A New Solar Assisted Heat Pump System with Underground Energy Storage: Modelling and Optimisation

被引:14
作者
Oclon, Pawel [1 ]
Lawrynczuk, Maciej [2 ]
Czamara, Marek [3 ]
机构
[1] Cracow Univ Technol, Fac Mech Engn, Inst Thermal Power Engn, Al Jana Pawla II 37, PL-31864 Krakow, Poland
[2] Warsaw Univ Technol, Fac Elect & Informat Technol, Inst Control & Computat Engn, Ul Nowowiejska 15-19, PL-00665 Warsaw, Poland
[3] Czamara Urzadzenia Chlodnicze Co, Ul Ceglarska 27, PL-34600 Limanowa, Poland
关键词
renewable energy; photovoltaic panel; heat pumps; optimisation; heuristic optimisation;
D O I
10.3390/en14165137
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The objectives of this work are: (a) to present a new system for building heating which is based on underground energy storage, (b) to develop a mathematical model of the system, and (c) to optimise the energy performance of the system. The system includes Photovoltaic Thermal Hybrid Solar Panels (PVT) panels with cooling, an evacuated solar collector and a water-to-water heat pump. Additionally, storage tanks, placed underground, are used to store the waste heat from PVT panels cooling. The thermal energy produced by the solar collectors is used for both domestic hot water preparation and thermal energy storage. Both PVT panels and solar collectors are assembled with a sun-tracking system to achieve the highest possible solar energy gain. Optimisation of the proposed system is considered to achieve the highest Renewable Energy Sources (RES) share during the heating period. Because the resulting optimisation problem is nonlinear, the classical gradient-based optimisation algorithm gives solutions that are not satisfying. As alternatives, three heuristic global optimisation methods are considered: the Genetic Algorithm (GA), the Particle Swarm Optimisation (PSO) algorithm, and the Jaya algorithm. It is shown that the Jaya algorithm outperforms the GA and PSO methods. The most significant result is that 93% of thermal energy is covered by using the underground energy storage unit consisting of two tanks.
引用
收藏
页数:15
相关论文
共 32 条
[1]   Life-Cycle Cost Minimization of Gas Turbine Power Cycles for Distributed Power Generation Using Sequential Quadratic Programming Method [J].
Aji, Satriya Sulistiyo ;
Kim, Young Sang ;
Ahn, Kook Young ;
Lee, Young Duk .
ENERGIES, 2018, 11 (12)
[2]   Developing Induction Motor State Observers with Increased Robustness [J].
Bialon, Tadeusz ;
Pasko, Marian ;
Niestroj, Roman .
ENERGIES, 2020, 13 (20)
[3]   Proton Exchange Membrane Fuel Cell Stack Design Optimization Using an Improved Jaya Algorithm [J].
Chakraborty, Uday K. .
ENERGIES, 2019, 12 (16)
[4]   Hybrid Adaptive Control for PEMFC Gas Pressure [J].
Chen, Jing ;
Zhang, Chenghui ;
Li, Ke ;
Zhan, Yuedong ;
Sun, Bo .
ENERGIES, 2020, 13 (20)
[5]   Experimental performance analysis of a solar assisted ground source heat pump system under different heating operation modes [J].
Dai, Lanhua ;
Li, Sufen ;
Lin DuanMu ;
Li, Xiangli ;
Shang, Yan ;
Dong, Ming .
APPLIED THERMAL ENGINEERING, 2015, 75 :325-333
[6]   A Mixed-Strategy-Based Whale Optimization Algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect [J].
Ding, Tan ;
Chang, Li ;
Li, Chaoshun ;
Feng, Chen ;
Zhang, Nan .
ENERGIES, 2018, 11 (09)
[7]   A simplified ground thermal response model for analyzing solar-assisted ground source heat pump systems [J].
Fine, Jamie P. ;
Nguyen, Hiep V. ;
Friedman, Jacob ;
Leong, Wey H. ;
Dworkin, Seth B. .
ENERGY CONVERSION AND MANAGEMENT, 2018, 165 :276-290
[8]  
Golberg DE., 1989, GENETIC ALGORITHMS S, P36
[9]  
Kennedy J., 1995, 1995 IEEE International Conference on Neural Networks Proceedings (Cat. No.95CH35828), P1942, DOI 10.1109/ICNN.1995.488968
[10]   Optimal Siting and Sizing of Wayside Energy Storage Systems in a DC Railway Line [J].
Lamedica, Regina ;
Ruvio, Alessandro ;
Palagi, Laura ;
Mortelliti, Nicola .
ENERGIES, 2020, 13 (23)