Abstract

Nowadays, renewable energy resources play an important role in replacing conventional energy resources such as fossil fuel by integrating solar, wind and geothermal energy. Photovoltaic energy is one of the very promising renewable energy resources which grew rapidly in the past few years, it can be used to produce electric energy through photovoltaic process. The primary objective of the research proposed in this paper is to facilitate the increasing penetration levels of PV systems in the electric distribution networks. In this work, the PV module electrical model is presented based on the mathematical equations and was implemented on MATLAB to simulate the non-linear characteristics I-V and P-V curves with variable input parameters which are irradiance and temperature based on Riyadh region. In addition, the reliability evaluation of distribution networks, including distributed generators of solar photovoltaic (PV) with varying output power capacity is presented also. The Monte Carlo simulation algorithm is applied to test the distribution network which is RBTS Bus 2 and the same has been conducted on the original case of distribution network substation 7029 which is located at KSA Riyadh. The two distribution networks have been modified to include the PV’s distributed generators. The distributed generators contribute to supply a part of the load during normal mode and supply the entire load during component failure or failure of grid operation supply. The PV stochastic models have been used to simulate the randomness of these resources. Moreover, the study shows that the implementation and integration of renewable resources as distributed generations have improved the reliability of the distribution networks.

Highlights

  • The electric power system has been used to generate, transmit and distribute power since the advent of electricity evolution and the foremost important objective of an electrical utility is to deliver economical, reliable, and quality power to its consumer

  • The Monte Carlo simulation algorithm is applied to test the distribution network which is RBTS Bus 2 and the same has been conducted on the original case of distribution network substation 7029 which is located at Kingdom of Saudi Arabia (KSA) Riyadh

  • As the main purpose of this study is to evaluate the reliability of MV network system with renewable energy resource which is the PV distributed generation with vary output power capacity to see their impact on the reliability, the following assumptions were created that shouldn't have a major impact on the results: 1) The permanent faults only are included in the study and all protection devices operate with success to isolate the faults

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Summary

Introduction

The electric power system has been used to generate, transmit and distribute power since the advent of electricity evolution and the foremost important objective of an electrical utility is to deliver economical, reliable, and quality power to its consumer. The electrical power network is extremely complex, a failure may result in loss of power to a large number of customers or sometimes catastrophic events such as blackouts and it is difficult to analyze the entire system at once For this reason, the power system is divided into three functional zones such as generation facility, transmission facility and distribution facility to evaluate the reliability of the system. Hierarchical level III includes all of the three functional zones and refers to the complete electric power system It deals with the reliability evaluation of the generation, transmission and distribution systems. In recent years there has been an increase in the global trend in general and particular in Kingdom of Saudi Arabia (KSA) towards finding and exploiting sources of renewable energy to generate electricity. The King Abdullah City for Atomic and Renewable Energy (KACARE) program seeks to ensure that half of the electricity generated in Saudi Arabia comes from renewable sources by 2032 [8]

Solar Radiation
DG Model
Load Model
System Reliability Indices
Monte Carlo Simulation
Case Study Application
Findings
Conclusions

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