A A Wind Forecasting Model Using Regression and Genetic Algorithm to Solve Economic Dispatch for Evaluating a Hybrid Power System

2021 ◽  
Vol 2 (2) ◽  
pp. 43-50
Author(s):  
Haidar Rahman ◽  
Ridwan Budi Prasetyo
Keyword(s):  
Genetic Algorithm ◽  
Wind Speed ◽  
Power System ◽  
Power Plants ◽  
Minimum Energy ◽  
Economic Dispatch ◽  
Electrical Energy ◽  
Operational Cost ◽  
Renewable Power ◽  
Using Data

In this research, the problem to find an evaluator to determine a location to build the standalone power system can be seen as problem which can be solved with Kernels Regression where, it will receive 2 inputs such as time and wind speed in order to predict the future wind speed. Afterward the obtained predicted wind speed will be converted into potential electrical energy with maximum and minimum energy and we will be using the Genetic Algorithm (GA) to solve the Economic Dispatch (EDC) to see the operational cost when dispatch into the grid. The data was taken from Baron Techno-Park and PLTH Pantai Baru, and will only be using data from the month of September - December since it is the rainy season. Therefore, since significant parameters such as energy per currency will show that operational cost of Baron Techno-Park have the least operational cost then PLTH Pantai Baru, hence the creation of renewable power plants in Baron Techno-Park are suitable and will have a good operational cost justification. Keywords: Economic Dispatch, Genetic Algorithm, Kernels Regression Standalone Power Plant.  

Multi-Objective Economic Emission Load Dispatch Solution Using Evolutionary Algorithm with and without Considering Wind Power Penetration and Valve Point Effect

2014 ◽  
Vol 626 ◽  
pp. 177-183
Author(s):  
K. Thenmalar ◽  
S. Ramesh ◽  
K.S. Anuja
Keyword(s):  
Quadratic Programming ◽  
Power System ◽  
Wind Power ◽  
Power Plants ◽  
Electrical Power ◽  
Electrical Energy ◽  
Fuel Cost ◽  
Electrical Power System ◽  
Bacterial Foraging Optimization ◽  
Multi Objective

The electrical power system is considered as the most complex man-made systems mainly due to their wide geographical coverage. Electrical energy industries contributes environmental pollution which rise questions concern environmental protection and methods of eliminating or reducing pollution from power plants either by design or by operational strategies. Electric power plants are mainly aimed to operate al low fuel cost strategies .In this paper a Multi –Objective Economic Emission Load Dispatch problem is solved to minimize the emission of nitrogen oxides (NOx) , oxides of other fuels that release during generation of electricity and fuel cost considering both Thermal generators and Wind turbines. A large number of iterations and oscillation are those of the major concern in solving the economic load dispatch problem by using the BFO(bacterial foraging optimization) method. By applying BFO method the economic dispatch problem is optimized to minimize the total generation cost of a power system while satisfying various equality and inequality constraints. The effect of Wind power on overall emission is also investigated here using Quadratic programming by wolf’s method. This method has better convergence characteristic. Wolf’s method is an extended simplex procedure which can be applied to Quadratic programming problems in which all the problem variables are non-negative.

scholarly journals Combined Emission Economic Dispatch of Power System in Presence of Solar and Wind Using Flower Pollination Algorithm

2019 ◽  
Vol 38 (3) ◽  
pp. 581-598
Author(s):  
Anum Abid ◽  
Tahir Nadeem Malik ◽  
Muhammad Mansoor Ashraf
Keyword(s):  
Power System ◽  
Economic Dispatch ◽  
Electrical Energy ◽  
Operational Planning ◽  
Flower Pollination Algorithm ◽  
Potential Solution ◽  
Renewable Energy Resources ◽  
Flower Pollination ◽  
Nonconvex Constrained Optimization ◽  
Output Characteristics

ED (Economic Dispatch) problem is one of the vital step in operational planning. It is a nonconvex constrained optimization problem. However, it is solved as convex problem by approximation of machine input/output characteristics, thus resulting in an inaccurate result. Reliable, secure and cheapest supply of electrical energy to the consumers is the prime objective in power system operational planning. Increase in fuel cost, reduction in fossil-fuel assets and ecological concerns have forced to integrate renewable energy resources in the generation mix. However, the instability of wind and solar power output affects the power network. For solution of such solar and wind integrated economic dispatch problems, evolutionary approaches are considered potential solution methodologies. These approaches are considered as potential solution methodologies for nonconvex ED problem. This paper presents CEED (Combined Emission Economic Dispatch) of a power system comprising of multiple solar, wind and thermal units using continuous and binary FPA (Flower Pollination Algorithm). Proposed algorithm is applied on 5, 6, 15, 26 and 40 thermal generators by integrating several solar and wind plants, for both convex and non-convex ED problems. Proposed algorithm is simulated in MATLAB 2014b. Results of simulations, when compared with other approaches, show promise of the approach.

scholarly journals Development of Optimized Methodology for Improvement Domestic Energy Management

2019 ◽  
Vol 8 (4) ◽  
pp. 5288-5294
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Wind Speed ◽  
Energy Management ◽  
Electrical Energy ◽  
Supply Side ◽  
Demand Side ◽  
Load Schedule ◽  
The Cost ◽  
Daily Load

Electrical energy management (EEM) is an object that has proceeds appointed importance in the 21 th - century in order to its assistance to economic development and ecological ascertainment. “EEM” may be perfected on the supply side “(SS)” or demand side “(DS)”. On the supply side, “EEM” is cultivated when: There is an outgrowth desire “(demand requirement is higher than supply)”. “EEM” assists to suspend the design a resent generation station. On the “DS”, “EEM” is used to minimize the cost of electrical energy consumption and the interrelated forfeitures. The technique utilized for “EEM” is demand side load management that plan at ending valley filling, peak clipping and strategic preservation of electrical systems [1]. Seeming new inventions like “distributed generation (DG)”, “distributed storage (DS)” and “DSLM” will modify the method we use and generate energy. A smart grid (SG) is an electrical network that manages electricity demand in an unstoppable sustainable, reliable and economic manner. A smart grid uses smart net meters to overcome the sickliness of traditional electrical grid. “(DSM)” is a vital advantage of “(SG)” to progress power efficiency, minimize the peak average load and minimize the cost. From basic purposes of DSM is shifting load from peak hours to off-peak hours and reducing consumption during peak hours. Generally, a deregulated grid system is considered where the retailer purchases electricity from the electricity market to cover the end users’ energy need. In this research, Demand Side Management (DSM) techniques (load shifting and Peak clipping) are used to maximize the profit for Retailer Company by reducing total power demand pending peak demand periods and achieve an optimal daily load schedule using linear programming method and Genetic Algorithm. This method is performed on the 69-bus radial network. Also, a short term Artificial Neural Network technique is used to get forecasted wind speed, solar radiation and forecasted users load for date 15-Aug-2019. The neural network here uses an actual hourly load data, actual hourly wind speed and solar radiation data. Then the forecasted data is used in the optimization to get optimal daily load schedule to maximize the profit for Retailer Company. Then comparison between profit using linear programing and genetic algorithm are made. The optimized DSM succeeded to maximize the profits of the company.

scholarly journals An Optimized Method of Wind Speed Prediction with Support Vector Machine and Genetic Algorithm

2021 ◽  
Vol 15 ◽  
pp. 212-217
Author(s):  
Guan-fa Li ◽  
Wen-sheng Zhu
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Support Vector Machine ◽  
Wind Speed ◽  
Power System ◽  
Prediction Models ◽  
Optimization Method ◽  
Support Vector ◽  
Wind Speed Prediction ◽  
Speed Prediction

Due to the randomness of wind speed and direction, the output power of wind turbine also has randomness. After large-scale wind power integration, it will bring a lot of adverse effects on the power quality of the power system, and also bring difficulties to the formulation of power system dispatching plan. In order to improve the prediction accuracy, an optimized method of wind speed prediction with support vector machine and genetic algorithm is put forward. Compared with other optimization methods, the simulation results show that the optimized genetic algorithm not only has good convergence speed, but also can find more suitable parameters for data samples. When the data is updated according to time series, the optimization range of vaccine and parameters is adaptively adjusted and updated. Therefore, as a new optimization method, the optimization method has certain theoretical significance and practical application value, and can be applied to other time series prediction models.

On-grid Photovoltaic Power System for Governmental Office Electrification

2021 ◽  
Vol 3 (2) ◽  
pp. 45-52
Author(s):  
Ali Nasser Hussain ◽  
Zuhair Sameen Shuker ◽  
Majid Khudair Abbas Al-Tamimi ◽  
Mimouna Abid
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Power System ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Solar Panels ◽  
Battery System ◽  
Daily Average ◽  
Renewable Power ◽  
Grid Connection

Solar energy is one of the most promising renewable energy sources. The potential solar energy has a capacity to meet all energy requirements for human survival on planet earth. Some applications such as a thermoelectric generator, electric power generation with the assistance of solar panels and water applications are required to reduce the demand for electricity generated by conventional power plants. The current work evaluates the effectiveness of solar energy for supplying the police building located in Diyala, Iraq. The installed renewable power system consists of photovoltaic/ battery system set with grid connection installed on the roof of the building with a capacity of 5.52 kWp and battery unit (200 A, 48 Volt). Based on the daily average load kWh and daily average solar irradiance for the selected site (4.3 kWh/m2), the results of the energy generated by the system for two selected days showed that for a sunny day is about (11.63 kWh) and for party cloudy day is about (8.02 kWh). The average of energy fed to the grid for a sunny day was recorded more by more than 3.0 kWh and for party cloudy day by more than 4.0 kWh.  The system installed at the first day of February of the year 2021. The obtained results encourage to install of photovoltaic systems in the selected site which can feed such facilities with renewable energy and deliver energy to the grid.

scholarly journals An Experimental Investigation of FNN Model for Wind Speed Forecasting Using EEMD and CS

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Jianzhou Wang ◽  
Haiyan Jiang ◽  
Bohui Han ◽  
Qingping Zhou
Keyword(s):  
Wind Speed ◽  
Power System ◽  
Wind Power ◽  
Wind Farm ◽  
Frequency Noise ◽  
Wind Speed Forecasting ◽  
System A ◽  
Wind Power System ◽  
And Performance ◽  
Using Data

With depletion of traditional energy and increasing environmental problems, wind energy, as an alternative renewable energy, has drawn more and more attention internationally. Meanwhile, wind is plentiful, clean, and environmentally friendly; moreover, its speed is a very important piece of information needed in the operations and planning of the wind power system. Therefore, choosing an effective forecasting model with good performance plays a quite significant role in wind power system. A hybrid CS-EEMD-FNN model is firstly proposed in this paper for multistep ahead prediction of wind speed, in which EEMD is employed as a data-cleaning method that aims to remove the high frequency noise embedded in the wind speed series. CS optimization algorithm is used to select the best parameters in the FNN model. In order to evaluate the effectiveness and performance of the proposed hybrid model, three other short-term wind speed forecasting models, namely, FNN model, EEMD-FNN model, and CS-FNN model, are carried out to forecast wind speed using data measured at a typical site in Shandong wind farm, China, over three seasons in 2011. Experimental results demonstrate that the developed hybrid CS-EEMD-FNN model outperforms other models with more accuracy, which is suitable to wind speed forecasting in this area.

scholarly journals Mitigation of the alternative energy for the wind farm center considering temperature and wind speed

2018 ◽  
Vol 204 ◽  
pp. 04013 ◽  
Author(s):  
Rima Septiani Prastika ◽  
A.N. Afandi ◽  
Dwi Prihanto
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Alternative Energy ◽  
Power Plants ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Natural Source ◽  
Final Conclusion ◽  
Sustainable Procurement

Recently, electric usages are increasing every year by year in many sectors. In facts, fossil fuels have been fueled to produce electrical energy availability at many power plants which are very limited for the sustainable procurement. Developing and implementing renewable energy sources should be urgently promoted to reduce the dependence on fossil fuels that have been fueled to generate electricity for the long period throughout various power plant combinations. In expectation, the natural source of electrical energy which environmentally friendly and easy to obtain in nature is recommended to explore for the existing energy producers. The natural source of energy can be operated as an alternative power plant to reduce environmental effects and to decrease air contaminants. These works cover those opportunities. In these studies, the method used is a quantitative category with collected primary and secondary data for all evaluations and mitigations. In general, these works are also designed for identifying problems and looking for literature, data collection, processing stage, analysis phase, and final conclusion. The data used is defined in terms of temperature, air pressure, and wind speed. The collected data are supposed to the Purwoharjo City of Banyuwangi Regency, with 10 meters above ground level. Naturally, the wind speed is about 3.5 m/s to 4 m/s and the average temperature is 300° Kelvin. The potentially generated wind energy at a single point of coordinates is around 85.17 Wh.

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