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Optimal power flow incorporating renewable uncertainty related opportunity costs
Computational Intelligence ( IF 2.8 ) Pub Date : 2020-04-01 , DOI: 10.1111/coin.12316
Titipong Samakpong 1 , Weerakorn Ongsakul 1 , Nimal Madhu Manjiparambil 1
Affiliation  

In this paper, an optimal power flow solution method incorporating a cost model that associates the uncertainty-related expense incurred with the use of renewable energy sources, viz., solar and wind, is demonstrated. Wind speed and solar radiation are assumed to follow Weibull and normal distributions and the uncertainty is simulated using Monte-Carlo approach. Wind turbine mathematical model is used to estimate the wind generator output, while the same for solar PV is estimated using PV-inverter models. The uncertainty-induced opportunity cost for both the renewable sources is composed of the costs due to both power excess and deficit. These cost components are indicative of the reserve requirement and loss of benefit, due to the unavailability of the corresponding generation. This research models and integrates the opportunity costs of renewable generation into a conventional OPF formulation, which is then solved using four variants of particle swarm optimization method. Among these, mutation-based PSO approach provided better results than others. The test system used is modified IEEE 39-bus network and the performance of the method as well as the effect of the uncertainty cost is evaluated under multiple renewable penetration levels. The results also indicate that solar generation is preferred over wind in terms of the uncertainty cost, while the use of stochastic natured renewable systems is economically justified and preferred over thermal generators.

中文翻译:

包含可再生不确定性相关机会成本的最优潮流

在本文中,展示了一种包含成本模型的最优潮流求解方法,该模型将与使用可再生能源(即太阳能和风能)相关的不确定性相关费用联系起来。假设风速和太阳辐射服从 Weibull 和正态分布,并使用 Monte-Carlo 方法模拟不确定性。风力涡轮机数学模型用于估计风力发电机的输出,而太阳能光伏则使用光伏逆变器模型进行估计。两种可再生能源的不确定性导致的机会成本由电力过剩和电力不足造成的成本组成。由于相应的发电不可用,这些成本构成表明储备要求和利益损失。该研究对可再生能源发电的机会成本进行建模并将其整合到传统的 OPF 公式​​中,然后使用粒子群优化方法的四种变体来解决该公式。其中,基于突变的 PSO 方法提供了比其他方法更好的结果。所使用的测试系统是修改后的 IEEE 39 总线网络,并在多个可再生渗透水平下评估了该方法的性能以及不确定性成本的影响。结果还表明,就不确定性成本而言,太阳能发电优于风能发电,而使用随机性质的可再生系统在经济上是合理的,并且优于火力发电。基于突变的 PSO 方法提供了比其他方法更好的结果。所使用的测试系统是修改后的 IEEE 39 总线网络,并在多个可再生渗透水平下评估了该方法的性能以及不确定性成本的影响。结果还表明,就不确定性成本而言,太阳能发电优于风能发电,而使用随机性质的可再生系统在经济上是合理的,并且优于火力发电。基于突变的 PSO 方法提供了比其他方法更好的结果。所使用的测试系统是修改后的 IEEE 39 总线网络,并在多个可再生渗透水平下评估了该方法的性能以及不确定性成本的影响。结果还表明,就不确定性成本而言,太阳能发电优于风能发电,而使用随机性质的可再生系统在经济上是合理的,并且优于火力发电。
更新日期:2020-04-01
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