Multi-objective planning for integrated energy systems considering both exergy efficiency and economy

Improving the comprehensive utilization level of energy has been a core goal for the optimal design of the integrated energy system (IES), which requires an accurate assessment of energy efficiency. The widely used criterion of conventional energy efficiency derived from the first law of thermodynamics has gradually been criticized for its shortcomings of neglecting the quality of energy. As a concept considering both the quantity and quality of energy, exergy efficiency has been recognized as a more reasonable index in recent decades. Nevertheless, it is a complicated problem to calculate the exergy efficiency among multiple energy forms in an electricity-gas-heating-cooling coupled IES, limiting its application in IES planning. This paper hence proposes the method of calculating the exergy efficiency of an IES by using a black-box model, after defining the concept of energy quality coefficient (EQC) that values the quality of various energy forms involved. And then, a multi-objective planning model considering both exergy efficiency and economy is thus proposed for the joint planning of energy generators, storages and networks, wherein a five-tier energy hub is modeled to deal with the multi-energy couplings. To reduce the difficulty of optimizing, several convex relaxation measures are designed to transform the non-convex original problem into a convex one. The proposed framework is verified in a real-world study case located in Guangzhou, China.

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

[2]  Jiang Zetao,et al.  Integrated Energy Station Design Considering Cold and Heat Storage , 2016 .

[3]  Clodomiro Unsihuay-Vila,et al.  A Model to Long-Term, Multiarea, Multistage, and Integrated Expansion Planning of Electricity and Natural Gas Systems , 2010, IEEE Transactions on Power Systems.

[4]  F. S. Hover,et al.  Convex Models of Distribution System Reconfiguration , 2012, IEEE Transactions on Power Systems.

[5]  Martin Geidl,et al.  Integrated Modeling and Optimization of Multi-Carrier Energy Systems , 2007 .

[6]  Giuseppe Forte,et al.  Environmental-constrained energy planning using energy-efficiency and distributed-generation facilities , 2008 .

[7]  Nilay Shah,et al.  A multi-objective optimization and multi-criteria evaluation integrated framework for distributed energy system optimal planning , 2018, Energy Conversion and Management.

[8]  D. Favrat,et al.  Energy and exergy analysis of a micro-compressed air energy storage and air cycle heating and cooling system , 2008 .

[9]  Shixue Wang,et al.  Energy and exergy analysis of thermoelectric generator system with humidified flue gas , 2018 .

[10]  Zhinong WEI,et al.  Multi-period integrated natural gas and electric power system probabilistic optimal power flow incorporating power-to-gas units , 2017 .

[11]  Elisa Guelpa,et al.  Entropy generation analysis for the design improvement of a latent heat storage system , 2013 .

[12]  Christos A. Frangopoulos,et al.  Recent developments and trends in optimization of energy systems , 2018, Energy.

[13]  Christopher J. Koroneos,et al.  Exergy analysis of renewable energy sources , 2003 .

[14]  Daniel Favrat,et al.  Conventional and advanced CO 2 based district energy systems , 2010 .

[15]  Lazaros G. Papageorgiou,et al.  A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level , 2012 .

[16]  Danxing Zheng,et al.  Energy Quality Factor and a New Thermodynamic Approach to Evaluate Cascade Utilization of Fossil Fuels , 2009 .

[17]  B Hua EXERGY ANALYSIS OF SOLAR ENERGY UTILIZING SYSTEM FOR LIGHT,HEAT,AND ELECTRICITY CONVERSION , 2005 .

[18]  Abdullah Abusorrah,et al.  Optimal Expansion Planning of Energy Hub With Multiple Energy Infrastructures , 2015, IEEE Transactions on Smart Grid.

[19]  Audrius Bagdanavicius,et al.  Combined analysis of electricity and heat networks , 2014 .

[20]  Chia-Chin Chuang,et al.  New approach to thermodynamics , 1997 .

[21]  Qiong Wu,et al.  Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects , 2010 .

[22]  Jeremy Rifkin,et al.  The third industrial revolution : how lateral power is transforming energy, the economy, and the world , 2011 .

[23]  Hoseyn Sayyaadi,et al.  Designing a solar powered Stirling heat engine based on multiple criteria: Maximized thermal efficiency and power , 2013 .

[24]  Lin Shi,et al.  Adapted computational method of energy level and energy quality evolution for combined cooling, heating and power systems with energy storage units , 2017 .

[25]  Russell Bent,et al.  Convex Relaxations for Gas Expansion Planning , 2015, INFORMS J. Comput..

[26]  Jianzhong Wu,et al.  Drivers and State-of-the-art of integrated energy systems in Europe , 2016 .

[27]  George Mavrotas,et al.  Multi-objective optimization and comparison framework for the design of Distributed Energy Systems , 2019, Energy Conversion and Management.

[28]  M. J. Moran,et al.  Fundamentals of Engineering Thermodynamics , 2014 .

[29]  Florian Kienzle,et al.  Valuing Investments in Multi-Energy Conversion, Storage, and Demand-Side Management Systems Under Uncertainty , 2011, IEEE Transactions on Sustainable Energy.

[30]  Chenghui Zhang,et al.  Multi-objective optimal operation and energy coupling analysis of combined cooling and heating system , 2016 .

[31]  Laihong Shen,et al.  A unified correlation for estimating specific chemical exergy of solid and liquid fuels , 2012 .

[32]  Wei Wang,et al.  Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis , 2019, Energy.

[33]  Steven H. Low,et al.  Convex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence , 2014, IEEE Transactions on Control of Network Systems.

[34]  Heejin Cho,et al.  A probability constrained multi-objective optimization model for CCHP system operation decision support , 2014 .

[35]  XinGang Liang,et al.  Entransy—A physical quantity describing heat transfer ability , 2007 .

[36]  Yongming Han,et al.  Review: Multi-objective optimization methods and application in energy saving , 2017 .

[37]  Marc A. Rosen,et al.  Advanced exergy analysis of an air conditioning system incorporating thermal energy storage , 2014 .

[38]  Wei-Jen Lee,et al.  The optimal structure planning and energy management strategies of smart multi energy systems , 2018, Energy.

[39]  T. W. Gedra,et al.  Natural gas and electricity optimal power flow , 2003, 2003 IEEE PES Transmission and Distribution Conference and Exposition (IEEE Cat. No.03CH37495).

[40]  Felix Ziegler,et al.  Absorption cycles. A review with regard to energetic efficiency , 1993 .

[41]  Sunwon Park,et al.  Optimization of a waste heat utilization network in an eco-industrial park , 2010 .

[42]  Jianyong Chen,et al.  5.7 Energy Quality Management , 2018 .