A MINLP model of optimal scheduling for a district heating and cooling system: A case study of an energy station in Tianjin

Abstract Rational scheduling strategy is the key to play the economy of district heating and cooling (DHC) system. However, very limited studies have been conducted on it using a suitable model or based on actual operational data, which made the obtained results not realistic or feasible. This paper proposes an actual operational-based optimal scheduling strategy to minimize the daily operation cost of an energy station in Tianjin integrated with electric chiller (EC) system, ground source heat pump (GSHP) system, water thermal energy storage (WTES) system and combined cooling, heating and power (CCHP) system under background of actual cooling load demand. Considering both nonlinear input-output characteristics and discrete working ranges of energy equipments, the mixed-integer nonlinear programming model is used to solve this problem. Results illustrate that the proposed optimal scheduling strategy can achieve zero waste of cooling energy and the cost saving ratio can reach to 24.3%, 34.2%, 47.3% and 63.9% under the load ratio of 75%, 60%, 45% and 30% respectively, compared with the existing scheduling strategy, which shows the cost saving effect is significant especially for the new-built energy station during the initial operation stage.

[1]  Ibrahim Dincer,et al.  Thermodynamic analyses and case studies of geothermal based multi-generation systems , 2012 .

[2]  Miao Li,et al.  Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings , 2014 .

[3]  Yingxin Zhu,et al.  District cooling and heating with seawater as heat source and sink in Dalian, China , 2007 .

[4]  Yongjun Sun,et al.  Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming , 2015 .

[5]  Frank Pettersson,et al.  Structural and operational optimisation of distributed energy systems , 2006 .

[6]  Marc A. Rosen,et al.  District heating and cooling: Review of technology and potential enhancements , 2012 .

[7]  Fu Xiao,et al.  Robust optimal design of district cooling systems and the impacts of uncertainty and reliability , 2016 .

[8]  Junghui Chen,et al.  Using cooling load forecast as the optimal operation scheme for a large multi-chiller system , 2011 .

[9]  Shengwei Wang,et al.  Impacts of cooling load calculation uncertainties on the design optimization of building cooling systems , 2015 .

[10]  Yan Lu,et al.  Optimal scheduling of chiller plant with thermal energy storage using mixed integer linear programming , 2013, 2013 American Control Conference.

[11]  Luis M. Serra,et al.  Operational strategy and marginal costs in simple trigeneration systems , 2009 .

[12]  Kody M. Powell,et al.  Heating, cooling, and electrical load forecasting for a large-scale district energy system , 2014 .

[13]  Truong Nghiem,et al.  Green Scheduling for Energy-Efficient Operation of Multiple Chiller Plants , 2012, 2012 IEEE 33rd Real-Time Systems Symposium.

[14]  Hongbo Ren,et al.  A MILP model for integrated plan and evaluation of distributed energy systems , 2010 .

[15]  Yingxin Zhu,et al.  Study on the decision-making of district cooling and heating systems by means of value engineering , 2010 .

[16]  Fu Xiao,et al.  Performance assessment of district cooling systems for a new development district at planning stage , 2015 .

[17]  Nengling Tai,et al.  Energy regulating and fluctuation stabilizing by air source heat pump and battery energy storage system in microgrid , 2016 .

[18]  Shang-Ho Tsai,et al.  Economic dispatch of chiller plant by improved ripple bee swarm optimization algorithm for saving energy , 2016 .

[19]  Tor-Martin Tveit,et al.  Multi-period MINLP model for optimising operation and structural changes to CHP plants in district heating networks with long-term thermal storage , 2009 .

[20]  Yung-Chung Chang,et al.  Economic dispatch of chiller plant by gradient method for saving energy , 2010 .

[21]  Yang Zhao,et al.  MPC-based optimal scheduling of grid-connected low energy buildings with thermal energy storages , 2015 .

[22]  Gaetano Florio,et al.  A mixed integer programming model for optimal design of trigeneration in a hospital complex , 2007 .

[23]  Patrizia Beraldi,et al.  Optimal design of a small size trigeneration plant in civil users: A MINLP (Mixed Integer Non Linear Programming Model) , 2015 .

[24]  Huang Xing-hua,et al.  Influence of energy demands ratio on the optimal facility scheme and feasibility of BCHP system , 2008 .

[25]  Ma,et al.  Development Strategies of Smart Grid in China and Abroad , 2013 .

[26]  Qinghua Wu,et al.  Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system , 2014 .

[27]  Louise Trygg,et al.  Increased use of district heating in industrial processes – Impacts on heat load duration , 2009 .

[28]  Masao Fukushima,et al.  A Two‐Stage Stochastic Mixed‐Integer Programming Approach to the Smart House Scheduling Problem , 2014 .

[29]  I. Dincer,et al.  A new approach for predicting cooling degree-hours and energy requirements in buildings , 2011 .

[30]  Risto Lahdelma,et al.  An efficient linear programming model and optimization algorithm for trigeneration , 2005 .

[31]  Kari Alanne,et al.  Distributed energy generation and sustainable development , 2006 .

[32]  Jorge Crichigno,et al.  Scheduling coupled photovoltaic, battery and conventional energy sources to maximize profit using linear programming , 2014 .

[33]  Zhe Tian,et al.  The improvement of a simulation model for a distributed CCHP system and its influence on optimal operation cost and strategy , 2016 .

[34]  Ruzhu Wang,et al.  Optimal operation of a micro-combined cooling, heating and power system driven by a gas engine , 2009 .

[35]  Long Wei-ding,et al.  An optimal sizing method for cogeneration plants , 2006 .