scholarly journals A fuzzy‐based multi‐objective robust optimization model for a regional hybrid energy system considering uncertainty

2020 ◽  
Vol 8 (4) ◽  
pp. 926-943 ◽  
Author(s):  
Xueying Song ◽  
Rui Zhao ◽  
Gejirifu De ◽  
Jing Wu ◽  
Huayu Shen ◽  
...  
Keyword(s):  
Robust Optimization ◽  
Optimization Model ◽  
Energy System ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
Multi Objective

scholarly journals A Short-Term Hybrid Energy System Robust Optimization Model for Regional Electric-Power Capacity Development Planning under Different Pollutant Control Pressures

2021 ◽  
Vol 13 (20) ◽  
pp. 11341
Author(s):  
Jixian Cui ◽  
Chenghao Liao ◽  
Ling Ji ◽  
Yulei Xie ◽  
Yangping Yu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Robust Optimization ◽  
Electric Power ◽  
Optimization Model ◽  
Energy System ◽  
Short Term ◽  
System Planning ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
Energy System Planning

This paper is aimed at proposing a short-term hybrid energy system robust optimization model for regional energy system planning and air pollution mitigation based on the inexact multi-stage stochastic integer programming and conditional value-at-risk method through a case study in Shandong Province, China. Six power conversion technologies (i.e., coal-fired power, hydropower, photovoltaic power, wind power, biomass power, and nuclear power) and power demand sectors (agriculture, industry, building industry, transportation, business, and residential department) were considered in the proposed model. The optimized electricity generation, capacity expansion schemes, and economic risks were selected to analyze nine defined scenarios. Results revealed that electricity generations of clean and new power had obvious increasing risks and were key considerations of establishing additional capacities to meet the rising social demands. Moreover, the levels of pollutants mitigation and risk-aversion had a significant influence on different power generation schemes and on the total system cost. In addition, the optimization method developed in this paper could effectively address uncertainties expressed as probability distributions and interval values, and could avoid the system risk in energy system planning problems. The proposed optimization model could be valuable for supporting the adjustment or justification of air pollution mitigation management and electric power planning schemes in Shandong, as well as in other regions of China.

scholarly journals Optimal Sizing of an Island Hybrid Microgrid Based on Improved Multi-Objective Grey Wolf Optimizer

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1581
Author(s):  
Wenqiang Zhu ◽  
Jiang Guo ◽  
Guo Zhao ◽  
Bing Zeng
Keyword(s):  
Power Supply ◽  
Tidal Current ◽  
System Optimization ◽  
Energy System ◽  
Energy Sources ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
Multi Objective

The hybrid renewable energy system is a promising and significant technology for clean and sustainable island power supply. Among the abundant ocean energy sources, tidal current energy appears to be very valuable due to its excellent predictability and stability, particularly compared with the intermittent wind and solar energy. In this paper, an island hybrid energy microgrid composed of photovoltaic, wind, tidal current, battery and diesel is constructed according to the actual energy sources. A sizing optimization method based on improved multi-objective grey wolf optimizer (IMOGWO) is presented to optimize the hybrid energy system. The proposed method is applied to determine the optimal system size, which is a multi-objective problem including the minimization of annualized cost of system (CACS) and deficiency of power supply probability (DPSP). MATLAB software is utilized to program and simulate the hybrid energy system. Optimization results confirm that IMOGWO is feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. Furthermore, comparison of hybrid systems with and without tidal current turbines is undertaken to confirm that the utilization of tidal current turbines can contribute to enhancing system reliability and reducing system investment, especially in areas with abundant tidal energy sources.

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