﻿ 基于最小偏差法的全球能源优化配置方法
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 山东大学学报(工学版)  2017, Vol. 47 Issue (6): 128-133  DOI: 10.6040/j.issn.1672-3961.0.2017.579 0

### 引用本文

ZHANG Hengxu, HAN Linxiao, SHI Fang. Optimal allocation of global energy based on minimum deviation method[J]. Journal of Shandong University (Engineering Science), 2017, 47(6): 128-133. DOI: 10.6040/j.issn.1672-3961.0.2017.579.

### 文章历史

Optimal allocation of global energy based on minimum deviation method
ZHANG Hengxu, HAN Linxiao, SHI Fang
Collaborative Innovation Center for Global Energy Interconnection (Shandong University), Jinan 250061, Shandong, China
Abstract: Global energy interconnection dedicated to form a new pattern of world energy development in which clean energy plays dominating role, the electric power was the center and the energy resources are optimally allocated worldwide. It will become the strong support to achieve sustainable development of society and economy in the future. To study the energy allocation in the background of global energy interconnection, a multi-objective optimization model was established. In this model, minimizing energy cost and minimizing transmission loss were objectives. Restrictions included energy supply, energy demand and capacity of transmission system. In order to reduce the influence of subjectivity on multi-objective optimization, the model was transformed into single-objective optimization model based on minimum deviation method and solved by GAMS software. The case study showed that electricity replacement could effectively reduce total energy cost. Based on this, the optimal allocation scheme of global energy under transcontinental grids was compared and analyzed, and its sensitivity on environmental benefits was discussed.
Key words: global energy interconnection    optimal allocation    minimum deviation method    ultra-high voltage    clean energy
0 引言

1 全球能源优化配置模型 1.1 全球能源配置影响因素

1.2 多目标优化模型 1.2.1 目标函数

 $\min F = \min \left( {{f_1}(x), {\rm{ }}{f_2}(x)} \right),$ (1)
 ${f_1}(x) = \sum\limits_k {{a_k}(i, j) \cdot {x_k}(i, j)},$ (2)
 ${f_2}(x) = \sum\limits_k {{b_k}(i, j) \cdot {x_k}(i, j)},$ (3)

1.2.2 约束条件

(1) 运输系统容量约束

 ${r_{k, \min }}(i, j) \leqslant {x_k}(i, j) \leqslant {r_{k, \max }}(i, j),$ (4)

(2) 能源可供给量约束

 $\sum\limits_j {{x_k}(i, j) \leqslant p(i)},$ (5)

(3) 能源需求量约束

 $\sum\limits_i {{x_k}(i, j) \geqslant q(j)},$ (6)

2 基于最小偏差法的优化方法 2.1 最小偏差法

 ${F_m} = \left( {{f_{m, 1}}(x), {f_{m, 2}}(x), \cdots, {f_{m, n}}(x)} \right),$ (7)

 $\min F_m^s = \sum\limits_{k = 0}^l {\frac{{{f_{m, k}}(x) - f_{m, k}^{\min }}}{{f_{m, k}^{\max } - f_{m, k}^{\min }}}} + \sum\limits_{k = l + 1}^n {\frac{{f_{m, k}^{\max } - {f_{m, k}}(x)}}{{f_{m, k}^{\max } - f_{m, k}^{\min }}}},$ (8)

2.2 全球能源优化配置方法

 $\min {\rm{ }}{F^s}{\rm{ = }}\frac{{{f_1}(x) - f_1^{\min }}}{{f_1^{\max } - f_1^{\min }}} + \frac{{{f_2}(x) - f_2^{\min }}}{{f_2^{\max } - f_2^{\min }}},$ (9)

 $\begin{array}{*{20}{l}} {\min {F^s}}\\ {{\rm{s}}{\rm{.t}}{\rm{.}}\left\{ \begin{array}{l} \sum\limits_j {{x_k}(i, j) \leqslant p(i), } \\ \sum\limits_i {{x_k}(i, j) \geqslant q(j), } \\ {r_{k, \min }}(i, j) \leqslant {x_k}(i, j) \leqslant {r_{k, \max }}(i, j), \end{array} \right.} \end{array}$ (10)

3 算例分析 3.1 传统模式下的全球能源优化配置

 图 1 优化配置后的全球化石能源流通情况 Figure 1 Global fossil energy flows after optimal allocation
3.2 洲际互联模式下的全球能源优化配置

 图 2 优化配置后的全球能源流通情况 Figure 2 Global energy flows after optimal allocation

3.3 环境效益影响分析

4 结语

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