关键词: Distribution system GHG emissions Grid-connected Power losses Voltage deviation

来  源:   DOI:10.1038/s41598-024-61413-8   PDF(Pubmed)

Abstract:
Economic development relies on access to electrical energy, which is crucial for society\'s growth. However, power shortages are challenging due to non-renewable energy depletion, unregulated use, and a lack of new energy sources. Ethiopia\'s Debre Markos distribution network experiences over 800 h of power outages annually, causing financial losses and resource waste on diesel generators (DGs) for backup use. To tackle these concerns, the present study suggests a hybrid power generation system, which combines solar and biogas resources, and integrates Superconducting Magnetic Energy Storage (SMES) and Pumped Hydro Energy Storage (PHES) technologies into the system. The study also thoroughly analyzes the current and anticipated demand connected to the distribution network using a backward/forward sweep load flow analysis method. The results indicate that the total power loss has reached its absolute maximum, and the voltage profiles of the networks have dropped below the minimal numerical values recommended by the Institute of Electrical and Electronics Engineers (IEEE) standards (i.e., 0.95-1.025 p.u.). After reviewing the current distribution network\'s operation, additional steps were taken to improve its effectiveness, using metaheuristic optimization techniques to account for various objective functions and constraints. In the results section, it is demonstrated that the whale optimization algorithm (WOA) outperforms other metaheuristic optimization techniques across three important objective functions: financial, reliability, and greenhouse gas (GHG) emissions. This comparison is based on the capability of the natural selection whale optimization algorithm (NSWOA) to achieve the best possible values for four significant metrics: Cost of Energy (COE), Net Present Cost (NPC), Loss of Power Supply Probability (LPSP), and GHG Emissions. The NSWOA achieved optimal values for these metrics, namely 0.0812 €/kWh, 3.0017 × 106 €, 0.00875, and 7.3679 × 106 kg reduced, respectively. This is attributable to their thorough economic, reliability, and environmental evaluation. Finally, the forward/backward sweep load flow analysis employed during the proposed system\'s integration significantly reduced the impact of new energy resources on the distribution network. This was evident in the reduction of total power losses from 470.78 to 18.54 kW and voltage deviation from 6.95 to 0.35 p.u., as well as the voltage profile of the distribution system being swung between 1 and 1.0234 p.u., which now comply with the standards set by the IEEE. Besides, a comparison of the cost and GHG emission efficiency of the proposed hybrid system with existing (grid + DGs) and alternative (only DGs) scenarios was done. The findings showed that, among the scenarios examined, the proposed system is the most economical and produces the least amount of GHG emissions.
摘要:
经济发展有赖于获得电能,这对社会的发展至关重要。然而,由于不可再生能源的枯竭,电力短缺具有挑战性,不受管制的使用,缺乏新能源。埃塞俄比亚的DebreMarkos分销网络每年经历超过800小时的停电,对备用柴油发电机(DG)造成财务损失和资源浪费。为了解决这些问题,本研究提出了一种混合发电系统,结合了太阳能和沼气资源,并将超导磁储能(SMES)和抽水储能(PHES)技术集成到系统中。该研究还使用后向/前向扫描潮流分析方法彻底分析了连接到配电网的当前和预期需求。结果表明,总功率损耗已达到其绝对最大值,并且网络的电压曲线已降至电气和电子工程师协会(IEEE)标准建议的最小数值以下(即,0.95-1.025p.u.)。在审查了当前配电网的运行情况后,采取了其他措施来提高其有效性,使用元启发式优化技术来考虑各种目标函数和约束。在结果部分,证明了鲸鱼优化算法(WOA)在三个重要目标函数上优于其他元启发式优化技术:财务,可靠性,温室气体(GHG)排放。此比较基于自然选择鲸鱼优化算法(NSWOA)的能力,以实现四个重要指标的最佳可能值:能源成本(COE),净现值成本(NPC),断电概率(LPSP)和温室气体排放。NSWOA实现了这些指标的最佳值,即0.0812€/kWh,3.0017×106€,0.00875,减少7.3679×106公斤,分别。这是由于他们彻底的经济,可靠性,和环境评价。最后,在提出的系统集成过程中采用的前向/后向扫描负荷流分析显著降低了新能源对配电网的影响。这在总功率损耗从470.78减少到18.54kW和电压偏差从6.95减少到0.35p.u.以及配电系统的电压曲线在1到1.0234p.u.之间摆动,现在符合IEEE设定的标准。此外,对拟议的混合动力系统与现有(电网+DG)和替代(仅DG)方案的成本和GHG排放效率进行了比较。调查结果显示,在所检查的场景中,拟议的系统是最经济的,产生的温室气体排放量最少。
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