Experimental validation of a real time energy management system for microgrids in islanded mode using a local day-ahead electricity market and MINLP

Energy management systems (EMS) are vital supervisory control tools used to optimally operate and schedule Microgrids (MG). In this paper, an EMS algorithm based on mixed-integer nonlinear programming (MINLP) is presented for MG in islanding mode considering different scenarios. A local energy market (LEM) is also proposed with in this EMS to obtain the cheapest price, maximizing the utilization of distributed energy resources. The proposed energy management is based on LEM and allows scheduling the MG generation with minimum information shared sent by generation units. Load demand management is carried out by demand response concept to improve reliability and efficiency as well as to reduce the total cost of energy (COE). Simulations are performed with real data to test the performance and accuracy of the proposed algorithm. The proposed algorithm is experimentally tested to evaluate processing speed as well as to validate the results obtained from the simulation setup on a real MG Testbed. The results of the EMS–MINLP based on LEM are compared with a conventional EMS based on LEM. Simulation and experimental results show the effectiveness of the proposed algorithm which provides a reduction of 15% in COE, in comparison with conventional EMS.

[1]  Chi-Keung Woo,et al.  Avoided cost estimation and cost-effectiveness of permanent load shifting in California , 2012 .

[2]  Pierluigi Siano,et al.  Combined Monte Carlo simulation and OPF for wind turbines integration into distribution networks , 2013 .

[3]  Zita Vale,et al.  Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming , 2010 .

[4]  Oriol Gomis-Bellmunt,et al.  Centralized and Distributed Active and Reactive Power Control of a Utility Connected Microgrid Using IEC61850 , 2012, IEEE Systems Journal.

[5]  Mehdi Ehsan,et al.  A dynamic fuzzy interactive approach for DG expansion planning , 2012 .

[6]  Gwo-Ching Liao,et al.  Solve environmental economic dispatch of Smart MicroGrid containing distributed generation system – Using chaotic quantum genetic algorithm , 2012 .

[7]  Andreas Sumper,et al.  Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets , 2013 .

[8]  Farrokh Aminifar,et al.  Load commitment in a smart home , 2012 .

[9]  Pierluigi Siano,et al.  Optimal wind turbines placement within a distribution market environment , 2013, Appl. Soft Comput..

[10]  M. Parsa Moghaddam,et al.  Integrating commercial demand response resources with unit commitment , 2013 .

[11]  S. M. Shahidehpour,et al.  A new approach for GenCos profit based unit commitment in day-ahead competitive electricity markets considering reserve uncertainty , 2007 .

[12]  Heikki N. Koivo,et al.  System modelling and online optimal management of MicroGrid using Mesh Adaptive Direct Search , 2010 .

[13]  Rashad M. Kamel,et al.  Enhancement of micro-grid performance during islanding mode using storage batteries and new fuzzy logic pitch angle controller , 2011 .

[14]  Oriol Gomis-Bellmunt,et al.  Operation of a Utility Connected Microgrid Using an IEC 61850-Based Multi-Level Management System , 2012, IEEE Transactions on Smart Grid.

[15]  Peter Cappers,et al.  An assessment of the role mass market demand response could play in contributing to the management of variable generation integration issues , 2012 .

[16]  Cristina Corchero,et al.  Optimal Bidding Strategies for Thermal and Generic Programming Units in the Day-Ahead Electricity Market , 2010, IEEE Transactions on Power Systems.

[17]  Fredrik Wallin,et al.  Forecasting for demand response in smart grids: An analysis on use of anthropologic and structural data and short term multiple loads forecasting , 2012 .

[18]  Ashoke Kumar Basu.  Microgrids: Planning of fuel energy management by strategic deployment of CHP-based DERs – An evolutionary algorithm approach , 2013 .

[19]  Ahmed Al-Salaymeh,et al.  Optimal operation of conventional power plants in power system with integrated renewable energy sources , 2013 .

[20]  P. Kanakasabapathy,et al.  Bidding strategy for pumped-storage plant in pool-based electricity market , 2010 .

[21]  C. Monteiro,et al.  Optimum residential load management strategy for real time pricing (RTP) demand response programs , 2012 .

[22]  Heikki N. Koivo,et al.  Multiobjective optimization using Mesh Adaptive Direct Search for power dispatch problem of microgrid , 2012 .

[23]  David Infield,et al.  Domestic electricity use: A high-resolution energy demand model , 2010 .

[24]  Mark Z. Jacobson,et al.  A Monte Carlo approach to generator portfolio planning and carbon emissions assessments of systems with large penetrations of variable renewables. , 2011 .

[25]  Pierluigi Siano,et al.  Evaluating the integration of wind power into distribution networks by using Monte Carlo simulation , 2013 .

[26]  Dong Gu Choi,et al.  An electricity generation planning model incorporating demand response , 2012 .

[27]  Josef Kallrath,et al.  Algebraic Modeling Systems , 2012 .

[28]  M. Haghifam,et al.  A demand response based solution for LMP management in power markets , 2011 .

[29]  Vahid Vahidinasab,et al.  Security-constrained self-scheduling of generation companies in day-ahead electricity markets considering financial risk , 2013 .

[30]  Riccardo Minciardi,et al.  Modeling and optimization of a hybrid system for the energy supply of a “Green” building , 2012 .

[31]  S. Ashok,et al.  Optimal management of microgrids , 2010, 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply.

[32]  Pablo Arboleya,et al.  Microgrid management with a quick response optimization algorithm for active power dispatch , 2012 .

[33]  P. Siano,et al.  Probabilistic Assessment of the Impact of Wind Energy Integration Into Distribution Networks , 2013, IEEE Transactions on Power Systems.

[34]  Amin Hajizadeh,et al.  Intelligent power management strategy of hybrid distributed generation system , 2007 .