An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming

被引:109
|
作者
Moradi, Mohammad H. [1 ]
Hajinazari, Mehdi [1 ]
Jamasb, Shahriar [2 ]
Paripour, Mahmoud [3 ]
机构
[1] Bu Ali Sina Univ, Fac Engn, Dept Elect Engn, Hamadan, Iran
[2] Hamedan Univ Technol, Dept Biomed Engn, Hamadan 65155, Iran
[3] Hamedan Univ Technol, Dept Sci, Hamadan 65155, Iran
关键词
Energy management system; Fuzzy set theory; Hybrid optimization method; Net present value; GREENHOUSE-GAS EMISSIONS; TRIGENERATION SYSTEMS; DISTRIBUTED GENERATION; COGENERATION SYSTEMS; OPERATION; MODEL; ALGORITHM; DISPATCH; LOAD; PERFORMANCE;
D O I
10.1016/j.energy.2012.10.005
中图分类号
O414.1 [热力学];
学科分类号
摘要
An optimization method, which considers the Combined Heat and Power (CHP) model under uncertainty, has been developed to determine the optimal capacities for the CHP and boiler such that thermal and electrical energy demands can be satisfied with high cost efficiency. The proposed method offers an energy management system (EMS) strategy which employs the fuzzy set theory to account for the uncertainties associated with electrical and thermal energy demands as well as those associated with natural gas and electrical power prices in order to determine the optimum ranges for boiler and CUP capacities which maximize an objective function based on the net present value (NPV). The reduction in operational strategy expenses arising from the monetary cost of the credit attainable by air pollution reduction is also taken into account in evaluation of the objective function. The optimal range for boiler and CHP capacities and the resulting projection for the range of optimal value of the objective function are derived using a hybrid optimization method involving the particle swarm optimization (PSO) and the linear programming algorithms. The viability of the proposed method is demonstrated by analyzing the decision to construct a CHP system for a typical hospital. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:86 / 101
页数:16
相关论文
共 50 条
  • [1] New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power
    Zeng, Xiangyu
    Berti, Stephen
    COMPUTATIONAL INTELLIGENCE, 2020, 36 (01) : 55 - 79
  • [2] Integration strategy optimization of solar-aided combined heat and power (CHP) system
    Wu, Junjie
    Han, Yu
    ENERGY, 2023, 263
  • [3] On Power Following Energy Management Strategy Based on Fuzzy Optimization
    Wang Xu-Feng
    Peng Fei
    Mao Bo-Bo
    Chen Wei-Rong
    2011 30TH CHINESE CONTROL CONFERENCE (CCC), 2011, : 5073 - 5077
  • [4] An energy management strategy for supplying combined heat and power by the fuel cell thermoelectric hybrid system
    Kwan, Trevor Hocksun
    Shen, Yongting
    Yao, Qinghe
    APPLIED ENERGY, 2019, 251
  • [5] Thermal optimization of combined heat and power (CHP) systems using nanofluids
    Kazemi-Beydokhti, Amin
    Heris, Saeed Zeinali
    ENERGY, 2012, 44 (01) : 241 - 247
  • [6] Optimization of a fuzzy based energy management strategy for a PV/WT/FC hybrid renewable system
    Mohamadian, Mustafa (mohamadian@modares.ac.ir), 1686, International Journal of Renewable Energy Research (07):
  • [7] Evaluation of Combined Heat and Power (CHP) Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS
    Cavallaro, Fausto
    Zavadskas, Edmundas Kazimieras
    Raslanas, Saulius
    SUSTAINABILITY, 2016, 8 (06)
  • [8] Energy management strategy based on CEEMDAN and fuzzy logic control for hybrid power system of ship
    Yang, Yicong
    Pan, Lin
    Wang, Jiying
    Deng, Zhenxing
    2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2023, : 1970 - 1975
  • [9] SOC Optimization Based Energy Management Strategy for Hybrid Energy Storage System in Vessel Integrated Power System
    Gao, Xueping
    Fu, Lijun
    IEEE ACCESS, 2020, 8 : 54611 - 54619
  • [10] Optimization strategy of a rural combined heat and power system considering biomass energy
    Guo, Wei
    Yang, Peng
    Sun, Shengbo
    Li, Huan
    Wang, Xiaotian
    Zhang, Xiuli
    Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2021, 49 (11): : 88 - 96