Content uploaded by Peter Kadar
Author content
All content in this area was uploaded by Peter Kadar on Jan 10, 2016
Content may be subject to copyright.
Pros and cons of the renewable energy application
Abstract
Nobody questions the reason for existence of fossil power plants meanwhile the acceptance of the renewable tools is often problematic. Of course the rationales based on the experiences of decade long operation the picture is not clear. The world turns to the consciousness that well-ruled renewables contribute to the sustainability. We summarize dozens of pros and cons and we are going to suggest ways to fit the renewable resources into the power system.
... State Estimation (SE) is a key element of power system operation ever since it was first introduced by Schweppe et al. in 1969 [1]. While transmission system operation quickly embraced this computational method, the ongoing structural shifts in the power network [2] -including electrification, distributed and variable generation, and the integration of smart functionalities -have elevated SE into the focus of scientific research, yielding substantial advancements in the field. Dehghanpour et al. conducted an extensive review of the method encompassing mathematical problem formulation, pseudo-measurement applications, metering instrument placement, network topology challenges, impacts of renewable energy integration, and addressing cybersecurity concerns [3]. ...
... As society and technology have progressed, humanity has gone through several energy transitions that have brought to the center of the energy mix different resources, such as wood, coal, oil, and gas. Currently, the paradigm shifts in the energy sector envisage the predominant use of renewable energy resources, which have a low environmental impact [8][9][10][11][12][13][14][15]. Redefining the energy mix is a complex problem considering the economic, social, technological, and geopolitical challenges that affect the energy sector [16][17][18][19]. ...
As civilization and technology have developed, there have been multiple energy transitions that have pushed various resources like coal, wood, oil, and gas to the forefront of the energy mix. Due to a variety of geopolitical initiatives, there have been progressively more restrictions on the energy sector in recent years. One of the main concerns of researchers is the widespread use of renewable energy and the replacement of fossil resources. The utilization of non-renewable energy sources results in a detrimental increase in greenhouse gas emissions. One of the most crucial strategies for lowering energy consumption and enhancing the energy system’s sustainability is to increase energy efficiency. Numerous studies note that energy transition has become necessary in the modern day. Using the analysis of the main components as an extraction method, hierarchical cluster analysis, this study focuses on the situation of the states of the European Union in their race for energy transition, taking into account the main challenges generated by geopolitical tensions and the energy poverty spectrum for the population. The conclusions of the study call for a reconfiguration of the energy mix based on renewable energy. Increasing the share of renewable energy is a goal pursued by EU countries, but energy policies must be considered in a broader context that includes the social aspects of the energy transition. So, just transition is a new concept that reshapes the actions of public authorities on the path to a low-carbon economy. Just transition is a necessity that puts the consumer at the center of attention so that the negative externalities generated by the move away from fossil fuels are minimized in terms of social impact.
... The availability and actual power generation of these variable resources is heavily influenced by weather conditions, challenging the security of electricity supply. In power systems exposed to increased volatility [1], model-based assessments, being a well-established approach to solve engineering problems [2][3], are of key importance. Both the recent advances in the availability of climate data and the novel modelling approaches such as the emergence of machine learning-based methods opened new ways for power system analysis and prospective studies on renewable energy integration. ...
... EKIK has been traditionally a strong advocate of various emerging interdisciplinary research activities in the past 10 years, notable examples include smart cities [61], smart infrastructure [62] and smart materials [63], digital health [64] and digital infection prevenction [65], plus renewable energy and sustainability [66] and AIbased cybersecurity [67]. ...
... These advantages can compensate for certain limitations, mostly seasonal fluctuations in output, the need for locations with adequate sunlight exposure, variations in insolation, shading and cell ageing (Gorjian et al., 2021). Location is a very important consideration because it determines a PV system's output (Kádár, 2014) and the profitability of solar farms. Location is a critical parameter in micro-scale residential PV installations, which have to strictly conform to local zoning requirements. ...
The study proposes a simple procedure for evaluating the suitability of various locations for the installation of micro-scale solar photovoltaic (PV) systems. The main aim of the study was to determine the applicability of GIS tools for assessing the suitability of different locations for solar energy generation. The applicability of open-source databases in geoinformation analyses was emphasized. The study was conducted in the urban municipality of Mrągowo in the Region of Warmia and Mazury, Poland. Mrągowo is characterized by considerable physiographic diversity, which influenced the results of the study. The evaluation focused on rooftops which are most widely used for the installation of micro-scale solar PV systems. For the purpose of generalization, the results of the evaluation were presented for the districts of Mrągowo, so as to assist state agencies, local governments, and non-public institutions in implementing local policies that support renewable energy generation. The average amount of energy (MWh) that can be generated per building and the total amount of energy (MWh) that can be generated in cadastral districts were calculated to determine the solar energy potential of the study site
... A dynamic analysis tool is needed to accurately describe the system's response to the rapid environmental change in weather conditions to study the SHIP system's performance [23], [24]. T*sol software is a professional simulation program for designing solar thermal systems, including domestic hot water (DHW), swimming pool heating, district heating, and heat process systems. ...
Worldwide, industrial process heat accounts for over two-thirds of global industrial energy consumption. Wherein solar thermal systems are expected to be a reliable alternative solution. The temperature output of the flat-plate collector (FPC) is enough to serve specific industrial applications where low temperature is needed for heat processes, as in the food and beverage sector where nearly all the demand is needed heating and more than 40% is below 100℃. This work presents a tankless solar heat for industrial process (SHIP) system using FPC to produce low temperature for process heat of a food factory in the climate of central Europe. The modelling system is developed based on heat transfer and thermodynamics phenomena, and it is resolved mathematically and validated experimentally onsite. Moreover, this study considers the Budapest region (47.50° N, 19.04° E-Hungary) as a case study. The metrological data is extracted by MeteoSyn software. The objective function is to meet the set temperature requirements for preheating water for food factories to minimize the annual energy costs by saving more fuel. The heat exchanger secondary loop's six different temperature configurations were used as 60, 55, 50, 45, 40 and 35℃, respectively, and each measurement was tested for several summertime days. Results show that tankless SHIP can help preheat water for temperatures below 100℃. By comparing the different configurations, they are acierating that all set temperature combinations can be achieved at a lower mass flow rate of 60 litres per hour for the primary and secondary loops. The obtained outcomes of this work show that integrating solar thermal systems into industrial processes for low-to-medium temperatures is a very economical and promising solution to replace fossil fuels.
... Each of the above processes has its own disadvantages. For instance, the amount of electricity generated by wind and solar power plants is highly dependent on external weather conditions [4]. These plants also face problems with integration into power network [5]. ...
Currently, there is an increase in average annual temperature and climate change across the various continents. Carbon dioxide emissions from energy facilities contributed to this condition. Implementation of oxy-fuel cycles is a promising solution for reducing carbon dioxide emissions from the energy sector. To date, the most efficient oxy-fuel cycle is the Allam cycle. In this cycle supercritical carbon dioxide acts as a working fluid of the cycle, wherein СО2’s temperature upstream of the turbine is 1,150 °С and the pressure is 30 MPa. Due to the high temperature of the working fluid, it is necessary to cool first stages of the carbon dioxide turbine. The feature of considered cooling system in this turbine is that carbon dioxide being used as a refrigerant too. This paper investigated two topologies of convective cooling systems in the carbon dioxide turbine’s nozzle blade as well as considers an option for increasing the intensity of heatexchange through the use of helical ribbing in the cylindrical cooling baffle. Numerical simulation involving the ANSYS software package was performed for two topologies of the cooling baffles arrangement in the nozzle blade body: configuration 1 -with 17 baffles of 1 mm diameter, configuration 2 -with three baffles of the blade profile shape. Configuration 1 proved to be more efficient: the Nusselt number has a value of 117, and average value of the heat transfer coefficient on the refrigerant side is 6,413 W/m2∙K. The effect of using helical ribbing in the cooling cylindrical baffle of the blade under study was investigated, which enabled to reduce the metal temperature by 54 °С on average and doubled the heat transfer coefficient.
This paper proposes anomaly detection for hydroelectric generating units by Fast Robust Random Cut Forest with a fast feature selection method by considering characteristics of operating data and Random Cut Trees. Hydroelectric generating units are renewable electric generating sources for electricity supply. Therefore, it is crucial to accurately detect anomalies of hydroelectric generating units. Moreover, effective features for anomaly detection should be selected to reduce operation costs of anomaly detection services. The proposed anomaly detection method can detect anomalies approximately thirty times faster than the conventional Robust Random Cut Forest with an accuracy comparative to that of the conventional method. The proposed feature selection method can select effective features almost fifty times faster than the conventional feature selection method.
PV based large scale energy generation has spread significantly. In spite of similar technical parameters the amount of yearly produced energy may differ by notable percents. It results from the operation of solar trackers and also from the different spectral behavior of the different PV panel types. In this paper we introduce a novel on site spectral sensitivity measurement method. The spectral characteristic is recalculated from separate power maximum measurements, where the measurements are made by spectrally different natural irradiation (sunrise, noon, foggy, cloudy, etc.).
Lately, the use of solar energy has seen considerable development.Transformation in electric energy is one of its applications which attracts considerableinterest, owing to the fact that it makes it possible to solve a major problem in isolatedcities that lack electrical supply networks. For solar energy use, the current drawbackremains its high cost. This problem can be resolved through different improvements interms of power production. For that, different axis of research can be explored [1-3].Over the past few years, solar cells arrays (SCA) have been connected to various loads in adirect coupled method. A PV module can produce the power at a point, called an operatingpoint, anywhere on the current- voltage (I-V) curve. The coordinates of the Operating pointare the operating voltage and current. There is a unique point near the knee of the I-Vcurve, called a maximum power point (MPP), at which the module operates with themaximum efficiency and produces the maximum output power. The point of maximumpower is the desired operating point for a PV array to obtain maximum efficiency. A PVarray is usually oversized to compensate for a low power yield during winter months. Thismismatching between a PV module and a load requires further over-sizing of the PV arrayand thus increases the overall system cost [3-5]. To mitigate this problem, differentmethods have been developed [6-12]. A maximum power point tracker (MPPT) can be usedto maintain the PV module’s operating point at the MPP. The system in a direct coupledmethod cannot always operate at maximum power point (MPP) of the solar array when theload, irradiance or temperature changes. A PV-load coupling system should be able tomaximize the energy output of the PV generator, which should operate always at itsmaximum power point (MPP) in order to achieve maximum global efficiency. Some authorshave supported the direct coupling between the PV generator and the load [2-3]. Severalmethods and algorithms to track the maximum power point have been developed [2-12].We focused our effort on improving the matching between PV sources and loads throughthe development of new performing methods. In this paper, a rapid approach for peakpower tracking is proposed. The system PV generator - load is optimized, when the workingpoint in direct coupling is quite near the MPP of the PV generator, so that the globalefficiency of the system is acceptable. Another method is proposed. It is based onreconfiguring on-line the SCA by changing the connections between different modules in order to minimize the losses due to load and operation conditions. Two strategies forimprovements are chosen for testing in this study, whatever the loads and operatingconditions.The experimental system used a microcontroller. It is robust when undergoing environmentchanges and load variations. The performance of the methods is verified throughsimulations and experiments.
This paper deals with the design and execution of a solar tracker systemdedicated to the PV conversion panels. The proposed single axis solar tracker deviceensures the optimization of the conversion of solar energy into electricity by properlyorienting the PV panel in accordance with the real position of the sun. The operation of theexperimental model of the device is based on a DC motor intelligently controlled by adedicated drive unit that moves a mini PV panel according to the signals received from twosimple but efficient light sensors. The performance and characteristics of the solar trackerare experimentally analyzed.
Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency.
The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control
methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements.
Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies
impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind
of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation,
fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as
the most adequate methodologies to address several planning, control and operation problems in power systems. Future power
systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity
and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires
more effective optimization and control techniques techniques so that the involved players can make the most adequate use
of existing resources in the new context. The application of computational intelligence methods to deal with several problems
of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises
of computational intelligence, and illustrate their potentials.