Electrical Energy Demand Research Articles

Research on Improving the Performance of Waterborne Surface Insulation Paint

With the rapid development of China's economy, the demand for electric energy in society is increasing, which puts forward higher requirements for the structure and scale of the national power network. High voltage direct current transmission is considered a new technology that can effectively alleviate the problems of power resource allocation and transmission. Insulation technology is an important part of high-voltage DC transmission and transformation technology. Currently, research on external insulation components such as silicone rubber sleeves is relatively mature, and there is relatively little research on DC internal insulation components such as epoxy poured insulators. Under direct current conditions, the surface of insulation materials is prone to charge accumulation effects, resulting in significant differences in insulation and flashover characteristics compared to AC insulation materials.

Design of piezoelectric nanogenerator based on BiFeO3/epoxy resin with potential application for wearable electronic devices

AbstractGrowing demand for electric energy in newly developed electronic systems causes increasing interest in research on piezoelectric nanogenerators (PENGs). Design and fabrication of such devices is challenging, considering cost of materials used in their construction. This is the main reason why intensive research has begun on 0‐3 composites with piezoelectric properties. One of the most promising constituent materials for composites fabrication are polymers, due to their low cost and easy processing. Herein, we present fabricated wearable PENG with good impact and vibration energy conversion properties. Correlation between matrix stiffness and piezoelectric properties of 0‐3 type composite is proposed. It was found that composite with 10 wt.% of BiFeO3 particles exhibits power output density for vibrations, finger tapping, and air stream pressure P = 11.12 nW cm−3, P = 4.83 μW cm−3, and P = 769.2 μW cm−3, respectively. Decrease in stiffness of epoxy matrix results at least in two‐times lower power output density for this same PENG. The obtained results demonstrate that the fabricated BFO/epoxy composites show the wide applicability and potential to be integrated with other functional devices, for example, as a part of wearable devices in smart shoes.

H2/CO production via high temperature electrolysis of H2O/CO2 coupling with solar spectral splitting at a tunable cut-off wavelength

Solar driven CO2/H2O splitting is a promising path for large-scale and long-term solar energy conversion and storage. In this work, a thermodynamic model of solar driven high-temperature CO2/H2O electrolysis was established, with the full solar spectrum split at a tunable cut-off wavelength for meeting the electrical and thermal energy demands of the process at a high efficiency. Compared with the system without spectral splitting, the solar-to-H2 efficiency can be significantly improved from 36.0 % to 45.5 % by introducing spectral splitting. Besides, the optimal electrolysis temperature can be largely lowered, from 1623 K to 1323 K due to the significant reduction of the solar radiation input for electricity generation. The exergy efficiency of CO2 electrolysis was shown to be higher than that of H2O electrolysis due to the higher molar exergy of CO compared to H2, although the first-law efficiency of H2O electrolysis is higher at Tele < ∼1200 K. A high concentration ratio of the solar-thermal process can lead to both high solar-to-fuel efficiency and high optimal electrolysis temperature because of the reduction of reradiation loss. The electrolysis temperature and the use of excessive CO2/H2O were shown to have an important effect on both the efficiency and the optimal cut-off wavelength because they are closely related with the thermal and electrical energy demands of the whole process. The optimal cut-off wavelength can be as low as 540 nm at electrolysis temperature of 1873 K (Tele = 1873 K) and excessive H2O coefficient of 6 (r = 6), and increases to the working limit of the photovoltaic material (900 nm in this work) as the electrolysis temperature and excessive coefficient decrease to Tele < 1023 K and r < 2.

Battery Cell Balancing of V2G-Equipped Microgrid in the Presence of Energy Storage Aggregator

High electricity consumption in Sarawak’s cities is a concern, driven by residential, industrial, and commercial users. Greater demand for electrical energy requires more electrical resources, affecting grid stability. To prevent blackouts and enhance grid resilience, electric vehicles can serve as distributed energy storage in microgrids. The biggest problem facing energy storage is that not all batteries within energy storage are the same. Every battery cell in the battery pack has a different rate of self-discharge, capacity, internal resistance, and aging, even though they have the same chemical and physical characteristics. These variations lead to power imbalances in energy storage. Therefore, to address this issue, a unique voltage equalization method using a modular flyback converter is presented. Its core objective is to correct voltage imbalances among batteries. The proposed method is modelled using MATLAB, and the performance of the system has been evaluated. Furthermore, the developed model is implemented in a microgrid and tested for two different cases (with and without energy storage for electric cars). From the simulation outcomes, it has been verified that the developed cell balancing technique performs well in equalizing the voltage of cells than the conventional methods.

Towards the implementation of Positive Energy Districts in industrial districts: an Italian case study

Owing to the opportunity to provide an annual positive energy balance and net-zero carbon emissions, Positive Energy Districts aim at fostering the energy transition of urban city centres. To fully support the decarbonization of cities, it may be interesting to extend their implementation to other energy intensive districts, such as cities’ industrial areas. In this regard, this paper addresses the opportunity to apply the Positive Energy District concept within the industrial area of a city in the South of Italy. A mixed-use building, the industrial wastewater treatment plant and an office building have been involved as users and equipped with a 250 kW wind turbine and multiple photovoltaic plants installed on the roof of the buildings, in parking areas and in an unused land, for a total peak power equal to 466 kW. The renewable-based plants’ generation has been simulated in HOMER Pro® software, on a quarter-hour basis, and an energy and environmental analysis have been performed using users’ real electric load profiles. The proposed configuration allows to save 55% of primary energy and carbon dioxide emissions compared to the baseline case where users’ electric energy demand is fully met by the power grid. In particular, the primary energy saving is equal to 1 GWh/y and the carbon dioxide emissions reduction is equal to 150 tCO2/y.

Investigation of harmonics analysis power system due to non-linear loads on the electrical energy quality results

With the increase in the demand for electrical energy, more reliable and better quality energy is needed. This concept has taken its place in the field of electrical engineering with the title of "power quality". Today, power electronics elements, transformers, arc furnaces, converters, etc. used in industry, harmonic emitting elements have caused deterioration of power quality and as a result, it has led us to ways to get rid of harmonics. In order to provide quality electrical energy, some criteria such as continuity of energy, stability of voltage and frequency, proximity of power factor to 1, balance of phase voltages and harmonic amounts in voltage should be taken into consideration. In this study, the energy quality of different units in Giresun University Güre Campus was investigated with CA 8333 energy analyzer. The results obtained were transferred to the computer environment with the help of graphics. In order to analyze the harmonics and inter harmonics in the power system and to see the effect on the system, series active power filter is modulated and simulated against different nonlinear loads in MATLAB/Simulink program. The results are shown with the FFT (Fast Fourier Transform) analysis program to see the elimination of harmonics in the system and their response to filtering. The results of harmonics in the power system with nonlinear loads before and after filtering are analyzed and examined. As a result of the analysis, suggestions are made regarding the measures that can be taken.

Development of an energy digital twin from a hotel supervision system using building energy modelling

In this work, the utilization of the supervision system of a five-story hotel located in Northern Italy as tool to calibrate and validate a building energy model (BEM) is evaluated. The BEM is created using the TRNSYS simulation environment with the aim to develop a digital twin, to study the energy consumption of the building-HVAC system. The procedure for the supervision system preparation and the data analysis procedure is presented. The digital twin is then used to compare two control strategies for the thermostats’ control during summer to increase the energy efficiency of the building-HVAC system, and to use the heat storage properties of the building envelope to shift and shave the peaks of power demands. Control rules that allow a better match between electrical energy demand and availability, developed, and tested using the BEM, are pursued with the final goal to prepare the inclusion of the hotel in a smart grid. The building is modelled using TRNSYS Type 56 as a multi-zone building, with 96 thermal zones while the building monitoring is performed during the summer season from June to October 2022.

Estimating Electrical Energy and Capacity Demand for Regional Electric Flight Operations at Two Mid-Size Airports in Washington, U.S

Advances in battery-powered electric motor systems, lightweight materials, and aircraft design have resulted in the development of new battery-electric aircraft that could gradually replace conventional fuel-powered aircraft for certain use cases in the coming years. In the face of tight climate action goals and large airport hubs facing capacity constraints, electric aircraft at regional airports could help respond to increased regional travel demands. Charging these aircraft may be a significant new load on the electric grid serving airports. In this paper, to understand these load impacts, we develop a framework for estimating future energy (annual MWh) and power (average and peak MW) demand for charging battery-electric aircraft at regional airports. We apply our modeling framework to two mid-size case study airports in Washington, U.S: Paine Field/Snohomish County Airport and Grant County International Airport. Our method has three parts: assumptions on flight operations growth, technical feasibility to serve these flights with electric aircraft, and actual adoption of electric aircraft to serve feasible trips. The results reveal that, while electricity demand could rise substantially over time, during the first decade of adoption utility companies are expected to be able to serve the energy and power needs of electric aviation with available capacity at existing substations close to the airports in our case studies.

Energy Assessment of Solar Power Plant On-Grid Bi-direction 3 KW 1 Phase

The potential for generating electricity from solar energy as one of the renewable energies is suitable for rural areas, small populations, or communal systems. However, this type of power plant requires a high investment budget. Photovoltaic power systems must be designed to meet the demand for electrical energy but require a large supply. To build a more efficient system, it is necessary to build a communal system. For a small population, a 3000-watt power generation system is made. It will be distributed directly to users; a 5000-watt system is made for a larger area. It will be distributed directly to users and interconnected between generators with the principle of load control. In this study, a solar power plant (PLTS) was designed with an on-grid bidirectional system. Solar panels' conversion of electrical energy is channeled to users and stored in a battery backup system. This PLTS system produces a maximum power of 3000 watts by using 8 units of 450wp solar panels, an inverter with a 48-volt on or off-grid mode system, and 4 12V 200 Ah backup batteries. From the measurement results, the PLTS system will start converting DC current into AC with a radiation value of 356 to 1258 W/m2. Produce on-grid AC current energy, a maximum of 2297 watts, and charge backup batteries with DC current, a maximum of 14.3 A. This on-grid (bidirectional) backup PLTS system can convert DC current into AC, supply it directly to the network electricity (grid), and perform energy backups when solar energy is not energized.

Optimal Selection of Conductors in Distribution System Designs Using Multi-Criteria Decision

The growth in the demand for electrical energy, which is driven by the constant growth of the metropolises and the expansion of the productive capacities of the industrial sector, entails the inevitable development of the electrical system to satisfy all the required demands in a convenient, efficient, and reliable manner. In this scenario, power distribution companies will continue to need to expand their electrical systems in the short and medium term to obtain the lowest investment and operating prices for the period considered in the analysis horizon. The expansion of the system can be projected statically or dynamically, which depends on the criteria that each distributor, in turn, applies in their expansion projects. Multi-criteria decision making can provide deeper analysis perspectives considering infinite possibilities for optimal network sizing and the technical, operational, quality of service, and even system reliability factors. This research proposes a multi-criteria decision technique based on the CRITIC method to determine the optimal design of an electrical distribution system. For this purpose, several design scenarios are defined with different types of electrical conductors, and the power flows are calculated in each. From these simulations, the results obtained in voltage profiles, namely active and reactive power losses, current levels, and the costs associated with the conductors used, are recorded. With the multi-criteria technique, the winning alternative is the design scenario containing the best joint solutions for the analysis variables. The proposed methodology is validated in an IEEE 34-bar test system. The Matpower tool, available through Matlab, generates power flows for each proposed design case. The results obtained in the analysis variables are generated and stored in a decision matrix of 210 alternatives. The proposed method represents a novel and powerful alternative for design proposals of distribution systems considering quality, efficiency, and cost criteria.

RETRACTED: Analysis and optimization of thermal power plants: Pinch and exergy methods

The increasing demand for electrical energy and the depletion of fossil fuel reserves have underscored the need for the analysis and optimization of thermal power plants. This research focuses on the analysis and optimization of a combined cycle power plant that utilizes natural gas as its primary fuel. The study employs exergy analysis, pinch analysis, and related concepts to analyze the energy flows and identify inefficiencies within the system. The aims of the research are to determine the overall losses, component efficiencies, and overall efficiency of the combined cycle power plant and to optimize its performance using the atomic orbital search algorithm. The optimization aims to reduce waste and increase the overall efficiency of the power plant. By using these methods and algorithms, the research aims to address the challenges associated with fossil fuel consumption and contribute to the sustainable and efficient production of electrical energy. The overall exergy efficiency of the power plant increased from 68.73% in the design mode to 70.56% after optimization, resulting in a significant improvement in energy utilization and a reduction in exergy losses across the cycle components. In the low-pressure section of the heat recovery steam generator, exergy losses decreased from 2791.3 kW to 1600.67 kW after optimization, while in the high-pressure section, exergy losses reduced from 45,013 kW to 42509.72 kW. These optimizations demonstrate the potential to minimize exergy waste and enhance the overall performance of the power plant.

The thermal decomposition kinetics of carbonaceous and ferruginous manganese ores in atmospheric conditions

The thermal decomposition of carbonate minerals as pre-treatment before smelting reduces the energy requirement for smelting. It can also make the combustion of fossil fuels for heating unnecassary. Thermal decomposition may become important in reducing greenhouse gas emissions when producing ferromanganese alloys while simultaneously reducing electrical energy demand during smelting. A kinetic reaction rate model for the thermal decomposition of manganese ores is presented, based on published reaction rate kinetics for the decomposition of manganese oxides and calcium carbonate. The model was validated against thermogravimetric data for two carbonaceous manganese ore samples and one ferruginous manganese ore sample. The reaction rate model shows that carbonate minerals in the manganese ores are decomposed at temperatures above 900 °C while pyrolusite is decomposed at temperatures from 450 °C to 500 °C. Mn2O3 decomposes rapidly at 550 °C. Braunite decomposition at temperatures below 1000 °C was negligible. The presence of organic carbon in the samples led to further reduction of the samples during thermal treatment.

Solar photovoltaic–thermal hydrogen production system based on full-spectrum utilization

Full-spectrum high-temperature water electrolysis enables efficient conversion from solar to hydrogen. However, the supply of electric and thermal energy derived from solar energy does not match the demand for electric and thermal energy in high-temperature water electrolysis, resulting in significant energy losses within the system. In this study, a solar photovoltaic-thermal hydrogen production system based on full-spectrum utilization is proposed. The concentrated sunlight is divided into two parts based on wavelength. Longer-wavelength sunlight is directed to the reactor, where it is converted into thermal energy to directly supply the endothermic water electrolysis reaction. Shorter-wavelength sunlight is directed to photovoltaic cells to generate electrical power for the reaction. To achieve a match between the supply and demand of electric and thermal energy, system parameters are optimized for the proposed system. The results demonstrate that the mismatch losses of the proposed system are reduced by 42.8 percentage points compared to a conventional photovoltaic water electrolysis system. The proposed system achieves a solar-to-hydrogen efficiency of 39.0% under optimum conditions with a cutoff wavelength of 1000 nm, surpassing that of photovoltaic water electrolysis and water-splitting thermochemical cycle systems by 19.0 and 21.6 percentage points, respectively. Based on the proposed method, the solar-to-hydrogen efficiency can be improved.

Application of Seasonal Trend Decomposition using Loess and Long Short-Term Memory in Peak Load Forecasting Model in Tien Giang

Daily peak load forecasting is critical for energy providers to meet the loads of grid-connected consumers. This study proposed a Seasonal Trend decomposition using Loess combined with Long Short-Term Memory (STL-LTSM) method and compared its performance on peak forecasting of electrical energy demand with Convolutional Neural Network and LSTM (CNN-LSTM), Wavenet, and the classic approaches Artificial Neural Network (ANN) and LSTM. The study evaluated the models using demand data from the power system in Tien Giang province, Vietnam, from 2020 to 2022, considering historical demand, holidays, and weather variables as input characteristics. The results showed that the proposed STL-LSTM model can predict future demand with lower Base Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Therefore, the proposed method can help energy suppliers make smart decisions and plan for future demand.

Enhancing Gas Turbine Power Plant Performance in Tropical Climates by Using Inlet Air Cooling with Desiccant Dehumidification and Evaporative Cooling

Abstract Gas turbine power plants play a crucial role in meeting the growing demand for electrical energy. However, their performance can be hindered by high ambient temperatures and humidity levels in tropical climates, leading to a drop in power output. This study investigates the potential benefits of using inlet air cooling with desiccant dehumidification and evaporative cooling to improve the performance of gas turbine power plants in tropical regions. The results show that this inlet air cooling method, integrating evaporative cooling, desiccant wheel, and Maisotsenko cooler, is a viable alternative for mitigating the performance decrease of gas turbines in hot tropical conditions. Furthermore, the compressor inlet temperature can be reduced on average by 11.5 °C by using turbine exhaust gases to heat the regeneration air utilized in the desiccant wheel for dehumidification. Additionally, the power requirement of the inlet air cooling system amounts to around 0.9 MW compared with an improvement of more than 2 MW in power output at peak temperature. Further research is needed to understand and quantify other benefits related to inlet air cooling, such as reducing emissions of harmful pollutants and operating at higher turbine inlet temperatures.

Multiobjective optimization of heat recovery steam generator in a combined cycle power using genetic algorithm

AbstractDue to the increasing demand for electrical energy, efforts to increase the thermal efficiency of the steam and gas power plants have led to extensive reform in these cycles. One of these common reforms is employing a conventional combined gas‐steam cycle. In combined cycle power plants that are built to produce power, a significant portion of the input energy is lost. In this research to achieve the thermodynamic properties of a combined cycle power plant after modeling the cycle and determining the cycle potential independent variables, multiobjective optimization by imposing restrictions on cost functions and changing them concerning exergy efficiency has been analyzed. The results show that increasing the parameters of superheated temperature, pinch point temperature difference, pump exhaust pressure, and condenser inlet flow rate improves the system performance and increases exergy efficiency. It is shown by two‐objective optimization that when costs are increased up to 40%, exergy efficiency is increased, and when an increase is more than 40% repeated results would be obtained. Applying costs lower than 5% is not considered according to software limitations. Also, the results show that it is possible to increase exergy efficiency up to 79.7% with a 40% investment cost.

Conceptual principles of forecasting demand on the day-ahead market using changes in hourly bidded demand between previous similar days

On the basis of the Law on the Electricity Market adopted in 2017, the retail electricity market in Ukraine opened on January 1, 2019, and later, on July 1, 2019, the wholesale electricity market was launched. The day-ahead market (DAM) is one of the key segments of the Ukrainian electricity market. In order to implement trading strategy and successfully conduct business, to maximize the economic results in the specified market segment, it is important to understand the market situation and the structure of demand and supply. One of the indicators that must be taken into account when planning sales in the course of one’s activity is the demand for electrical energy. Currently, there are no universal algorithms in Ukraine suitable for short-term (per day) forecasting of the amount of electrical energy that will be traded on DAM. Therefore, to solve such a problem, a specialized forecasting algorithm is proposed. The basis of the developed algorithm is the possibility of considering the formulated problem in a parametric form, where, as indicators, the forecast and real data of the hourly demand on the DAM are used. At the same time, in order to find the forecast hourly demand on the market “a day ahead” – the values of the unknown indicators of the problem – an iterative method of their search is used based on statistical data of the amount of electricity purchases on the DAM, using the principle of multi-iteration analysis of changes in demand for previous similar days. The proposed algorithm is implemented in the MS Excel package, which indicates its versatility and ease of use. The high speed of obtaining a solution to the formulated problem is shown.

Robust Distribution Network Reconfiguration in the Presence of Distributed Generation Under Uncertainty in Demand and Load Variations

In modern power systems, distributed generation (DG) plays an important role in energy losses reduction, but DG penetration in such networks is restricted by technical and investment limitations. Therefore, distribution network reconfiguration (DNR) and DG operation reduce power losses more efficiently than when only DG is utilized. Also, network reconfiguration mitigates improper DG placement in such systems which are subjected to high penetration of variable loads and DG. On the other hand, electrical energy demand is estimated by load forecasting methods and therefore is a time-variant and uncertain parameter. Moreover, DG power generation is uncertain and depends on variable load power. Consequently, models presented for the reconfiguration problem should be adequately robust against load and generation uncertainties. Thus, the present paper proposes an effective robust model for reconfiguring distribution networks with load and generation uncertainties. The proposed model is sufficiently simple for implementation and is accurate enough to find the optimal solutions in acceptable computational times. The main features of the proposed model are its high robustness against uncertain parameters, in which proposed configurations are not changed easily by small variations in DG power and load amounts, and its effectiveness, which means that uncertain parameters may change the obtained solutions.

Geothermal energy exploitation in an island-based 100% renewables strategy. Case study of Tenerife (Spain)

The large-scale integration of non-dispatchable renewable energy must be carefully planned, especially in poorly robust electrical energy systems. Tenerife is the most populated of the islands in the Canary Archipelago (Spain) and has an isolated electrical system. It is envisaged for the horizon of 2040 that the island will have a high contribution of non-dispatchable renewable energies (fundamentally wind and solar photovoltaic). Tenerife also has exploitable high enthalpy geothermal resources. An energy planning model is implemented in this paper based on which different scenarios with high non-dispatchable renewable energy penetration in the island's electrical system are simulated. Geothermal energy is also incorporated in the simulations as a dispatchable renewable energy source, with the power required sized according to the hypotheses of each scenario. The results are compared according to different technical and economic parameters. An evaluation is also made of the influence that the capacity of the electrical system to take on higher non-dispatchable renewable power and the presence of energy accumulation systems might have on the minimization of losses in the non-dispatchable renewable energy capacity factor. The results of the simulated scenarios show that geothermal energy could meet up to 28.8% of the island's electrical energy demand, increasing the stability, flexibility and supply guarantee of system. A 100% renewable system could be possible through the incorporation of this energy source and the planning of energy accumulation systems. In the case study, the economic saving for Spain's electrical system could exceed 400 €million per year.

Estimating the demand function for electrical services for the family sector in Erbil governorate

This study aimed to estimate the function of demand for electric energy in the domestic sector in the Erbil governorate for the year 2022. The importance of the study comes from the fact that electric power is of great importance in the domestic sector, The electrical sector has an impact on all different areas of life. And by showing the factors affecting the increase in the demand for domestic electricity, where the domestic sector is one of the most important and most consumers of electric energy. The study relied on the deductive approach to study the determinants of demand for household electrical energy by collecting data through a questionnaire for a sample of families in Erbil governorate. And then using standard models to determine the quantitative relationship between expenditure on household electrical energy with its determinants. The study reached a number of conclusions, including: The results of estimating the determinants of demand for electrical energy in Erbil governorate are (monthly income, number of family members, housing area, educational level, presence of students in the family, number of appliances in the house, working hours Appliances in the house, the mechanism of confrontation against the separation of electrical loads, the determining factors for reducing the demand for electricity), where the estimated coefficients signals were in agreement with the economic theory and at high levels of significance. The study concluded with a number of proposals, including: rationalizing the consumption of electrical energy by using mechanisms, spreading awareness and increasing the consumption culture among members of society. Work on the commitment to pay the monthly bills, In addition to paying the accumulated bills, Using legitimate electricity and not working on electricity theft, Interest by the government and families in using renewable energy such as solar panels and wind turbines.