Integrated Power Plant Research Articles

Explainable forecasting of global horizontal irradiance over multiple time steps using temporal fusion transformer

Accurate prediction of solar irradiance is essential for the successful integration of solar power plants into electrical systems. Despite recent advancements in deep learning technology yielding impressive results in solar forecasting, their lack of interpretability has hindered their widespread adoption. In this paper, we propose a novel approach that integrates a Temporal Fusion Transformer (TFT) with a McClear model to achieve accurate and interpretable forecasting performance. The TFT is a deep learning model that provides transparency in its predictions through the use of interpretable self-attention layers for long-term dependencies, recurrent layers for local processing, specialized components for feature selection, and gating layers to suppress extraneous components. The model is capable of learning temporal associations between continuous time-series variables, namely, historical global horizontal irradiance (GHI) and clear sky GHI, accounting for cloud cover variability and clear sky conditions that are often ignored by most machine learning solar forecasters. Additionally, it minimizes a quantile loss during training to produce accurate probabilistic forecasts. In this study, we evaluate the performance of hourly GHI forecasts on eight diverse datasets with varying climates: temperate, cold, arid, and equatorial, for multiple temporal horizons of 2, 3, 6, 12, and 24 h. The model is benchmarked against both climatological persistence for deterministic forecasting and Complete History Persistence Ensemble for probabilistic forecasting. To prove that our model is not location locked, it has been blind tested on four completely different datasets. The results demonstrate that the proposed model outperforms its counterparts across all forecast horizons.

Smart Urban Wind Power Forecasting: Integrating Weibull Distribution, Recurrent Neural Networks, and Numerical Weather Prediction

The design, operational planning, and integration of wind power plants with other renewables and the grid face challenges attributed to the intermittent nature of wind power generation. Addressing this issue necessitates the development of a smart wind power (and in particular wind speed) forecasting approach. This is a complex task due to substantial fluctuations in wind speed. To overcome the inherent stochastic nature of wind speed and mitigate related challenges, traditionally, numerical weather prediction (NWP) models are employed for wind speed forecasting. However, the applicability of NWP models is limited to short-term forecasting due to their computational constraints. In this study, a hybrid AI-based approach is proposed to improve forecast accuracy over a 48 h horizon for the city of Montreal. The results demonstrate that by integrating the probability distribution of wind speed with a deep learning model, the forecasted values align closely with the observed values in terms of seasonality and trend, exhibiting enhanced accuracy. Evaluation metrics reveal a substantial reduction in the root mean squared error (13–31%) across three prediction horizons (summer, fall, and winter) compared to a single long, short-term memory model. Furthermore, integrating the improved model with the numerical weather prediction model yields increased accuracy and decreased error compared to the LSTM–Weibull model.

Progress in Concentrated Solar Power, Photovoltaics, and Integrated Power Plants Towards Expanding the Introduction of Renewable Energy in the Asia/Pacific Region

Progress in Concentrated Solar Power, Photovoltaics, and Integrated Power Plants Towards Expanding the Introduction of Renewable Energy in the Asia/Pacific Region

Indirect power cycles integration in concentrated solar power plants with thermochemical energy storage based on calcium hydroxide technology

Thermochemical energy storage is attracting interest as a relevant alternative energy storage system in concentrating solar power plants. Efficient, low-cost, and environmentally friendly thermal energy storage is one of the main challenges for the large-scale deployment of solar energy. The reversible hydration/dehydration process of calcium oxide is one of the most promising concepts for energy storage integration at intermediate temperatures in solar plants. The efficient integration of concentrated solar power with a thermochemical energy storage system based on the calcium hydroxide concept, individually or integrated into a hybrid system with sensible heat storage, can be a feasible solution for long-term energy storage. Efficient energy recovery and subsequent power production are crucial. This work presents a novel analysis of the indirect integration of different power cycle configurations to optimise the roundtrip efficiency of the system. Steam Rankine, closed CO2 Brayton, and organic Rankine cycles are considered. The analyses show power block efficiencies in the range of 38–50%, with a global roundtrip efficiency of 37.1% in the case of the CO2 supercritical cycle.

Economic Power Dispatch of a Grid-Tied Photovoltaic-Based Energy Management System: Co-Optimization Approach

The requirement for the integration of power plants due to the cyclical rise in electrical energy consumption is due to the fluctuating load demand experienced with the current grid systems. This integration necessitates effectively allocating loads to the power plants for a minimum grid-tied transmission line cost, while meeting the network constraints. In this paper, we formulate an optimization problem of minimizing the total operational cost of all committed plants transmitted to the grid, while also meeting the network constraints and ensuring economic power dispatch (EPD) and energy management system co-optimization. The developed particle swarm optimization (PSO) method resolves the optimization problem using a piecewise quadratic function to describe the operational cost of the generation units, and the B coefficient approach is employed to estimate the transmission losses. Intelligent adjustments are made to the acceleration coefficients, and a brand-new algorithm is suggested for distributing the initial power values to the generation units. The developed economic power dispatch strategy successfully demonstrated an imperative cost reduction, with a connected load of 850 MW, 1263 MW, and 2630 MW of power demand, contrasted with previous PSO application cost values percentage, maximum yearly cost savings of (0.55%, 91.87), (46.55%, 3.78), and (73.86%, 89.10), respectively, and significant environmental benefits. The proposed co-optimization approach can significantly enhance the self-consumption ratio compared to the baseline method.

Reduction of energy losses through the integration of photovoltaic power plants in distribution networks

AbstractIn Latin America, distribution networks are mostly radial, with high energy losses, representing about 16% of the region's electricity consumption. In Cuba, one of the alternatives that has been proposed to reduce these losses is the distribution of photovoltaic (PV) power plants of up to 3 MWp in them. This paper presents a new hybrid optimization algorithm to localize and size PV power plants to minimize energy losses in radial distribution networks. The method localizes the power plants using Empirical Discrete Metaheuristic in conjunction with a novel strategy that reduces the execution time of the algorithm. The sizes are found using the Coordinate Search Method, which performs one‐dimensional searches in the directions of the variables of the objective function. The algorithm was run on a 33‐bus IEEE test system in which up to five power plants were optimally installed, taking into account load variations at the distribution level and changes in the weather conditions under which the power plants operate. It should be noted that the execution times for each scenario did not exceed 30 s. The algorithm was validated by comparing it with other methods found in the literature and proved to be more efficient than them.

Comprehensive review of power system oscillations in large-scale power electronic-based renewable energy power plants

Recently, the large-scale integration of power electronic-based renewable energy power plants has changed the operation and response mechanism of the power system, resulting in several emerging oscillation issues that have seriously been threatening the system's stability. It helps us to recognize the similarities and differences among the triggering causes and formation mechanisms of oscillation scenarios. Following several typical oscillation events in the real world and the timescale decomposition method, this paper comprehensively reviews the wide-bandwidth oscillation study from the aspects of the analysis methods, possible cause, mechanism, and mitigation solution. The paper provides a perspective to classify the oscillations in the modern power systems on the basis of the oscillation frequency and the main oscillation module. This classification framework involves not only emerging oscillations in the power system with large-scale renewable energy sources integration but also includes typical oscillations in traditional power systems. It also systematically presents the relative relationship, development process, and inner influence between emerging oscillations and typical oscillations. Based on this review, the future research is suggested to focus on the relationship between different analytical methods or oscillation mechanisms, as well as the stability risk assessment of hybrid alternating current and direct current power systems.

Towards nearly zero emissions natural gas-fired power plants using cryogenic carbon dioxide capture technology

Cryogenic carbon capture (CCC) is one of the most recent and promising technologies for reducing carbon dioxide emissions, hence mitigating the global warming. The present research aims at exploring the feasibility of integrating it into existing thermal power plants in Egypt that are commonly operated by natural gas.A simulation model is developed using Aspen Plus Dynamics software to accurately predict the behavior of the thermal power plant after applying such integration. The model incorporates the CCC cycle established by Sustainable Energy Solutions into a natural gas power plant of Abu Qir, Egypt. The integral plant is benchmarked at various part loads scenarios. The study investigates the ability of capturing up to 99% of the emitted CO2 and determines the consequent penalties in the generated power and the overall thermal efficiency.The results demonstrated successful integration of the thermal power plant and the CCC revealing smooth operation and safe transition between different part loads. By capturing 99% of the emitted CO2, both the generated power and the overall efficiency dropped maximally by 10.73%. The integration led to a maximum energy penalty of 0.840 MJe/kgCO2 which is much smaller than other conventional carbon capture techniques.Applying this technology to all thermal power plants in Egypt, about 89 M tonnes of CO2 emissions will be captured annually. Further integrations of CCC-ECL into other chemical and industrial facilities would significantly lead to a cleaner environment.

Thermo-Environ-Economic Optimization of an Integrated Combined-Cycle Power Plant Based on a Multi-objective Water Cycle Algorithm

The integration of power plants and desalination systems has attracted increasing attention over the past few years as an effective solution to tackle sustainable development and climate change issues. In this light, this paper introduces a novel modelling and optimization approach for a combined-cycle power plant (CCPP) integrated with reverse osmosis (RO) and multi-effect distillation (MED) desalination systems. The integrated CCPP and RO–MED desalination system is thermodynamically modelled utilizing MATLAB and EES software environments, and the results are validated via Thermoflex software simulations. Comprehensive energy, exergic, exergoeconomic, and exergoenvironmental (4E) analyses are performed to assess the performance of the integrated system. Furthermore, a new multi-objective water cycle algorithm (MOWCA) is implemented to optimize the main performance parameters of the integrated system. Finally, a real-world case study is performed based on Iran's Shahid Salimi Neka power plant. The results reveal that the system exergy efficiency is increased from 8.4 to 51.1% through the proposed MOWCA approach, and the energy and freshwater costs are reduced by 8.4% and 29.4%, respectively. The latter results correspond to an environmental impact reduction of 14.2% and 33.5%. Hence, the objective functions are improved from all exergic, exergoeconomic, and exergoenvironmental perspectives, proving the approach to be a valuable tool towards implementing more sustainable combined power plants and desalination systems.

A fusion approach for evaluating ground conditions for seismic microzoning at the Egyptian Solar Park in Benban, Aswan

Seismic microzoning is the process of mapping out and comprehending the differences in ground motion due to earthquakes in a certain location. Accurate seismic microzoning is vital for the development and safety of buildings and infrastructure in earthquake-prone locations. In this work, we present the application of microtremors, multichannel analysis of surface and machine learning approaches for seismic microzoning at Benban Solar Park in Aswan, Egypt. The findings of the investigation indicated that the ground at Benban Solar Park was generally stiff, with certain regions having stronger stiffness and damping qualities than others. The data also indicated variances in the ground conditions at various sites inside the solar park, with certain regions having a greater risk of ground motion due to earthquakes. Overall, the combination of microtremors, multichannel analysis, and machine learning has shown to be an excellent strategy for correctly and effectively mapping out the ground conditions at Benban Solar Park and assuring the safety and structural integrity of the solar power plants at the park. Moreover, the results of the research could be used to guide the design and construction of the future solar power plants at the park and to examine the safety and structural integrity of the solar park. Furthermore, the application of these techniques not only ensures the safety and structural integrity of the solar power plants at Benban Solar Park, but also promotes sustainable development by providing valuable information for the design and construction of future solar power plants at the park, in line with the principles of environmentally-conscious and responsible development.

Energy, exergy and exergoeconomic (3E) analyses of an organic Rankine cycle integrated combined cycle power plant

Energy, exergy and exergoeconomic (3E) analyses of an organic Rankine cycle integrated combined cycle power plant

Estimating the Overload Capacity of IGBTs by the Criterion of Their Heating in Conducting State

The last decade has witnessed a growing demand for replacing conventional generation by power plants based on renewable energy sources, which are connected to the grid through converting devices (inverters). A distinctive feature of such devices that the inertia moment notion is not applicable to them. In addition, some of their components were not originally meant for full-valued participation in emergency control. In view of these circumstances, the integration of such power plants into the grid may entail degradation of both the power system stability and power supply reliability level. Using the example of 10 types of 600 A IGBT modules commercially available from three manufacturers [Infineon Technologies AG (Neubiberg, Germany), Elektrovypryamitel JSC (Saransk, Russia), and Fuji Electric (Tokyo, Japan)], the limit transistor collector current loads at which the semiconductor thermal destruction occurs as a consequence of its inadmissible overheating caused by conductivity heat release are estimated. The thermoelectric analysis was carried out in the Matlab/Simulink environment based on IGBT thermoelectric models. The performed simulation has shown a high degree of IGBT safety margin in terms of collector current (on average 275% of its maximum continuous value). If necessary, this value can be increased further by upgrading (forcing) the cooling system or shifting to a higher gate--emitter voltage, which allows the load range to be widened by about 30–50 percentage points. The study results have shown a high IGBT overload capacity in terms of heating the transistors by the current passing through them (a power source connected to the grid through an inverter can experience overloads, in terms of its thermal operation mode, commensurable with those of standard generating equipment). In view of the high IGBT overload capacity in terms of heating, other restrictions will be the governing ones, in particular, for the transistor safe operation range, which should be taken into consideration when initially choosing, if necessary, transistors for a higher collector current.

Empirical modeling of ex-vessel debris bed formation in a pre-flooded reactor cavity

To secure the containment integrity of a nuclear power plant (NPP) in severe accident situation of ex-vessel corium release into the reactor cavity, a pre-flooding strategy of a reactor cavity has been adopted in various NPPs, including Korean PWRs. Molten corium released into the pre-flooded water pool is fragmentized and forms a particulate debris bed at the bottom of the cavity. To prevent the containment failure, it is important to properly remove the heat from the debris bed, which can be accomplished by water ingression into the bed. The water ingression characteristics are highly dependent on the debris bed shape. In this study, several main parameters affecting the debris bed shape were determined with respect to phenomena of free-fall & sedimentation, particle dispersion by steam spike and convection flow, and self-leveling. Then empirical model was developed and validated using the results of DEFCON (Debris bed Formation and COolability experimeNt) experiments. The model’s error was within ±10% when only free-fall & sedimentation were present. When steam-spike or convection was added to free-fall & sedimentation condition, the error increased to within ±20%. When all three were simultaneously present (free-fall & sedimentation, steam-spike, and convection), the model predicted most of the experimental results within ±20% error, except for several cases where convection had a significant impact. The effect of self-leveling itself was within ±10%. Considering all phenomena related to particulate debris bed formation, most cases had an error of ±20%. In addition, the debris bed shape formed by poly-disperse particles was predicted appropriately by the mode using the mass mean diameter of the particle size distribution, with an error range of ±20%. Consequently, it is expected that the proposed model of the debris bed shape can be utilized in an integrated severe accident analysis code for the evaluation on the ex-vessel debris bed coolability in the pre-flooded reactor cavity.

Modeling and Simulation of a Large-Scale Wind Power Plant Considering Grid Code Requirements

The load demand to a power grid, as well as the interest in clean and low-cost energy resources, has led to the high integration of wind power plants into power system grids. There are grid code standards that are set for the design and integration of these wind power plants. These codes often look at the design operation of the wind power plant in islanded mode, where possible analysis of the most sensitive power system quantities such as voltage, frequency, reactive power, etc. is carried out. Therefore, in this study, attention was paid to the application of these codes to keep the design and integration of wind power plants well standardized as much as possible. The purpose of this paper is to review and discuss the literature and theory about the design of wind turbine generators and model and simulate a large-scale wind power plant. The modeling was successfully carried out on RSCAD, and the results obtained show that the wind power plant can be further used for other studies such as voltage stability improvement in power grids.

Development, exergoeconomic assessment and optimization of a novel municipal solid waste-incineration and solar thermal energy based integrated power plant: An effort to improve the performance of the power plant

Due to the growing population rate and increasing social activities, the content of municipal solid waste (MSW) production is increasing. Energy production from MSW is one of the promising ways to dispose of waste and reduce the limitations of fossil energies. However, this technology has a relatively low efficiency due to the high volume of moisture and inert materials in MSW and the lower heating value of waste. The integration of solar thermal collectors is one of the suggested solutions to increase the temperature of inlet steam to the power generation cycle in order to improve the power plant performance. In this regards, the present study develops a comprehensive thermodynamic-conceptual and exergoeconomic investigation of the performance of a MSW-incineration (MSWI) plant integrated with a parabolic trough collector (PTC)-based solar field. Accordingly, the temperature of the steam elevates by the solar field before entering the electric power generation cycle. Additionally, the solar unit is integrated with a phase change material (PCM)-based storage system. The use of storage tank at the delivery line of PTC can improve the power plant’s reliability. A comprehensive comparison of the developed power plant with the conventional MSWI power plant is presented. In addition, the technical and economic behaviors of the considered power plant have been optimized under two different single and multi-objective optimization scenarios. The outcomes indicated that the developed power plant can provide 15.75% and 15.68% higher energetic and exergetic efficiencies compared to MSWI power plant. In addition, the rate of electric power obtained from S-MSWI power plant is almost 16.1% more compared to MSWI power plant. However, the total cost rate of MSWI plant is almost 24.13% lower compared to the developed power plant. But, the value of LCOE in the developed power plant is approximately 8.93% lower than MSWI power plant. It was also found that, the multi-objective optimization can provide better and optimal results to energy engineers and decision makers compared the single-optimization. The conceptual design of the implementation of the solar field is also developed in a specific geographical condition. Additionally, this research comes from the key technology of the National Key Laboratory of Environmental Protection.

Special issue on “Optimal design and operation of energy systems”

Special issue on “Optimal design and operation of energy systems”

Beneficial role of diurnal smoothing for grid integration of wind power

Smoothing of generation variability, i.e. reduction of variance in the aggregate generation is crucial for grid integration of large-scale wind power plants. Prior studies of smoothing have focused on geographical smoothing, based on distance. In contrast, we propose a novel concept ‘diurnal smoothing’ that depends on spatial variations in the timing of seasonal-mean diurnal cycle peak. Considering the case of India, which experiences a strong diurnal cycle of wind-speed, we show how spatial heterogeneity in the wind diurnal cycle can be exploited to smooth wind power variability over and above geographical smoothing. For any given separation distance between sites, the hourly wind speed correlation is highly variable. Difference in timing of the diurnal cycle peak is an important factor for explaining this variability and we define smoothing from differently timed seasonal-mean diurnal cycle as ‘diurnal smoothing’. We show that apart from separation distance, the diurnal cycle is crucial for correlation among sites separated by 200 km or more with strong diurnal cycles (amplitude more than approximately 0.5 m s−1). Thus, diurnal smoothing is a vital factor in the aggregation of large wind power plants, and grid integration is benefited by considering (in addition to distance) new wind plant sites with largely separated diurnal cycles, especially those differing by roughly 12 h. Such diurnal smoothing is relevant for regions across the world with strong wind speed diurnal cycles. Ultimately grid integration depends on variations in total wind and solar generation and demand. Hence, their combined effects must be studied.

Efficiency Optimization via Mission Profile-Based Power Routing by Design of Hybrid Grid Connecting Converter Architecture

Hybrid grids with low voltage direct current (LVdc) distribution are an attractive opportunity for the integration of electric vehicle charging stations and photovoltaic power plants. With dc connectivity reduced power losses are possible, however, multiple conversion stages can impair an efficient operation. A solution can be the use of an “interconnected” architecture that allows the integration of multiple insulated dc and ac grids. The reconfiguration of this modular topology allows optimization for different design objectives. This work investigates the system efficiency-optimized reconfiguration. Two approaches for deriving the reconfiguration of the hybrid grid connecting converter architecture based on mission profiles are proposed. A validation of the analysis via laboratory results is given.

Techno-Economic and Environmental Analysis of the Integration of Solar Tracked or Fixed-Tilt Photovoltaic Power Plants to Open Coal Fields of Thermal Power Plants in Turkey

Techno-Economic and Environmental Analysis of the Integration of Solar Tracked or Fixed-Tilt Photovoltaic Power Plants to Open Coal Fields of Thermal Power Plants in Turkey

Developing a three-phase converter to be used in a prototype of a virtual inertia system based on frequency and active power relationship

The integration of power plants based on renewable energy sources (RES) into existing energy systems causes a number of problems, one of which is the violation of the stability of the generators parallel operation. One of the possible methods for the above problem solving is the use of virtual inertia systems (VIS). In this paper, we review the process of a converter developing for further use in a VIS prototype. The developed device converts direct current from a laboratory power supply into a sinusoidal three-phase voltage of industrial frequency. The switching of the converter’s power transistors is controlled through digital signal processor (DSP) TMS 320 F 28379 D via IR 2110 drivers. Using Altium Designer, a schematic diagram and layout of the printed circuit board of the converter were developed. Based on the manufactured printed circuit board, a converter was assembled, the correctness of its operation was checked, and a conclusion was made about the possibility of its use in the VIS prototype.