Solar Photovoltaic Power Prediction Using Big Data Tools

Solar photovoltaic (PV) installation has been continually growing to be utilized in a grid-connected or stand-alone network. However, since the generation of solar PV power is highly variable because of different factors, its accurate forecasting is critical for a reliable integration to the grid and for supplying the load in a stand-alone network. This paper presents a prediction model for calculating solar PV power based on historical data, such as solar PV data, solar irradiance, and weather data, which are stored, managed, and processed using big data tools. The considered variables in calculating the solar PV power include solar irradiance, efficiency of the PV system, and characteristics of the PV system. The solar PV power profiles for each day of January, which is a summer season, were presented to show the variability of the solar PV power in numerical examples. The simulation results show relatively accurate forecasting with 17.57 kW and 2.80% as the best root mean square error and mean relative error, respectively. Thus, the proposed solar PV power prediction model can help power system engineers in generation planning for a grid-connected or stand-alone solar PV system.

Application of Support Vector Regression and Time Series Method in Short-term Power Load Forecasting with Regional difference

Aims: Short-term load forecasting Background: Short-term load forecasting has played a key role in power dispatching. It provides basic data for basic power generation planning and system safety analysis so that the power dispatching work is more practical and the power generation efficiency is higher. Objective: It provides basic data for basic power generation planning and system safety analysis and makes power dispatching work more practical and power generation efficiency higher. It ensures the safe operation of the electricity market and relieves the pressure of supply and demand. Results: It has the advantage of minimizing the structural risk and has good generalization performance to the predicted object. At the same time, the global optimization is ensured, a lot of mapping calculation is reduced, the actual risk is reduced, and the prediction performance is improved. Conclusion: The target model has higher forecasting accuracy than other forecasting models and can effectively solve the problems of the power market.

Overview of Electrical Energy Planning in West Sumatera

Electrical energy is one of the most important components in the development of an area. The development of sustainable development accompanied by rapid technological advances and an increase in living standards can cause the consumption of electrical energy to continue to increase, including in West Sumatra Province. To meet the needs of electrical energy in the future, it is necessary to build and develop the existing electrical system at PT. PLN (Persero) in order to serve the needs of electrical energy in the future. One of them is by predicting or predicting the demand for electrical energy in the next few years by utilizing historical data on the consumption of electrical energy in the past. In this study, the authors predict the electricity needs of West Sumatra Province from 2019 to 2028. The need for electrical energy tends to increase from year to year. In 2019 the need for electrical energy is 3,705 GWh, while in 2028 it is 6,980 GWh with an average growth in energy sales of 7.29 percent. The household sector has the highest demand for electrical energy in 2028, namely 3,769 GWh with an average percentage increase per year of 6.6 percent. Keywords: Power system planning, Electrical energy consumption, Generation planning and Electrification ratio.

YOUTH KNOWLEDGE ABOUT THE GENERATION PLANNING PROGRAM AND ATTITUDE OF YOUTH IN MATURITY AGE OF MARRIAGE AT SMA NEGERI 4 BATAM

Background : Generation Planning is a program developed in the context of preparing and planning family life for adolescents. One of the main focuses in this program is the maturity of marriage age for adolescents. The purpose of this study was to describe the knowledge of adolescents about the Generation Planning program and the attitudes of adolescents in the maturity of the marital age at SMA Negeri 4 Batam. Method : This study used a descriptive research design. The length of the research was 6 months with a population of all students of class X and XI SMA N 4 Batam as many as 737 students, the sampling was systematic random sampling with a sample size of 88 respondents. , Result : as many as 53 respondents (60.2%) and good as many as 35 respondents (39.8%). Frequency distribution of the majority of adolescents' attitudes have positive attitudes as many as 63 respondents (71.6%) and those who have negative attitudes are 25 respondents (28.4%) conclusion : Adolescent knowledge about the Planning Generation program at SMAN 4 Batam is the majority of the knowledge is Less as many as 53 respondents (60%) The attitude of adolescents in the Maturity of the Marriage Age at SMAN 4 Batam is that the majority are positive as many as 63 respondents (71%)

Application of Compromise Programming in the Energy Generation Planning

The need for the right electricity planning is closely related to the analysis that has to be done on its generating capacity. Of course, in order to make such planning, the choice of the method by which the process is carried out must be considered. The inclusion of multiple objectives (goals) enables us to create models that are useful in researching and expanding electricity generation systems. Compromised programming used in this paper aims to find compromise solutions among different conflicting objectives in the electricity generation system. One such case is the goal of minimizing the cost and CO2 emissions. Using this logic, the paper deals with an example of electricity generation planning for a given region.