Optimal Operation of a Combined Heat and Power System Considering Real-time Energy Prices

The combined heat and power (CHP) systems can provide heat and electricity simultaneously. They are promising in the future energy landscape because of high efficiency and low emissions. This paper proposes a new operation optimization model of CHPs in deregulated energy markets. Both CHPs' overall efficiency and heat to electricity ratio are closely linked with the loading level, which are dynamically determined in this paper. A discrete optimization model is then proposed to determine the optimal real-time operation strategies for the CHPs. The optimization problem is solved by the interior point method with discrete time intervals, in which the discrete optimal operation points can be identified effectively. This step projects the potential operation strategies that could produce maximum benefits. Finally, a dynamic programming algorithm is developed to maximize the profits of CHPs through dynamically modifying the operation strategies projected in the previous step considering transient constraints. The proposed new methodology is demonstrated on a 1-MW CHP system with real-time data.

[1]  M. Lehtonen,et al.  Analyzing the optimal coordination of a residential micro-CHP system with a power sink , 2015 .

[2]  Pierluigi Mancarella,et al.  Assessment of the greenhouse gas emissions from cogeneration and trigeneration systems. Part I: Models and indicators , 2008 .

[3]  S. Granville Optimal reactive dispatch through interior point methods , 1994 .

[4]  Whitney Colella,et al.  Design options for achieving a rapidly variable heat-to-power ratio in a combined heat and power (CHP) fuel cell system (FCS) , 2002 .

[5]  Nelson Fumo,et al.  Performance analysis of CCHP and CHP systems operating following the thermal and electric load , 2009 .

[6]  Jun Liu,et al.  Adaptive barrier filter-line-search interior point method for optimal power flow with FACTS devices , 2015 .

[7]  Jiangjiang Wang,et al.  An illustration of the optimization of combined cooling heating and power systems using genetic algorithm , 2014 .

[8]  Zhiqiang Zhai,et al.  Performance comparison of combined cooling heating and power system in different operation modes , 2011 .

[9]  Arthur H. Rosenfeld,et al.  Combined heat and power (CHP or cogeneration) for saving energy and carbon in commercial buildings , 1998 .

[10]  Saffa Riffat,et al.  Development of small-scale and micro-scale biomass-fuelled CHP systems – A literature review , 2009 .

[11]  M. Kurrat,et al.  Virtual power plants with combined heat and power micro-units , 2005, 2005 International Conference on Future Power Systems.

[12]  Paolo Iora,et al.  Innovative combined heat and power system based on a double shaft intercooled externally fired gas cycle , 2013 .

[13]  B. Mohammadi-ivatloo,et al.  Combined heat and power economic dispatch problem solution using particle swarm optimization with ti , 2013 .

[14]  Z. Wu,et al.  Microgrid economic optimal operation of the combined heat and power system with renewable energy , 2010, IEEE PES General Meeting.

[15]  A. Abbasi,et al.  Unified electrical and thermal energy expansion planning with considering network reconfiguration , 2015 .

[16]  Qian Ai,et al.  Optimal Operation of Combined Heat and Power System Based on Forecasted Energy Prices in Real-Time Markets , 2015 .

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

[18]  S. Chowdhury,et al.  Planned Scheduling for Economic Power Sharing in a CHP-Based Micro-Grid , 2012, IEEE Transactions on Power Systems.

[19]  Ali Reza Seifi,et al.  Simultaneous Integrated stochastic electrical and thermal energy expansion planning , 2014 .

[20]  Ala Hasan,et al.  Selection of micro-cogeneration for net zero energy buildings (NZEB) using weighted energy matching index , 2014 .

[21]  Antonio Piacentino,et al.  Energy saving in airports by trigeneration. Part I: Assessing economic and technical potential , 2006 .

[22]  M. M. Ardehali,et al.  Combined cooling, heating, and power system optimal pricing for electricity and natural gas using particle swarm optimization based on bi-level programming approach: Case study of Canadian energy sector , 2015 .

[23]  Dag Henning Cost minimization for a local utility through CHP, heat storage and load management , 1998 .

[24]  Mohammad Hassan Moradi,et al.  An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming , 2013 .