Demand response of grid-connected microgrid based on metaheuristic optimization algorithm

ABSTRACT

Demand Response Programs (DRPs) have gained the microgrid (MG) operators phenomenal attention for mobilizing the end-users in alleviating the uncertainties associated with renewable energy sources. In this research work, the effective MG energy management system (EMS) in conjunction with price-driven DRPs is proposed to achieve synergistic coordination between the energy providers and consumers and reduce operational costs. The flexible price elasticity model is implemented instead of using the price elasticity models with a preordained constant value like most existing literature. This results in a more realistic characterization of customer responsiveness to energy price changes and promotes the DRPs under a grid-connected MG environment. With this regard, a stochastic day-ahead energy management strategy is proposed to incorporate four distinct DRPs and schedule the MG distributed energy resources. The proposed strategy is verified on a practical 3-feeder MG test system with a majority of 50% industrial load considered. The short-term scheduling period of 15 min ahead solar and wind power forecast is considered to optimize the microgrid dispatch costs accurately. The intermittent nature of renewable energy sources is addressed by employing a stochastic-based scenario generation and reduction approach. A novel and nature-inspired Black Widow Optimization (BWO) is applied to determine the optimal scheduling configuration. The effectiveness of the BWO is validated in terms of rate of convergence, computational time, and solution efficacy. Finally, the best DRP has been chosen based on its technical and economic performance indices by employing a multi-criteria decision-making approach.

KEYWORDS:

• Black widow optimization
• demand response program
• energy management system
• flexible price response model
• microgrid
• multi-criteria decision making
• stochastic programming

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Arvind R. Singh

Arvind R. Singh Key Laboratory of Power System Intelligent Dispatch and Control, School of Electrical Engineering, Shandong University, Ministry of Education, Jinan, China. Arvind R. Singh has obtained his BE (2009) from Walchand College of Sanlgi, Maharashtra, India. He obtained M. Tech. (2011) from College of Engineering, Pune, Maharashtra, India and Ph. D. (2017) from Visvesvaraya National Institute of Technology Nagpur, India. He is a Senior Member of IEEE and member of IAENG. Currenlty working as a postdoctoral research fellow at school of electrical engineering, shandong university, jinan china. His reasearch interests are Microgrid Operation, Control and Protection. Optimal operation of distributed energy resources in Microgrids. Smart grids and Integration of Renewable energy sources. Optimal Generation Scheduling and Energy Management of Microgrids.

Lei Ding

Lei Ding Key Laboratory of Power System Intelligent Dispatch and Control, School of Electrical Engineering, Shandong University, Ministry of Education, Jinan, China. Lei Ding (Senior Member, IEEE) received the B.E. and Ph.D. degrees in electrical engineering from Shandong University, Jinan, China, in 2001 and 2007, respectively. From 2008 to 2009, he was a Postdoctoral Researcher with Tsinghua University, Beijing, China. From 2010 to 2011, he was a Research Associate with the University of Manchester. He is currently a Professor with the School of Electrical Engineering, Shandong University. His research interests include power system wide-area protection, low inertia systems, and integration of renewable energy.

D. Koteswara Raju

D Koteswara Raju was completed B. Tech. in Electrical and Electronics Engineering from JNTU Hyderabad, India in 2006 and M Tech in Power System Engineering from ANU Vijayawada, India in 2009. He obtained his Ph.D. in 2017 from Visvesvaraya National Institute of Technology (VNIT), Nagpur, India. At present he is working as an Assistant Professor in the Department of Electrical Engineering, NIT Silchar, India. His reasearch interests are Power System Operation, Control and Protection. Optimal operation of distributed energy resources in Microgrids . Smart grids and Integration of Renewable energy sources. Soft Computing Algorithms for Optimal Generation Scheduling and Energy Management of Microgrids.

R. Seshu Kumar

R. Seshu Kumar completed his B.Tech in Electrical Engineering from JNUT Kakanada University in 2012 and M.Tech in Power System Emhapsis High Voltage Engineering from JNUT Kakanada University in 2015. Currently, pursuing his Ph.D in Electrical Engineering Department of National Institute of Technology Silchar, India. Soft Computing Algorithms for Optimal Generation Scheduling and Energy Management of Microgrids.

L. Phani Raghav

Lolla Phani Raghav completed his B.Tech in Electrical Engineering from JNUT Kakanada University in 2012 and M.Tech in Power System and Automation Engineering from Geetam University in 2014. Currently, pursuing his Ph.D in Electrical Engineering Department of National Institute of Technology Silchar, India. Soft Computing Algorithms for Optimal Generation Scheduling and Energy Management of Microgrids.