Air Pollution Dispersion Modelling using GRAL in Area Near Coal-Steam Power Plant at Central Java

Sulfur dioxide and Nitrogen dioxide were significant emissions emitted from coal-steam power plants that may cause health problems for humans and damage the environment. Studying the SO2 and NO2 gradients in Indonesian residential communities is critical for evaluating resident's SO2 and NO2 exposure. The method developed to assist analysis of spatial SO2 and NO2 gradients on a community scale combines a mesoscale Lagrangian dispersion model with field observations around coal-steam power plants using GRAL. The objectives of this study focused on GRAL dispersion of SO2 and NO2 in an Indonesian residential community near the coal-steam power plant, with a 6 km x 8 km resolution. Analysis of this model indicates a correlation between simulation and observation, with SO2 coefficient correlation (R) within 0.5 – 0.82 and NO2 coefficient correlation (R) within 0.30 – 0.59. Model performances analyze by NMSE and FB. The SO2 model is comparable to observation data since it has a better average NMSE and FB than the NO2 model. Due to data limitation of observation collected by grab sampling instead of continuous ambient measurement system affect different respond time compared with hourly data from the model.

Social and Environmental Responsibility of Tidore ESPP to the Community of Tidore City Village, Tidore Islands

This study aims to (1) determine the implementation of social and environmental responsibility of ESPP Tidore to the community in the rum village (2) to determine the factors that influence the implementation of social and environmental responsibility of ESPP Tidore to the community of Rum City of Tidore Islands. The results showed that the Tidore ESPP was operated in mid 2017. After that, it was inaugurated by the Government in August 2016, until entering 2021 only 4 programs were implemented. Even though it has been in operation for 5 years. This indicates unpreparedness in the planning of Corporate Social Responsibility (CSR) programs and obstacles regarding the Technical component of Electric Steam Power Plant (ESPP) Operation. Distribution of Corporate Social Responsibility (CSR) and even then because it considers the pressure from the community for the sake of improving communication in the business climate, in addition to obligations that are regulated based on existing regulations.

Development of a Software System for Selecting Steam Power Plant to Convert Municipal Solid Waste to Energy

A software system that enhances the selection of appropriate power plant capacity that will convert combustible municipal solid waste (MSW) into energy was developed. The aggregate of waste to be converted was determined and the corresponding heating value was established. The capacities of steam power plants’ components required for the conversion were determined, using thermodynamic mathematical models. An algorithm based on models used to determine the energy potential, the power potential of MSW, the capacities of the components of the steam power plant, were translated into computer soft code using Java programming language; saturated steam and superheated steam tables, together with the thermodynamic properties of the power plant required were incorporated into the soft code. About 584 tons of MSW having a heating value of 20 MJ/kg was the quantity of waste experimented for energy generation. This information was input into the software as data and was processed. Then, the software was able to predict 3245.54 MWh energy potential for the quantity of waste, and electrical power potential of 40.54 MW. The capacities of the steam power plant components that were predicted include 100.35 MW of boiler power, 40.54 MW of turbine power, and 59.80 MW of condenser power. The methodology adopted will make it easy for the managers in the waste-to-energy sector to appropriately select the suitable capacity of the required steam power plant that can convert any quantify of MSW at any geographical location, without going through the engineering calculation and stress or rigor involved in the plant capacity design. Moreover, the accuracy obtained for the software is greater than 99%.

Self-Tuning PID-Genetic Algorithm Controller for Steam Drum Boiler Water Level Control System

A control system with uncertainty or unpredictable disturbance needs more effort to be controlled. A conventional PID Controller is the most popular method used in industries. It was tuned and adjusted by the designer, and it has fixed parameters during operation. However, the disturbance effect causes the desired system performance unreachable. By using a self-tuning controller, the problem should be tackled. In this paper, the PID-Genetic Algorithm (PID-GA) controller was proposed and tested with the steam drum water level control system of a steam power plant. Variation in power load causes noisy water level characteristics and should be maintained at + 0.4 meters from the setpoint to prevent the power plant trip. From the simulation, PID-GA can reduce disturbance of the minimum, nominal, and maximum load with perturbation peaks 0.18 m, 0.22 m, and 0.26 m respectively.Keywords: genetic algorithm, NWL, PID-GA, steam drum, steam power plant.