomorphic Embedding Load Flow Method
Article Menu

Export Article

Open AccessArticle

Game Theoretical Energy Management with Storage Capacity Optimization and Photo-Voltaic Cell Generated Power Forecasting in Micro Grid

1
Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
2
Department of Electronics and Electrical Systems, The University of Lahore, Lahore 54000, Pakistan
3
Department of Electrical Engineering, Institute of Space Technology (IST), Islamabad 44000, Pakistan
4
Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
*
Authors to whom correspondence should be addressed.
This manuscript is an extended version of paper published in the proceedings of 33rd International Conference on Advanced Information Networking and Applications (AINA), Matsue, Japan, 27–29 March 2019.
Sustainability 2019, 11(10), 2763; https://doi.org/10.3390/su11102763
Received: 18 March 2019 / Revised: 17 April 2019 / Accepted: 25 April 2019 / Published: 14 May 2019
(This article belongs to the Special Issue Smart Energy Management for Smart Grids)
  |  
PDF [1510 KB, uploaded 17 May 2019]
  |  

Abstract

In order to ensure optimal and secure functionality of Micro Grid (MG), energy management system plays vital role in managing multiple electrical load and distributed energy technologies. With the evolution of Smart Grids (SG), energy generation system that includes renewable resources is introduced in MG. This work focuses on coordinated energy management of traditional and renewable resources. Users and MG with storage capacity is taken into account to perform energy management efficiently. First of all, two stage Stackelberg game is formulated. Every player in game theory tries to increase its payoff and also ensures user comfort and system reliability. In the next step, two forecasting techniques are proposed in order to forecast Photo Voltaic Cell (PVC) generation for announcing optimal prices. Furthermore, existence and uniqueness of Nash Equilibrium (NE) of energy management algorithm are also proved. In simulation, results clearly show that proposed game theoretic approach along with storage capacity optimization and forecasting techniques give benefit to both players, i.e., users and MG. The proposed technique Gray wolf optimized Auto Regressive Integrated Moving Average (GARIMA) gives 40% better result and Cuckoo Search Auto Regressive Integrated Moving Average (CARIMA) gives 30% better results as compared to existing techniques. View Full-Text
Keywords: forecasting; solar generation; storage capacity; game theory; nash equilibrium; distributed energy management algorithm; micro grid; meta heuristic techniques forecasting; solar generation; storage capacity; game theory; nash equilibrium; distributed energy management algorithm; micro grid; meta heuristic techniques
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Naz, A.; Javaid, N.; Rasheed, M.B.; Haseeb, A.; Alhussein, M.; Aurangzeb, K. Game Theoretical Energy Management with Storage Capacity Optimization and Photo-Voltaic Cell Generated Power Forecasting in Micro Grid. Sustainability 2019, 11, 2763.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top