Network Reliability Analysis as a Tool to Guide Investment Decisions in Distributed Generation

• 作者: Jonathan Serugunda Milton Edimu Patrick Kabanda Samson Ttondo Ssemakalu
• 来源期刊: 电力能源(英文)
• 学科: 医学
• 关键词: DETERMINISTIC METHODS Distributed Generation Network RELIABILITY RELIABILITY ANALYSIS STOCHASTIC METHODS
• 年，卷（期）: 2018,（9）
• 页码范围: 64-84
• 页数: 21页
• 分类号: R73

摘要

Distributed Generation (DG) in any quantity is relevant to supplement the available energy capacity based on various locations, that is, whether a site specific or non-site specific energy technology. The evacuation infrastructure that delivers power to the distribution grid is designed with appropriate capacity in terms of size and length. The evacuation lines and distribution network however behave differently as they possess inherent characteristics and are exposed to varying external conditions. It is thus feasible to expect that these networks behave stochastically due to fault conditions and variable loads that destabilize the system. This in essence impacts on the availability of the evacuation infrastructure and consequently on the amount of energy delivered to the grid from the DG stations. Reliability of the evacuation point of a DG is however not a common or prioritized criteria in the decision process that guides investment in DG. This paper reviews a planned solar based DG plant in Uganda. Over the last couple of years, Uganda has seen a significant increase in the penetration levels of DG. With a network that is predominantly radial and experiences low reliability levels, one would thus expect reliability analysis to feature significantly in the assessment of the proposed DG plants. This is however not the case. This paper, uses reliability analysis to assess the impact of different evacuation options of the proposed DG plant on its dispatch levels. The evacuation options were selected based on infrastructure options in other locations with similar solar irradiances as the planned DG location. Outage data were collected and analyzed using the chi square method. It was found to be variable and fitting to different Probability Distribution Functions (PDF). Using stochastic methods, a model that incorporates the PDFs was developed to compute the reliability indices. These were assessed using chi square and found to be variable and fitting different PDFs as well. The viability of the project is reviewed