Integrated energy and ancillary services provision in multi-energy systems

Multi-energy systems (MES) in which operation and planning of electricity networks is optimally framed within a context of interaction with other energy vectors such as heat, cooling and gas, are receiving increasing interest from the point of view of providing flexibility to the power system. In this outlook, MES have the potential to provide real time demand response services by deploying the possibility to internally shift energy vectors between different plant components, thus decreasing the equivalent electricity input from the grid. This could be particularly relevant to provide ancillary services to future systems. On these premises, the aim of this paper is to set out a framework for the techno-economic assessment of integrated provision of energy and ancillary services from MES while supplying local multi-energy demand. The concepts of fuel-to-power arbitrage or equivalently of multi-energy arbitrage, electricity shifting potential, and ancillary services profitability maps are introduced and discussed to synthesize the developed framework. Specific numerical applications are presented to illustrate through case studies the implications of the proposed concepts.

[1]  Pierluigi Mancarella,et al.  Distributed multi-generation: A comprehensive view , 2009 .

[2]  Pierluigi Mancarella,et al.  Operational optimization of multigeneration systems , 2012 .

[3]  Pierluigi Mancarella,et al.  Multi-energy systems : An overview of concepts and evaluation models , 2015 .

[4]  Robert F. Boehm Developments in the design of thermal systems , 1997 .

[5]  A. Bakirtzis,et al.  Optimal Self-Scheduling of a Thermal Producer in Short-Term Electricity Markets by MILP , 2010, IEEE Transactions on Power Systems.

[6]  M. Krarti Cogeneration: Combined Heat and Power Systems , 2005 .

[7]  Bart De Schutter,et al.  Demand Response With Micro-CHP Systems , 2011, Proceedings of the IEEE.

[8]  Pierluigi Mancarella,et al.  Distributed multi-generation systems: energy models and analyses , 2009 .

[9]  Pierluigi Mancarella,et al.  Real-Time Demand Response From Energy Shifting in Distributed Multi-Generation , 2013, IEEE Transactions on Smart Grid.

[10]  G. Chicco,et al.  From cogeneration to trigeneration: profitable alternatives in a competitive market , 2006, IEEE Transactions on Energy Conversion.

[11]  Kankar Bhattacharya,et al.  Optimal Operation of Residential Energy Hubs in Smart Grids , 2012, IEEE Transactions on Smart Grid.

[12]  G. Andersson,et al.  Optimal Power Flow of Multiple Energy Carriers , 2007, IEEE Transactions on Power Systems.

[13]  Pierluigi Mancarella,et al.  Matrix modelling of small-scale trigeneration systems and application to operational optimization , 2009 .

[14]  A. Conejo,et al.  Optimal Response of a Power Generator to Energy, AGC, and Reserve Pool-Based Markets , 2002, IEEE Power Engineering Review.

[15]  Pierluigi Mancarella From cogeneration to trigeneration: energy planning and evaluation in a competitive market framework , 2006 .

[16]  Antonio Valero,et al.  Developments in the Design of Thermal Systems: An introduction of thermoeconomics , 1997 .

[17]  Pierluigi Mancarella Cogeneration systems with electric heat pumps: Energy-shifting properties and equivalent plant modelling , 2009 .

[18]  Goran Strbac,et al.  Fundamentals of Power System Economics: Kirschen/Power System Economics , 2005 .

[19]  D. Kirschen,et al.  Fundamentals of power system economics , 1991 .

[20]  P. Mancarella,et al.  Decentralized Participation of Flexible Demand in Electricity Markets—Part II: Application With Electric Vehicles and Heat Pump Systems , 2013, IEEE Transactions on Power Systems.

[21]  Leslie Daryl Danny Harvey,et al.  A Handbook on Low-Energy Buildings and District-Energy Systems : Fundamentals, Techniques and Examples , 2012 .