Definition and on-field validation of a microgrid energy management system to manage load and renewables uncertainties and system operator requirements

Abstract The present paper proposes an Energy Management System (EMS) to be used in grid connected microgrids. To do this, first a suitable model (for optimization purposes) of all the components that typically appear in a microgrid is presented, then, four possible electric network models are detailed and finally the overall architecture of the optimization problem of the EMS is set up. Moreover, as the optimization of the energy production/consumption of a microgrid relies on the thermal and electric load and on the renewables forecasting, an online empirical correction of forecasted data is proposed, highlighting its positive impact on the overall operational cost of the microgrid. Another aspect which is accounted regards the possibility of allowing the EMS to act as a power plant controller in compliance with the Distribution System Operator (DSO) requirements in terms of reactive power management and voltage control (as requested by the majority of grid codes and national regulations). So, the proposed algorithm structure splits the optimization problem into two sub problems: the first one basically dictates the active power production of the dispatchable units minimizing an economic objective function, while the second accounts for the satisfaction of the DSO requirements. The experimental validation of the proposed EMS is performed on the University of Genoa Smart Polygeneration Microgrid (SPM), where the proposed EMS is currently running. The considered test cases highlight the effectiveness of the proposed EMS in economically operating the microgrid (compared to simpler EMS previously installed in the SPM) and in satisfying the reactive power or voltage regulation requirements provided by the Italian technical requirements.

[1]  A. Piccolo,et al.  Evaluating the Impact of Network Investment Deferral on Distributed Generation Expansion , 2009, IEEE Transactions on Power Systems.

[2]  Hak-Man Kim,et al.  A microgrid energy management system for inducing optimal demand response , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[3]  Yogesh L. Simmhan,et al.  Energy management systems: state of the art and emerging trends , 2013, IEEE Communications Magazine.

[4]  F. Pilo,et al.  A multiobjective evolutionary algorithm for the sizing and siting of distributed generation , 2005, IEEE Transactions on Power Systems.

[5]  Sung-Kwan Joo,et al.  Social Welfare Maximization in Transmission Enhancement Considering Network Congestion , 2008, IEEE Transactions on Power Systems.

[6]  Pascal Van Hentenryck,et al.  A Linear-Programming Approximation of AC Power Flows , 2012, INFORMS J. Comput..

[7]  R. Adapa,et al.  Control of parallel connected inverters in stand-alone AC supply systems , 1991, Conference Record of the 1991 IEEE Industry Applications Society Annual Meeting.

[8]  Ali Davoudi,et al.  Hierarchical Structure of Microgrids Control System , 2012, IEEE Transactions on Smart Grid.

[9]  Chris Marnay,et al.  Integration of distributed energy resources. The CERTS Microgrid Concept , 2002 .

[10]  Ali Hooshmand,et al.  Experimental Demonstration of a Tiered Power Management System for Economic Operation of Grid-Tied Microgrids , 2014, IEEE Transactions on Sustainable Energy.

[11]  Seyed Hossein Hosseinian,et al.  An Optimal Dispatch Algorithm for Managing Residential Distributed Energy Resources , 2014, IEEE Transactions on Smart Grid.

[12]  Josep M. Guerrero,et al.  Aalborg Universitet Optimal Power Flow in Microgrids with Energy Storage , 2013 .

[13]  E.F. El-Saadany,et al.  Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization , 2010, IEEE Transactions on Power Systems.

[14]  Stefano Bracco,et al.  An optimization algorithm for the operation planning of the University of Genoa smart polygeneration microgrid , 2013, 2013 IREP Symposium Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid.

[15]  G. Winkler,et al.  Intelligent energy management of electrical power systems with distributed feeding on the basis of forecasts of demand and generation , 2001 .

[16]  N.P. Padhy,et al.  Unit commitment-a bibliographical survey , 2004, IEEE Transactions on Power Systems.

[17]  A. Bonfiglio,et al.  A technique for the optimal control and operation of grid-connected photovoltaic production units , 2012, 2012 47th International Universities Power Engineering Conference (UPEC).

[18]  Rodrigo Palma-Behnke,et al.  A Microgrid Energy Management System Based on the Rolling Horizon Strategy , 2013, IEEE Transactions on Smart Grid.

[19]  A. Piccolo,et al.  Exploring the Tradeoffs Between Incentives for Distributed Generation Developers and DNOs , 2007, IEEE Transactions on Power Systems.

[20]  E. M. Davidson,et al.  Distribution Power Flow Management Utilizing an Online Optimal Power Flow Technique , 2012, IEEE Transactions on Power Systems.

[21]  Stefano Bracco,et al.  An Energy Management System for the Savona Campus Smart Polygeneration Microgrid , 2017, IEEE Systems Journal.

[22]  Peter Palensky,et al.  Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads , 2011, IEEE Transactions on Industrial Informatics.

[23]  Pierluigi Siano,et al.  Hybrid GA and OPF evaluation of network capacity for distributed generation connections , 2008 .

[24]  Georgios B. Giannakis,et al.  Distributed Optimal Power Flow for Smart Microgrids , 2012, IEEE Transactions on Smart Grid.

[25]  D. A. Halamay,et al.  Optimal Energy Storage Sizing and Control for Wind Power Applications , 2011, IEEE Transactions on Sustainable Energy.

[26]  Federico Delfino,et al.  Definition and Experimental Validation of a Simplified Model for a Microgrid Thermal Network and its Integration into Energy Management Systems , 2016 .

[27]  R. Iravani,et al.  Microgrids management , 2008, IEEE Power and Energy Magazine.

[28]  Claudio A. Cañizares,et al.  A Centralized Energy Management System for Isolated Microgrids , 2014, IEEE Transactions on Smart Grid.

[29]  Vincent Del Toro,et al.  Electric Power Systems , 1991 .

[30]  Stefano Bracco,et al.  Day ahead microgrid optimization: A comparison among different models , 2014 .

[31]  Stephen J. Wright,et al.  Interior-point methods , 2000 .

[32]  Federico Delfino,et al.  An approximate methodology to verify the compliance of large photovoltaic power plants to system operator steady-state requirements , 2015 .

[33]  P. Siano,et al.  Combined Operations of Renewable Energy Systems and Responsive Demand in a Smart Grid , 2011, IEEE Transactions on Sustainable Energy.

[34]  Aouss Gabash,et al.  Active-Reactive Optimal Power Flow in Distribution Networks With Embedded Generation and Battery Storage , 2012, IEEE Transactions on Power Systems.

[35]  R. Iravani,et al.  Steady-State Model and Power Flow Analysis of Electronically-Coupled Distributed Resource Units , 2007, IEEE Transactions on Power Delivery.

[36]  Goran Strbac,et al.  Microgrids - Large Scale Integration of Microgeneration to Low Voltage Grids , 2006 .

[37]  Lennart Söder,et al.  Multi-objective coordinated droop-based voltage regulation in distribution grids with PV systems , 2014 .

[38]  J.P. Barton,et al.  Energy storage and its use with intermittent renewable energy , 2004, IEEE Transactions on Energy Conversion.