Application of diesel generators to supply the load demand on isolated islands in Indonesia has widely spread. With increases in oil price and the concerns about global warming, the integration of ...diesel generators with renewable energy systems have become an attractive energy sources for supplying the load demand. This paper performs an optimal design of integrated system involving Wind-PV-Diesel-Battery system for isolated island with CO2 emission evaluation by using genetic algorithm. The proposed system has been designed for the hybrid power generation in East Nusa Tenggara, Indonesia-latitude 09.30S, longitude 122.0E. From simulation results, the proposed system is able to minimize the total annual cost of the system under study and reduce CO2 emission generated by diesel generators.
This paper presents an application of Gaussian Processes (GPs) for forecasting electrical energy consumption, a case study is considered, which is the main campus of Assiut University located in ...Assiut city in the middle of Egypt. GPs are a tool that can handle uncertainties in prediction. The study carried out here incorporates the effect of several variables on the prediction process, which constitute the inputs to a GP model. We consider three significant factors affecting the energy consumption including weather conditions, schedules related to work and human activities, and occupancy. Each factor is further divided into a number of time-dependent variables that are used as the inputs to the GP model, which infers the energy consumption per month. Based on historical data of these variables, the hyper parameters of the GP model are optimized offline and the resulted model is tested for 12-month-ahead prediction. In order to enhance the GP forecasting model, a nonlinear autoregressive (NAR) model based on neural networks is used to predict the future values of the inputs in order to use the GP model for prediction. Different types of the GP kernels are examined. The performance of the GP models with the different kernels is validated using different validation criteria and compared with a feed-forward neural network for predicting the electrical energy consumption. This work leads to the best forecasting accuracy results in mean absolute percentage error (MAPE) of about 5 % during a whole year using GP approach.
This paper presents a digital model of decentralized Load Frequency Control (LFC) using an optimal PID controller-based Particle Swarm Optimization (PSO) in Egyptian Power System (EPS) considering ...communication delays. The EPS includes both conventional generation units (i.e., non-reheat, reheat, and hydraulic power plants) with inherent non-linearities and wind power, which extracted from Zafarana wind farm, location in Egypt. Thus, the optimal digital controller-based Tustin’s technique is designed for every subsystem of the EPS separately to guarantee the stability of the overall closed-loop system. The performance of the proposed digital model is tested and compared with the analog model under variation in loading patterns, loading conditions, system parameters, wind farm penetration, and communication delays. Results approved that, the proposed digital model can effectively regulate the system frequency and guarantee robust performance under different conditions. Also, it gives a reliable performance at large sampling times, which means a reduction of implementation cost.
This paper presents a small hybrid power system consists of two types of power generation; wind turbine and diesel generation, DG connected to power distribution system. The fluctuations like random ...nature of wind power, turbulent wind, and sudden changes in load demand create imbalances in power distribution that can affect the frequency and the voltage in the power system. So, addition of Energy capacitor System, ECS is useful for compensation of fluctuating power, since it is capable of controlling both active and reactive power simultaneously and can smooth the output power flow. Hence, this paper proposes herein a dynamic model and simulation of a grid connected wind/DG based-ECS with power flow controllers between load and generation. Moreover, the paper presents a study to analyze the leveling of output fluctuation of wind power with the installation of ECS. To control the power exchanged between the ECS system and the AC grid, a load Following Control, LFC based supervisor is proposed with the aim to minimize variations of the power generated by the diesel generator. The interesting performance of the proposed supervisor is shown with the help of simulations. The computer simulation program is confirmed on a realistic circuit model which implemented in the Simulink environment of Matlab and works as if on line.
Dealing with power distribution system became one of the most important arts in the field of power system, especially in the rapid increase of the distributed generation (DG) penetration to the ...distribution level which is a vital and important part of the entire power system. In this paper, a very special power distribution system with a unique deployment of distributed generation, such as, photovoltaic and wind generation has been studied. Energy storage system is utilized to play the main role to control the system’s power quality and the system frequency, as load following operation (LFO) and automatic generation control (AGC), respectively. In this paper, a working criterion has been introduced followed by a case study focuses on two important conditions, one of them when the proposed system is connected to the electrical grid (upper system) and the other one when the system is completely islanded. In both cases, the crucial usage of the ECS gives a concrete result which made the system fully recommended to be applied in real life.
Optimization of diesel generators (DGs) and renewable energy sources have to be done within a cost-benefit, high reliability and environmentally friendly framework. Most of the optimization methods ...just consider only the economical point of view. This paper presents complete optimization method involving of cost, reliability and pollutant emission into optimization process. The reliability level is analyzed using basic probabilistic concept in order to find loss of load probability (LOLP). This value is then used to determine the customer damage cost due to electricity interruption. Meanwhile, CO2 emission as an indicator of pollution is calculated to determine the annual emission cost (AEC). By considering both reliability level and CO2 emission, the optimization results do not just show economic merit but will satisfy both of reliability level and environmental issue.
This paper presents a comparative study using new approach for optimum design of rooftop grid connected PV system installation on an institutional building at Minia University, Egypt. The new ...approach demonstrated in this paper based on optimal configuration of PV modules along with inverters according to not only MPP voltage range but also maximum DC input currents of the inverter. Five different brands of commercially available PV modules and inverters have been conducted in this study. Many different configurations of rooftop grid connected PV systems have been investigated and a comparative study among these configurations has been carried out taking into account PV modules and inverters specifications. Energy production aptitudes, cost of energy, simple payback time and GHG emissions have been appraised for each configuration using proposed MATLAB computer approach. Simulation results show that, annual energy production of about 258. 8 MWh, COE of about 0. 5482 $/kWh, payback period equal 6. 95 years and total annual GHG emissions reduction of about 180. 9 tons.
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