Optimization Of Hybrid Renewable Energy System Using Adaptive Neuro-Fuzzy (Wind And Pv)

ABSTRACT

In recent, electrical power networks a number of failures due to overloading of the transmission lines, stability problems, mismatch in supply and demand, narrow scope for expanding the transmission network and other issues like global warming, environmental conditions, etc. have been noticed. It was stated that Hybrid Power Systems (HPSs) is a promising solution for the shortages of electricity in such situations. However, HPSs are still facing several problems.  These problems are the cost of electrical kilowatt-hour and repetitive breaking in the utility grid with existence varying loads. Besides the problem of non-optimal utilization of available renewable energy resources and the problems associated with the operation  of large generators along small loads, which are the high cost of generation and the minimize in lifetime of the generator. This work is on the study and optimization of hybrid renewable energy of solar and wind using adaptive neuro-fuzzy (ANFIS). A fuzzy control system based on ANFIS has been proposed to optimize the performance of the Hybrid Power Systems. The proposed system has ten ANFIS models, which linked to the outputs of the proposed control system. All models have been trained to achieve the minimum root mean square error (RMSE). The proposed system has been built and simulated using MATLAB.

NOMENCLATURE

 CHAPTER ONE

1.0                                                        INTRODUCTION

1.1                                           BACKGROUND OF THE STUDY

Several developing countries (such as in Nigeria) have still faced a lot of electricity problems. One o of the main problem is the electricity demand growth [Shivarama Krishna, 2014]. In addition, most of the remote and rural areas still out of electricity service [Abdel-Qader, 2008]. In such countries, many of the commercial and educational buildings use traditional power sources as a backup system. Traditional power sources have an acceptable investment cost and they are available with different power capacities. However, the educational buildings have random load demands. The random load demands situation causes a decreasing in the lifetime of traditional generators and an increasing of the running and maintenance cost.

In the recent past interest in distributed generation has increased tremendously due to the cost of fuel, carbon footprint concerns, load demand, and its delivery of clean power, etc.  At present, the electrical power system is facing various problems like network communication, load demand, environmental constraints and limited expansion of lines that influence the sustainability and reliability. These issues have encouraged researchers to utilize solar and wind generation for the reduction of transmission losses, carbon emissions and fuel cost. These sources can be operated either in private or grid-connected modes. The idea of wind and solar associated with a conventional system, though innovative, has caused more difficulties for planners and analysts due to the need to improve voltage stability and sustainability.

In today’s world, the increasing need for energy and the factors, such as increasing energy costs, limited reserves, and environmental pollution, leads the renewable energy to be the most attractive energy source. Since these sources have unlimited supply and they do not cause environmental pollution, they are studied extensively lately and utilized more and more every day.

Renewable energy sources consist of solar energy, wind energy, geothermal energy, and wave energy which are considered to be endless since they exist naturally and they always renew themselves [V. Quasching, 2005]. It is one of the important topics that researchers and scientist work on to obtain energy from these sources and use this energy by transforming it into the form of electrical energy.

Solar and wind energies have a distinguished place among these energy types. There are wind and sun everywhere on earth; therefore, there is more intense study on these sources. The aim is not only to obtain the energy but also to turn the energy to proper values, manage the existent energy, and terminate the harmonics. While managing all these, lowering the cost of the system in every step is taken into consideration. Today, producing electrical energy from these renewable sources appears to be the main objective [V. Quasching, 2005].

The combined operation of these systems is far more complex than operating them separately. In a system with only solar or wind energy, just one element is controlled. In a hybrid scheme, both sources are controlled individually and simultaneously depending upon the operating conditions and energy demand. During low sunlight conditions, photovoltaic (PV) solar panel cannot supply consistent power. Similarly, wind turbine will not work in conditions without wind. In this case, the required energy must have the structure to make up the lack of energy in conditions when this system does not work regularly or the composition produces less energy than the requirement. Power management assures that the system works efficiently while preventing the lack of energy in loads. Here it is aimed at obtaining clean and sustainable energy in stable frequency and definite voltage. While or after obtaining the energy, harmonics must be definitely controlled.

Nowadays renewable energy sources are structured in two ways as grid connected and standalone. Renewable energy sources as solar energy and wind energy can be used to feed loads far from the grid especially the home type ones. However, there are problems in these types of systems when there is no sun or wind. Users become fully powerless after the batteries are flat which are used as backup systems. An alternative situation to this is to connect the loads to the grid if they are close to it, in conditions that there is no sun or wind and the batteries are empty [G. M. Masters, 2004].

Due to capability of good performance with random load demands hybrid power systems, (HPSs) become the best alternate power system for supply random load cases [D. K. Lal, B. B. Dash, 2011]. HPSs usually contain traditional and renewable power sources. However, HPSs still face a lot of shortcomings and difficulties such as:

• The cost and repetitive breaking in the utility grid with existence varying
• Non-optimal utilization of available renewable energy

Researchers are searching for better strategies to utilize the maximum power with the current integrated energy systems. The optimization can achieve an optimum power solution within the predefined conditions.

In the literature, various distributed generation systems like wind, solar, etc. combined with conventional thermal generators are proposed to alleviate many of the concerns. Abaci et al. [2016] clarified the planning of generators considering the monetary criteria, values of shunt capacitors, load tap changers in the OPF outline. Shi et al. [2012] have talked about and reviewed diverse systems utilized with optimum power factor (OPF) under wind power constraints and environmental cost benefits. Sichilalu et al. [2017] have endeavored to consolidate a heat pump-based water heater model which is delivered by wind and a PV solar system considering price minimization and electricity tariff as an objective. Levron et al. [2013] demonstrated control of stored energy to balance the power generation by renewable energy sources. Biswas et al. [2017] have demonstrated some vulnerability of PV and wind, where the constraints are incorporated with conventional generators for the objective function. Reserve cost, penalty cost, and estimated cost of renewable energies are additionally considered for taking care of the optimum power factor issue.

1.2                                                  PROBLEM STATEMENT

The incorporation of renewable energy resources (RERs) into electrical grid is very challenging problem due to their intermittent nature. This paper solves an optimal power flow (OPF) considering wind–solar–storage hybrid generation system. The primary components of the hybrid power system include conventional thermal generators, wind farms and solar photovoltaic modules with batteries. The main critical problem in operating the wind farm or solar PV plant is that these RERs cannot be scheduled in the same manner as conventional generators, because they involve climate factors such as wind velocity and solar irradiation. This paper proposes a new strategy for the optimal power flow problem taking into account the impact of uncertainties in wind and solar PV system.

1.3                                   AIM AND OBJECTIVE OF THE PROJECT

The major aim of the research is to ensure that maximum power is transferred to the grid from the PV and Wind Generating system. At the end of this study the following objectives shall be achieved:

1. The system is going to be integrated
2. Maximum power point tracking System stability

• And system protection is also going to be studied.

1. optimal power flow methods under different constraints condition of renewable energy sources (solar and wind) shall be presented.
2. The current and future applications of optimal power flow programs in smart system planning, operations, sensitivity calculation, and control are presented.

1.4                                      SCOPE OF THE PROJECT

High cost of renewable energy systems has led to its slow adoption in many countries. Hence, it is vital to select an appropriate size of the system in order to reduce the cost and excess energy produced as well as to maximize the available resources. The sizing of hybrid system must satisfy the LPSP (Loss of Power Supply Probability) which determines the ability of the system to meet the load requirements. Once the lowest configurations are determined, the cost of the system must then be taken into consideration to determine the system with the lowest cost. The optimization methodology proposed in this paper uses the ANFIS (Adaptive Neuro-Fuzzy Inference System) to model the PV and wind sources. The algorithm developed is compared to HOMER (Hybrid Optimization Model for Electric Renewables) and HOGA (Hybrid Optimization by Genetic Algorithms) software and the results demonstrate an accuracy of 96% for PV and wind. The optimized system is simulated and the results show that low excess energy is achieved.

1.5                                         SIGNIFICANCE OF THE PROJECT

This work presents a comprehensive study of optimal power flows methods with renewable energy constraints. Additionally, this work presents a progress of optimal power flow solution from its beginning to its present form. This study will help the engineers and researchers to optimize power flow with renewable energy sources (solar and wind).

1.6                                             LIMITATION OF THE STUDY

There are many types of renewable energy sources and many methods of optimization, but this work is limited to studying the optimization of Photovoltaic and wind energy using adaptive neura-fuzzy method.

1.7                                              PURPOSE OF THE PROJECT

Capacity optimization is the key of hybrid renewable power system design and the basis of optimal scheduling. The purpose of optimization is to achieve a Reliable and stable power supply, and to improve energy utilization rate and economic performance for a grid-independent hybrid PV/wind system.

1.8                                                         PROJECT ORGANIZATION

The work is organized as follows: chapter one discuses the introductory part of the work,   chapter two presents the literature review of the study,  chapter three describes the methods applied, chapter four discusses the results of the work, chapter five summarizes the research outcomes and the recommendations.