Long-term Generation Expansion Planning including renewable energy sources considering uncertainties in restructured environment

Alizadeh, Vahid (2018) Long-term Generation Expansion Planning including renewable energy sources considering uncertainties in restructured environment. Masters thesis, University of Mohaghegh Ardabili.

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Text (برنامه ریزی بلند مدت توسعه تولید در حضور منابع انرژی تجدیدپذیر با در نظرگرفتن عدم قطعیت ها در محیط تجدید ساختار یافته) Vahid Alizadeh.pdf Download (541kB) | Preview

Abstract

In this thesis, the problem of long-term generation expansion planning of electrical energy in the presence of renewable energy sources with regard to uncertainty in forecasted load, availability of system components, as well as uncertainty in the output power of renewable energy units and electricity prices in restructured environment of the electricity industry have been addressed. In addition to optimizing the total investment costs, operation and maintenance costs of power units, maximizing the profit function in a competitive environment and reducing environmental pollution during the planning period, the system will have the ability to respond to the increasing demand for energy in a stable and reliable situation. In order to achieve the above mentioned objectives, the initial investment cost and the cost of maintenance, operation and salvage cost of electricity generation units in the first stage, and the environmental and economic indices in the second phase are considered as objective functions. The limitations of reliability, pollution, economic, maximum development units and reserve capacity are considered as constraints. Among renewable energy sources, wind and solar units are considered in the GEP with regard to their generation uncertainty. Also, to optimize the problem, a dragonfly multi-objective algorithm (MODA) has been used. After optimizing the objective functions, a fuzzy decision method is used to select the best particle. Proposed methods have been tested on the IEEE 24 bus system and are finally analyzed based on various indicators. The evaluation of the simulation results revealed the necessity of modeling the uncertainties in the GEP problem and it is clear that the entry of uncertainties and constraints in the GEP problem in the restructured environment increases the initial cost But in the long run, it reduces operating costs and also increases the profit function compared to the traditional one. Also, due to the increase in unit capacity, the reliability index of the system increases significantly

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