scholarly journals Active power ouptut optimization for wind farms and thermal units by minimizing the operating cost and emissions

2020 ◽  
Vol 10 (4) ◽  
pp. 3412
Author(s):  
Nazha Cherkaoui ◽  
Abdelaziz Belfqih ◽  
Faissal El Mariami ◽  
Jamal Boukherouaa ◽  
Abdelmajid Berdai
Keyword(s):  
Objective Function ◽  
Power Plants ◽  
Fossil Fuels ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Operating Cost ◽  
Wind Farms ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Grey Wolf Optimizer

In recent years, many works have been done in order to discuss economic dispatch in which wind farms are installed in electrical grids in addition to conventional power plants. Nevertheless, the emissions caused by fossil fuels have not been considered in most of the studies done before. In fact, thermal power plants produce important quantities of emissions for instance, carbon dioxide (CO2) and sulphur dioxide (SO2) that are harmful to the environment. This paper presents an optimization algorithm with the objective to minimize the emission levels and the production cost. A comparison of the results obtained with different optimization methods leads us to opt for the grey wolf optimizer technique (GWO) to use for solving the proposed objective function. First, the method used to estimate the wind power of a plant is presented. Second, the economic dispatch models for wind and thermal generators are presented followed by the emission dispatch model for the thermal units.Then, the proposed objective function is formulated. Finally, the simulation results obtained by applying the GWO and other known optimization techniques are analysed and compared.

scholarly journals Emission Constrained Economic Dispatch with PV Energy Penetration

2019 ◽  
Vol 8 (12) ◽  
pp. 3021-3026
Keyword(s):  
Renewable Energy ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Thermal Power ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Optimization Strategy ◽  
Renewable Energy Resources ◽  
Pv System ◽  
Power Stations

Power system planners are forced to consider the alarming rate of environmental pollution and rapiddepletion of fossil fuels andutilize renewable energy resources to mitigate the environmental effects of thermal power stations. Combined Economic Emission Dispatch(CEED)offers an effectivesolution to reducefossil fuel emissions as well ascost.Since 1985, CEED is considered to be a common optimization strategy. Literature contains lot of optimization methods for the strategy.In the recent times, using PV energy has proved to be a feasible and dependable alternative for electricity generation systems based on fossil fuels. In the developing countries, the dependency on fossil fuels has been seen as inevitable. At present,the use of renewable energy sources is rapidly increasing in inconventional power generation systems. The present paper puts forwardan approach of combining PVenergy-based grid integrated PV system with fossil fuel based thermal power plant using evolutionary programmingbased optimization technique.Among the various optimization techniques, the Particle Swarm Optimization (PSO) is considered to be the most suitable technique for the problem is explained in detailed manner.The proposed method is to combine CEED with the PV energy and thereby reduces the use of conventional energy resources.It also permits an effective utilizationof abundantlyavailable PV energy.It is tested on standard IEEE 30 bus system with the real time ratings of proposed PV plant situated in Tamilnadu.

scholarly journals Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski
Keyword(s):  
Large Scale ◽  
Thermal Power ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Pso Algorithm ◽  
Search Space ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Ramp Rate ◽  
Dynamic Economic Dispatch

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

scholarly journals Assessment of efficiency and prospects for the use of hybrid thermal low-capacity power plants in the Republic of Vietnam

2019 ◽  
Vol 124 ◽  
pp. 01040 ◽  
Author(s):  
D. T. Nguen ◽  
D. N. Pham ◽  
G. R. Mingaleeva ◽  
O. V. Afanaseva ◽  
P. Zunino
Keyword(s):  
Power Plants ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Thermal Power ◽  
Climatic Conditions ◽  
Energy Sources ◽  
Thermal Power Plants ◽  
Basic Design ◽  
Air Heating ◽  
The Republic

The growing demand for energy and fossil fuels creates increased number of difficulties, while renewable energy sources are still rarely used worldwide, particularly in Vietnam. In this article hybrid thermal power plants based on gas turbine plants are discussed, the increased efficiency of which is achieved by air heating after the compressor in solar air heaters. The basic design equations and the results of evaluating the efficiency and fuel consumption are presented for two thermal power plants of 4.6 MW and 11.8 MW. The dependence of the results on the intensity of solar extraction for the climatic conditions of the Ninh Thuan province of the Republic of Vietnam is discussed.

CFD Based Ash Deposition Prediction in a BFB Firing Mixtures of Peat and Forest Residue

2003 ◽  
Author(s):  
Christian Mueller ◽  
Dan Lundmark ◽  
Bengt-Johan Skrifvars ◽  
Rainer Backman ◽  
Maria Zevenhoven ◽  
...  
Keyword(s):  
Combustion Chamber ◽  
Computational Fluid Dynamic ◽  
Power Plants ◽  
Fossil Fuels ◽  
Fluid Dynamic ◽  
Thermal Power ◽  
Biomass Combustion ◽  
Mineral Matter ◽  
Forest Residue ◽  
Bubbling Fluidized Bed

Fuels currently used for energy production in thermal power plants are characterized by their huge variety ranging from fossil fuels to biomass and waste. This multitude of fuels offers opportunities to the energy industry and nowadays many power plants do not fire either of these fuels but mixtures of them are burnt. While this procedure may lead to overall economic and environmental advantages it is very demanding for the boiler operators to still meet expectations concerning boiler performance, boiler availability and emission regulations. In the course of this latest trend in boiler operation, ash related operational problems such as slagging, fouling and corrosion are ranking very high on the list of reasons leading to significant reduction of boiler availability. Ash related problems strongly dependent on fuel specific aspects, such as the mineral matter distribution in the fuel, aspects specific to the used combustion technique as well as design aspects unique for the combustion chamber of any operating power plant. The overall goal in combustion related research is therefore the prediction of potential operational problems originating from fuel streams entering the combustion chamber as well as those originating from the design of individual furnaces. In our earlier work we have strongly focused on developing an advanced ash behavior prediction tool for biomass combustion combining computational fluid dynamic calculations (CFD) and advanced fuel analysis. In this paper the tool is applied to analyze the slagging and fouling tendency in a 295 MW bubbling fluidized bed boiler fired with mixtures of peat and forest residue. In addition to the overall deposition prediction this work focuses on details of the models used in the computational fluid dynamic calculations. These include a study on the importance of the accurate description of the fuel feeding system and related to this aspect the advanced description of the bubbling bed with regard to release of primary gas and ash particles from its surface to the freeboard. Evaluation of the predictions comparing simulation results with deposits on the furnace walls show good agreement.

scholarly journals Exergoeconomic optimization of a thermal power plant using particle swarm optimization

2013 ◽  
Vol 17 (2) ◽  
pp. 509-524 ◽  
Author(s):  
Axel Groniewsky
Keyword(s):  
Power Plant ◽  
Energy Conversion ◽  
Power Plants ◽  
Optimization Problems ◽  
State Of The Art ◽  
Search Algorithm ◽  
Thermal Power ◽  
Optimization Methods ◽  
Conversion System ◽  
Energy Conversion System

The basic concept in applying numerical optimization methods for power plants optimization problems is to combine a State of the art search algorithm with a powerful, power plant simulation program to optimize the energy conversion system from both economic and thermodynamic viewpoints. Improving the energy conversion system by optimizing the design and operation and studying interactions among plant components requires the investigation of a large number of possible design and operational alternatives. State of the art search algorithms can assist in the development of cost-effective power plant concepts. The aim of this paper is to present how nature-inspired swarm intelligence (especially PSO) can be applied in the field of power plant optimization and how to find solutions for the problems arising and also to apply exergoeconomic optimization technics for thermal power plants.

scholarly journals An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xu Chen ◽  
Bin Xu ◽  
Wenli Du
Keyword(s):  
Particle Swarm Optimization ◽  
Learning Strategy ◽  
Economic Dispatch ◽  
Operating Cost ◽  
Particle Swarm ◽  
Inequality Constraints ◽  
Optimization Techniques ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Save Energy

Economic dispatch (ED) plays an important role in power system operation, since it can decrease the operating cost, save energy resources, and reduce environmental load. This paper presents an improved particle swarm optimization called biogeography-based learning particle swarm optimization (BLPSO) for solving the ED problems involving different equality and inequality constraints, such as power balance, prohibited operating zones, and ramp-rate limits. In the proposed BLPSO, a biogeography-based learning strategy is employed in which particles learn from each other based on the quality of their personal best positions, and thus it can provide a more efficient balance between exploration and exploitation. The proposed BLPSO is applied to solve five ED problems and compared with other optimization techniques in the literature. Experimental results demonstrate that the BLPSO is a promising approach for solving the ED problems.

scholarly journals Editorial

2019 ◽  
Vol 18 (2) ◽  
pp. 02
Author(s):  
Diogo Berta Pitz
Keyword(s):  
Gas Turbines ◽  
Power Plants ◽  
Fossil Fuels ◽  
Industrial Revolution ◽  
Thermal Power ◽  
Steam Generators ◽  
Computing Power ◽  
Energy Demands ◽  
Residential Use ◽  
Engineering Projects

Since the Industrial Revolution mankind has been interested in obtaining energy from various sources in order to fulfill its ever-increasing energy demands for industrial, commercial and residential use. Fortunately, we have been able to produce energy in quantities that permit technological innovations and the spread of existing technologies around the world. Such success is due not only to the search for alternatives to fossil fuels, but also to the development of devices that allow fuels to be used in rational, efficient ways. The refinement of equipment that improve our lives – from refrigeration devices used in residential applications to steam generators and gas turbines employed to generate electricity in thermal power plants – is only possible due to physical understanding of processes such as heat transfer, combustion, fluid flow dynamics and thermodynamic systems. Physical modeling of such phenomena provides tools for optimization of engineering projects, which ultimately results in an efficient use of the energy resources available. In an era where the computing power available allows us to analyze models that are ever more faithful to the physical behavior of real processes, we have the ability to push existing technologies to ever-increasing limits of energy efficiency and to explore the viability of new processes.

Artificial Intelligence for Optimal Sitting of Individual and Networks of Wind Farms

2019 ◽  
Author(s):  
Seyyed Pooya Hekmati Athar ◽  
Dorsa Ziaei ◽  
Navid Goudarzi
Keyword(s):  
North Carolina ◽  
Site Selection ◽  
Geographical Information Systems ◽  
Power Plants ◽  
Wind Farm ◽  
Wind Farms ◽  
Optimization Techniques ◽  
Geographical Information ◽  
Fireworks Algorithm ◽  
Weather Patterns

Abstract Renewable Energy (RE)-based power production often comes with certain challenges in variability and uncertainty of generated electricity. One promising solution to tackle these challenges is developing a network of RE power plants with sites located far enough from each other that experience different weather patterns. Most of the site selection-related literature use Geographical Information Systems to determine the studied site RE suitability. This work converts the site selection into a numerical problem through a novel Networked Renewable Power Plant Site Selection model and solves it by employing optimization techniques. To enhance the accuracy of the results, it compares a set of criteria for individual and network of sites at different regions to determine the exact locations for RE plant developments. The Analytical Hierarchy Process is used for criteria weighing. The state-of-the-art meta-heuristic Bare Bones of Fireworks algorithm offer a simple, fast, yet accurate approach to solve the optimization. The proposed method is applied on North Carolina wind farms for both individual and a network of sites. The results identified the areas with the highest wind capacity potential for individual or a network of wind farms in North Carolina. The identified suitable areas were verified with Amazon Wind Farm US East.

scholarly journals Beyond Strict Regulations to Achieve Environmental and Economic Health—An Optimal PM2.5 Mitigation Policy for Korea

2020 ◽  
Vol 17 (16) ◽  
pp. 5725
Author(s):  
Kyungwon Park ◽  
Taeyeon Yoon ◽  
Changsub Shim ◽  
Eunjin Kang ◽  
Yongsuk Hong ◽  
...  
Keyword(s):  
Air Quality ◽  
Computable General Equilibrium ◽  
Power Plants ◽  
Fossil Fuels ◽  
Thermal Power ◽  
Computable General Equilibrium Model ◽  
Policy Paradigm ◽  
Korean Economy ◽  
High Dependency ◽  
Pm2.5 Emissions

Growing concern about particulate matter (PM2.5) pressures Korea to reduce the health risks associated with its high dependency on fossil fuels. The Korean economy relies heavily on large thermal power plants—a major source of PM2.5 emissions. Although air quality regulations can negatively impact local economies, the Korean government announced two strict air quality mitigation policies in 2019. We develop a regional static computable general equilibrium model to simulate the economic and environmental impacts of these polices under alternative hypothetical scenarios. We separate two regions, Chungcheongnam-do, the most polluted region, and the rest of the country, in our model. As policy options, we introduce a regional development tax and a tradable market for PM emission permits, similar to an air pollution tax and a carbon permits market, respectively. The results show that allowing higher tax rates and a tradable permits market gives the optimal combination, with the PM2.5 emissions reduced by 2.35% without sacrificing economic growth. Since alternative options present, for example, a 0.04% loss of gross domestic product to reduce PM emissions by the same amount, our results here may present a new policy paradigm for managing air pollutants such as PM2.5.

scholarly journals Measuring the Ecological Efficiency of Thermal Power Plants: Evidence from Pakistan

2020 ◽  
Vol 37 (1) ◽  
pp. 159-184
Author(s):  
Imran Qaiser ◽  
Theocharis Grigoriadis
Keyword(s):  
Power Plants ◽  
Fossil Fuels ◽  
Thermal Power ◽  
Returns To Scale ◽  
Material Balance ◽  
Environmental Benefits ◽  
Fuel Oil ◽  
Data Envelopment ◽  
Balance Principle ◽  
Residual Fuel Oil

This paper assesses the environmental and economic efficiency of thermal plants operating on fossil fuels in Pakistan using methods based on data envelopment analysis. Using the material balance principle, we find that cost- and carbon-efficient points can only be obtained simultaneously by switching to gas. However, under an assumption of variable returns to scale, these points can still be obtained without this conversion through the application of best practices. Furthermore, about 26% of costs and about 34% of carbon emissions can be reduced without a switch to gas, but instead by using technically efficient inputs; this approach can also lead to a significant reduction in electricity prices and considerable environmental benefits. Power plants operating on residual fuel oil are significantly more technically efficient than plants operating on gas. Nonetheless, both types of plants have an equal share in forming the metafrontier as exhibited by the meta-technology ratio. There is a definite need to make plants more efficient by using the best possible combination of inputs and overhauling. Bootstrap results also suggest that further improvement in efficiency is possible.

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