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Capacity Optimization Configuration of Wind/PV/Hydrogen Multi-Energy Complementary System
DOI: 10.12677/MOS.2024.131055, PDF, HTML, XML, 下载: 158  浏览: 281

Abstract: In order to solve the problem of wind and solar energy abandonment caused by intermittence and randomness, this paper introduces a wind/PV/hydrogen multi-energy complementary system. Reasonable capacity allocation is the key to solve the economy and ensure the stability of solar power generation, so this paper establishes a solar hydrogen power generation model considering hydrogen storage capacity. With the minimum deviation between system output power and user load as the objective function and the safe operating boundary of each device as the constraint, ge-netic algorithm is used to seek the optimal configuration. In order to verify the effectiveness, com-bined with the historical data of the wind/PV complementary project, the optimal capacity scheme of the energy storage device was solved according to the actual local weather data and user load data, and the energy and economic analysis of the system was carried out to ensure the feasibility of the system. The results show that the optimal energy storage configuration is composed of 132.62 MW electrolyser, 49.68 MW fuel cell and 1100.75 km3 hydrogen storage tank. The payback life of the system under this configuration is 4.6 years, and the energy growth rate is 24.72%.

1. 引言

2. 风–光–氢综合能源系统

3. 模型建立

3.1. 风力发电系统

Figure 1. Structural diagram of wind-solar-hydrogen multi-energy integrated system

Figure 2. Operating strategy of the proposed system

${P}_{w}=\left\{\begin{array}{l}0,\text{\hspace{0.17em}}\text{\hspace{0.17em}}v<{v}_{in}\text{\hspace{0.17em}}\text{ }\text{or}\text{\hspace{0.17em}}\text{ }v>{v}_{out}\\ {P}_{wr}\frac{v-{v}_{in}}{{v}_{out}-{v}_{in}},\text{\hspace{0.17em}}\text{\hspace{0.17em}}{v}_{in} (1)

${v}_{h}={v}_{{h}_{0}}{\left(\frac{h}{{h}_{0}}\right)}^{\frac{1}{7}}$ (2)

Table 1. Parameters of the wind turbine

3.2. 光伏发电模型

${P}_{p}=\alpha {P}_{pr}\frac{A}{{A}_{0}}\left[1+{k}_{p}\left({T}_{p}-{T}_{pr}\right)\right]$ (3)

Table 2. Parameters of the PV panel

3.3. 储氢系统

${\text{H}}_{\text{2}}\text{O}\to 2{\text{H}}^{+}+\frac{1}{2}{\text{O}}_{2}+2{\text{e}}^{-}$

$2{\text{H}}^{+}+2{\text{e}}^{-}={\text{H}}_{2}$

${\text{H}}_{2}=2{\text{H}}^{+}+2\text{e}$

$2{\text{H}}^{+}+\frac{1}{2}{\text{O}}_{2}+2{\text{e}}^{-}={\text{H}}_{\text{2}}\text{O}$

$\text{SOC}\left(t\right)=\text{SOC}\left(t-1\right)+{\eta }_{E}\left({P}_{T}\left(t\right)-{P}_{load}\left(t\right)\right)\rho$ (4)

$\text{SOC}\left(t\right)=\text{SOC}\left(t-1\right)+{\eta }_{FC}\left({P}_{T}\left(t\right)-{P}_{load}\left(t\right)\right)\sigma$ (5)

Table 3. Parameters of hydrogen storage system

4. 系统优化

4.1. 目标函数

$f=\mathrm{min}\left(\frac{\sqrt{{\sum }_{t=1}^{N}{\left({P}_{T}\left(t\right)-{P}_{load}\left(t\right)\right)}^{2}}}{N}\right)$ (6)

${P}_{T}\left(t\right)={P}_{w}\left(t\right)+{P}_{p}\left(t\right)+{P}_{{H}_{2}}\left(t\right)$ (7)

4.2. 约束条件

1) 风力发电输出功率约束

${P}_{w}\left(\mathrm{min}\right)\le {P}_{w}\left(t\right)\le {P}_{w}\left(\mathrm{max}\right)$ (8)

2) 光伏发电输出功率约束

${P}_{p}\left(\mathrm{min}\right)\le {P}_{p}\left(t\right)\le {P}_{p}\left(\mathrm{max}\right)$ (9)

3) 电解槽制氢约束

${q}_{{H}_{2}}\left(\mathrm{min}\right)\le {q}_{{H}_{2}}\left(t\right)\le {q}_{{H}_{2}}\left(\mathrm{max}\right)$ (10)

4) 储氢罐容量约束

${V}_{{H}_{2}}\left(\mathrm{min}\right)\le {V}_{{H}_{2}}\left(t\right)\le {V}_{{H}_{2}}\left(\mathrm{max}\right)$ (11)

5) 燃料电池容量约束

$E\left(\mathrm{min}\right)\le E\left(t\right)\le E\left(\mathrm{max}\right)$ (12)

6) 燃料电池充放电约束。

${P}_{c}\left(\mathrm{min}\right)\le {P}_{c}\left(t\right)\le {P}_{c}\left(\mathrm{max}\right)$ (13)

${P}_{d}\left(\mathrm{min}\right)\le {P}_{d}\left(t\right)\le {P}_{d}\left(\mathrm{max}\right)$ (14)

7) 能量平衡约束

$E\left(t-1\right)+{P}_{c}\left(t\right)\Delta t=E\left(t\right)$ (15)

$E\left(t-1\right)-{P}_{d}\left(t\right)\Delta t=E\left(t\right)$ (16)

${P}_{w}\left(t\right)+{P}_{p}\left(t\right)+{P}_{{H}_{2}}\left(t\right)+{P}_{g}\left(t\right)={P}_{load}\left(t\right)$ (17)

4.3. 评价指标

$\eta =\frac{\sum {P}_{{H}_{2}}\left(t\right)}{\sum {P}_{w}\left(t\right)+\sum {P}_{p}\left(t\right)}$ (18)

$\text{NPV}=\underset{i}{\overset{m}{\sum }}\frac{{\left(\text{NCF}\right)}^{m}}{{\left(1+i\right)}^{m}}-\sum {C}_{i}$ (19)

$\text{NCF}={C}_{{H}_{2}}-{C}_{OM}$ (20)

5. 案例分析数据

Table 4. Four extreme weather conditions

Figure 3. The wind velocity and solar radiation intensity of the selected weather

6. 结果与讨论

6.1. 四种极端情况对比

Figure 4. Daily running status of the system in four cases

Table 5. The optimal configuration of hydrogen storage system in four cases

6.2. 综合四种极端情况分析

Figure 5. Comprehensive analysis of four cases

6.3. 能源和经济分析

Table 6. Equipment cost

Figure 6. NPV of system in five cases

7. 结论

1) 与常规发电系统相比，配备储能系统在四种天气情况下均有显著优势，最优配置方案可提高24.72%的能源增长率。该配置由390 MW风力发电机组、310 MW光伏发电机组、132.62 MW电解槽、49.68 MW燃料电池和1100.75 km3储氢罐组成。

2) 对系统进行经济性分析，在最优配置下，系统的投资回收年限为4.6年，NPV为2.38亿元，在保证经济性的同时提高了系统的能源利用率和供电可靠性，满足可持续发展理念。

3) 但本文在数据选择方面，只选取了典型的天气条件进行分析，没有基于全年数据求解最佳储氢容量，存在一定的不准确性，未来的工作中将基于更多的实际数据进行分析预测，减少系统不确定性。

NOTES

*第一作者。

#通讯作者。

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