Journal articles on the topic 'Consumers' demand for electric power'
To see the other types of publications on this topic, follow the link: Consumers' demand for electric power.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Consumers' demand for electric power.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Tretyakov, Evgeny. "Demand management by active consumers in intelligent electric power systems." E3S Web of Conferences 157 (2020): 05006. http://dx.doi.org/10.1051/e3sconf/202015705006.
Full textAbstract:
The approaches to demand management by active consumers through forming a given schedule of power consumption in the required period of time based on the solution of the optimization problem in the form of maximizing the power of connected controlled electric receivers of various types are presented. The model of demand management by active consumers is justified, taking into account the following factors: load sensitivity for connecting a transformer substation to a change in consumer load; load priority; consistent load reduction levels with flexible performance and power control; permissible set of electric receivers in accordance with the technological process, network schedule, other logical conditions corresponding to adjacency lists. An algorithm has been developed for limiting power on the part of active consumers based on the widespread use of digital data processing technologies, modern technical means of measurement, control and switching of end consumers in real time. The presented research results indicate the validity of the demand management method by active consumers in the normal mode of intelligent electric power systems and the possibility of its practical implementation in an industrial enterprise with reference to the technological process.
2
Tretyakov, Evgeny. "Demand management by active consumers in intelligent electric power systems." E3S Web of Conferences 164 (2020): 10004. http://dx.doi.org/10.1051/e3sconf/202016410004.
Full textAbstract:
The approaches to demand management by active consumers through forming a given schedule of power consumption in the required period of time based on the solution of the optimization problem in the form of maximizing the power of connected controlled electric receivers of various types are presented. The model of demand management by active consumers is justified, taking into account the following factors: load sensitivity for connecting a transformer substation to a change in consumer load; load priority; consistent load reduction levels with flexible performance and power control; permissible set of electric receivers in accordance with the technological process, network schedule, other logical conditions corresponding to adjacency lists. An algorithm has been developed for limiting power on the part of active consumers based on the widespread use of digital data processing technologies, modern technical means of measurement, control and switching of end consumers in real time. The presented research results indicate the validity of the demand management method by active consumers in the normal mode of intelligent electric power systems and the possibility of its practical implementation in an industrial enterprise with reference to the technological process.
3
Gull, Muhammad S., Nasir Mehmood, Huzaifa Rauf, Muhammad Khalid, and Naveed Arshad. "Soft Load Shedding Based Demand Control of Residential Consumers." Electronics 11, no. 4 (February 16, 2022): 615. http://dx.doi.org/10.3390/electronics11040615.
Full textAbstract:
Power generation and consumption is an instantaneous process and maintaining the balance between demand and supply is crucial since the demand and supply mismatch leads to various risks like over-investment, over-generation, under-generation, and the collapse of the power system. Therefore, the reduction in demand and supply mismatch is critical to ensure the safety and reliability of power system operation and economics. A typical and common approach, called full load shedding (FLS), is practiced in cases where electric power demand exceeds the available generation. FLS operation alleviates the power demand by cutting down the load for an entire area or region, which results in several challenges and problems for the utilities and consumers. In this study, a demand-side management (DSM) technique, called Soft-load shedding (SLS), is proposed, which uses data analytics and software-based architecture, and utilizes the real-world time-series energy consumption data available at one-minute granularity for a diversified group of residential consumers. The procedure is based on pattern identification extracted from the dataset and allocates a certain quota of power to be distributed on selected consumers such that the excessive demand is reduced, thereby minimizing the demand and supply mismatch. The results show that the proposed strategy obtains a significant reduction in the demand and supply mismatch such that the mismatch remains in the range of 10–15%, especially during the period where demand exceeds generation, operating within the utility constraints, and under the available generation, to avoid power system failure without affecting any lifeline consumer, with a minimum impact on the consumer’s comfort.
4
Hu, Yu-Chen, Yu-Hsiu Lin, and Harinahalli Lokesh Gururaj. "Partitional Clustering-Hybridized Neuro-Fuzzy Classification Evolved through Parallel Evolutionary Computing and Applied to Energy Decomposition for Demand-Side Management in a Smart Home." Processes 9, no. 9 (August 29, 2021): 1539. http://dx.doi.org/10.3390/pr9091539.
Full textAbstract:
The key advantage of smart meters over rotating-disc meters is their ability to transmit electric energy consumption data to power utilities’ remote data centers. Besides enabling the automated collection of consumers’ electric energy consumption data for billing purposes, data gathered by smart meters and analyzed through Artificial Intelligence (AI) make the realization of consumer-centric use cases possible. A smart meter installed in a domestic sector of an electrical grid and used for the realization of consumer-centric use cases is located at the entry point of a household/building’s electrical grid connection and can gather composite/circuit-level electric energy consumption data. However, it is not able to decompose its measured circuit-level electric energy consumption into appliance-level electric energy consumption. In this research, we present an AI model, a neuro-fuzzy classifier integrated with partitional clustering and metaheuristically optimized through parallel-computing-accelerated evolutionary computing, that performs energy decomposition on smart meter data in residential demand-side management, where a publicly available UK-DALE (UK Domestic Appliance-Level Electricity) dataset is used to experimentally test the presented model to classify the On/Off status of monitored electrical appliances. As shown in this research, the presented AI model is effective at providing energy decomposition for domestic consumers. Further, energy decomposition can be provided for industrial as well as commercial consumers.
5
Son, Namrye, Seunghak Yang, and Jeongseung Na. "Deep Neural Network and Long Short-Term Memory for Electric Power Load Forecasting." Applied Sciences 10, no. 18 (September 17, 2020): 6489. http://dx.doi.org/10.3390/app10186489.
Full textAbstract:
Forecasting domestic and foreign power demand is crucial for planning the operation and expansion of facilities. Power demand patterns are very complex owing to energy market deregulation. Therefore, developing an appropriate power forecasting model for an electrical grid is challenging. In particular, when consumers use power irregularly, the utility cannot accurately predict short- and long-term power consumption. Utilities that experience short- and long-term power demands cannot operate power supplies reliably; in worst-case scenarios, blackouts occur. Therefore, the utility must predict the power demands by analyzing the customers’ power consumption patterns for power supply stabilization. For this, a medium- and long-term power forecasting is proposed. The electricity demand forecast was divided into medium-term and long-term load forecast for customers with different power consumption patterns. Among various deep learning methods, deep neural networks (DNNs) and long short-term memory (LSTM) were employed for the time series prediction. The DNN and LSTM performances were compared to verify the proposed model. The two models were tested, and the results were examined with the accuracies of the six most commonly used evaluation measures in the medium- and long-term electric power load forecasting. The DNN outperformed the LSTM, regardless of the customer’s power pattern.
6
Tretyakov, Evgeny. "Advanced methods of transportation and distribution of electrical power in smart power grids of railways." MATEC Web of Conferences 239 (2018): 01010. http://dx.doi.org/10.1051/matecconf/201823901010.
Full textAbstract:
The relevance of the work is determined by the need to improve the electrical distribution grids of railways on the basis of digital technologies. The article presents advanced methods of transportation and distribution of electric power in smart power grids of railways based on multi-agent control. The analysis of the power supply system for stationary railroad consumers was performed and advanced ways of their development were defined. These methods should provide increased speed, adaptive determination of restrictions on using electric power equipment, management of mode parameters, sectioning and power flow modes in electrical distribution grids, restoration of power supply after emergency events. The method of adaptive control of transportation and distribution of electric energy in the power supply system of stationary railway consumers is developed based on the hierarchical structure of IEC 61850. This method takes into account the coordination of managing and local controllers in the data exchange environment, the control results and the variable area of responsibility of controllers and their division according to their functional purpose based on the multi-agent approach. The method of power flow control was developed to reduce power losses, increase the capacity of transport channels and ensure the restoration of the normal mode of the electric network by reconfiguring it and controlling active elements based on graph theory. The method takes into account the expected daily load curve, limits on the demand for capacity by active consumers and the possibility of a closed mode of electrical network operation through controlled cross-sections. The simulation results presented on the test circuit have showed the feasibility and efficiency of the proposed approaches.
7
Marangoni, Filipe, Leandro Magatão, and Lúcia Valéria Ramos de Arruda. "Demand Response Optimization Model to Energy and Power Expenses Analysis and Contract Revision." Energies 13, no. 11 (June 1, 2020): 2803. http://dx.doi.org/10.3390/en13112803.
Full textAbstract:
This paper proposes a mathematical model based on mixed integer linear programming (MILP). This model aids the decision-making process in local generation use and demand response application to power demand contract adequacy by Brazilian consumers/prosumers. Electric energy billing in Brazil has some specificities which make it difficult to consider the choice of the tariff modality, the determination of the optimal contracted demand value, and demand response actions. In order to bridge this gap, the model considers local generation connected to the grid (distributed generation) and establishes an optimized solution indicating power energy contract aspects and the potential reduction in expenses for the next billing period (12 months). Different alternative sources already available or of interest to the consumer can be considered. The proposed mathematical model configures an optimization tool for the feasibility analysis of local generation use and, concomitantly, (i) checking the tariff modality, (ii) revising the demand contract, and (iii) suggesting demand response actions. The presented result shows a significant reduction in the energy and power expenses, which confirms the usefulness of this proposal. In the end, the optimized answers promote benefits for both, the consumer/prosumer and the electric utility.
8
Joshi, Govind, and Salman Mohagheghi. "Optimal Operation of Combined Energy and Water Systems for Community Resilience against Natural Disasters." Energies 14, no. 19 (September 26, 2021): 6132. http://dx.doi.org/10.3390/en14196132.
Full textAbstract:
One of the most critical challenges for modern power systems is to reliably supply electricity to its consumers during and in the aftermath of natural disasters. As our dependence on electrical power has increased over the years, long-term power outages can lead to devastating impacts on affected communities. Furthermore, power outages can halt the operation of water treatment plants, leading to shortages in clean water, which is essential during post-disaster recovery. One way to address this is to temporarily reconfigure power and water networks into localized networks, i.e., electric microgrids and water micro-nets, that utilize local resources to supply local demand independently of the main power grid and/or water network. Utilizing distributed energy resources such as wind and solar and treating wastewater locally for potable reuse can provide the operational flexibility for such systems to operate sustainably. However, due to uncertainties in both renewable energy generation and electric/water consumption, ensuring sustainable operation is a challenging task. In this paper, an optimal operational strategy is proposed for an islanded microgrid/micro-net, considering the stochastic nature of renewable energy resources, electric demand, and water demand. An energy storage system is modeled to address the uncertainty in power generation and demand, in conjunction with local water storage and wastewater treatment to accommodate variable water demands. A two-stage stochastic programming model is formulated and solved to determine an optimal operation strategy for the combined system.
9
Diamenu, Godwin. "Statistical Analysis of Electric Power Distribution Grid Outages." European Journal of Engineering and Technology Research 6, no. 3 (April 12, 2021): 27–33. http://dx.doi.org/10.24018/ejers.2021.6.3.2406.
Full textAbstract:
Power systems in general supply consumers with electrical energy as economically and reliably as possible. Reliable electric power systems serve customer loads without interruptions in supply voltage. Electric power generation facilities must produce enough power to meet customer demand. Electrical energy produced and delivered to customers through generation, transmission and distribution systems, constitutes one of the largest consumers markets the world over. The benefits of electric power systems are integrated into the much faster modern life in such extent that it is impossible to imagine the society without the electrical energy. The rapid growth of electric power distribution grids over the past few decades has resulted in a large increment in the number of grid lines in operation and their total length. These grid lines are exposed to faults as a result of lightning, short circuits, faulty equipment, mis-operation, human errors, overload, and aging among others. A fault implies any abnormal condition which causes a reduction in the basic insulation strength between phase conductors or phase conductors and earth, or any earthed screens surrounding the conductors. In this paper, different types of faults that affected the electric power distribution grid of selected operational districts of Electricity Company of Ghana (ECG) in the Western region of Ghana was analyzed and the results presented. Outages due to bad weather and load shedding contributed significantly to the unplanned outages that occurred in the medium voltage (MV) distribution grid. Blown fuse and loose contact faults were the major contributor to unplanned outages in the low voltage (LV) electric power distribution grid.
10
Diamenu, Godwin. "Statistical Analysis of Electric Power Distribution Grid Outages." European Journal of Engineering and Technology Research 6, no. 3 (April 12, 2021): 92–98. http://dx.doi.org/10.24018/ejeng.2021.6.3.2406.
Full textAbstract:
Power systems in general supply consumers with electrical energy as economically and reliably as possible. Reliable electric power systems serve customer loads without interruptions in supply voltage. Electric power generation facilities must produce enough power to meet customer demand. Electrical energy produced and delivered to customers through generation, transmission and distribution systems, constitutes one of the largest consumers markets the world over. The benefits of electric power systems are integrated into the much faster modern life in such extent that it is impossible to imagine the society without the electrical energy. The rapid growth of electric power distribution grids over the past few decades has resulted in a large increment in the number of grid lines in operation and their total length. These grid lines are exposed to faults as a result of lightning, short circuits, faulty equipment, mis-operation, human errors, overload, and aging among others. A fault implies any abnormal condition which causes a reduction in the basic insulation strength between phase conductors or phase conductors and earth, or any earthed screens surrounding the conductors. In this paper, different types of faults that affected the electric power distribution grid of selected operational districts of Electricity Company of Ghana (ECG) in the Western region of Ghana was analyzed and the results presented. Outages due to bad weather and load shedding contributed significantly to the unplanned outages that occurred in the medium voltage (MV) distribution grid. Blown fuse and loose contact faults were the major contributor to unplanned outages in the low voltage (LV) electric power distribution grid.
11
Park, EungSuk, BoRam Kim, SooHyun Park, and Daecheol Kim. "Analysis of the Effects of the Home Energy Management System from an Open Innovation Perspective." Journal of Open Innovation: Technology, Market, and Complexity 4, no. 3 (August 3, 2018): 31. http://dx.doi.org/10.3390/joitmc4030031.
Full textAbstract:
The Home Energy Management System (HEMS) is a system for the efficient electric power consumption of each household. It can provide real-time electricity cost information according to electricity consumption, and households can immediately control their consumption of electricity. In this study, we analyzed the effects of the HEMS on the stability of demand for electric power. To do this, we analyzed the causal relationship between the amounts of electric power generation and consumption, from the system dynamics perspective. From the analysis, we found that in the current structure, the fluctuation of the quantity of demand became large due to the time delay in households recognizing the electric bill and adjusting their electric power consumption. However, when the HEMS was introduced, it could be seen that electric power demand remained stable since consumers could see their electricity bill in real-time and could manage their electricity consumption by themselves.
12
Zhang, Xiao Hong. "Research on the Mathematical Model for the Price Regulation of Power Demand-Side." Advanced Materials Research 189-193 (February 2011): 1218–21. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.1218.
Full textAbstract:
Power Demand-side Management (DSM) originated in the USA and was introduced into China later. As China's rapid economic development, social electric power energy demand is increasing, therefore, strengthen DSM, using reasonable price regulation and guide consumers the rational allocation of electricity methods and structure, so that we can achieve efficient use of power resources. From the perspective of electricity consumers and suppliers, this paper analyzed the relationship between them by constructing mathematical model, expected to provide some theoretical basis and practical guidance for the practice of government and power companies.
13
Dolega, Waldemar. "Development of electric power network infrastructure in aspect of electric energy supply security – case study Poland." E3S Web of Conferences 84 (2019): 02002. http://dx.doi.org/10.1051/e3sconf/20198402002.
Full textAbstract:
In this paper, an analysis of issues related to development of national electric power network infrastructure in aspect of electric energy security is performed. Profile of network infrastructure in area of transmission and distribution is performed. Threats for electric energy supply security connected with transmission and distribution infrastructure are discussed. Both transmission and distribution electric power network are adapted for presently occurred typical conditions of electric energy demand and realization of internal tasks in normal conditions, but can create potential threat for electric energy supply security. In the context of forecasted increase of electric energy demand, inadequate power in National Electric Power System (NEPS) in domestic sources and available through intersystem connections, uneven location of sources and consumers at shortage of proper network transmission capacities, necessity of improvement of quality and electric energy supply reliability to final consumers and intensive development of renewable energy sources, present network infrastructure in area of transmission and distribution will be insufficient. Development of 400 and 220 kV transmission network, 110 kV distribution network especially in area of cities, MV distribution network especially in rural areas and realization of investments for improvement of export-import possibilities of NEPS will be necessary. Challenges for transmission and distribution system operators in area of network development are performed. They concern mainly investment sphere and area connected with preparation and construction of network investments.
14
Singh, Pushpendra, Kedar Sharma, and Akash Talwariya. "Advancement of power generation system by instalment of solar photovoltaic system for multiple wells: A Case Study." Journal of Physics: Conference Series 2208, no. 1 (March 1, 2022): 012009. http://dx.doi.org/10.1088/1742-6596/2208/1/012009.
Full textAbstract:
Abstract This paper proposes the solution for electricity issues in agriculture sector of particular location in Rajasthan. The issues reported about the availability of ground water and availability of Electricity from electric Grid. The study proposes a centralized solar photovoltaic system for available nearby open wells, which are being operated by diesel engine pump-sets, which emits greenhouse gases and pollute the environment. The proposed centralized photovoltaic system will provide power for submersible pump sets. The additional available power can be stored in batteries, utilized for charging the batteries of electrical vehicles or sell back to electric grid. This paper shows the cost analysis for proposed systems that can be applied and effective centralized solar photovoltaic system in the area considered for study. Centralized solar photovoltaic generation supply to different consumers in different slots and may increase the conflict between consumers, demand side management provide suitable solution to consumers is proposed and analyse in future work.
15
Jakowski, Damian, and Marek Dzida. "Increasing Power Supply Safety in the Aspect of Supporting the Renewable Energy Sources by Conventional and Virtual Power Stores." Polish Maritime Research 25, s1 (May 1, 2018): 189–97. http://dx.doi.org/10.2478/pomr-2018-0041.
Full textAbstract:
Abstract This paper presents characteristics and purposefulness of supporting the renewable energy sources (OZE) by means of energy stores. The main emphasis was placed on analysis of virtual energy stores available for implementation in Polish economy conditions. A role which management of Demand Side Response (DSR) may play in balancing Polish electric power system, is discussed. Implementation of such solutions together with conventional energy stores may significantly influence power supply safety by assuring continuity of electric power supply at an acceptable price. Involvement of electric power consumers (DSR) should be one of the basic solutions for power markets in Poland and Europe.
16
Galperova, Elena, and Vasiliy Galperov. "A Methodological Approach to the Assessment of the Impact of Digital Technologies Development in Energy Industry on Electricity Price and Demand in a Region." E3S Web of Conferences 209 (2020): 06006. http://dx.doi.org/10.1051/e3sconf/202020906006.
Full textAbstract:
The relevance of this study is due to the importance of assessing the prospective dynamics and structure of demand for energy carriers when developing and making strategic decisions in the field of energy and economic security of the country and its regions. The advance of digital technology redefines the properties of electric power supply systems, erases the boundary between electric power producers and consumers, and impacts the formation of electricity price and demand in the region. This study presents a method of electricity costing in the regional power system, which serves as an integral part of the approach to assessing the impact of intelligent systems development on the demand for electricity in the region. The approach is unique in that it simulates the behavior of electricity consumers and producers of various types as they pursue their own interests and assesses the impact of this behavior on the demand and price of electricity in the regional power system. Determining the cost of electricity in the system is based on the consistent alignment of the required amount of electricity consumption with the capabilities of producers seeking to achieve their best economic performance. Each producer is described as an optimization model, which is a standalone agent in a multi-agent power system model.
17
Naveen, P., W. Kiing Ing, M. Kobina Danquah, A. S. Sidhu, and A. Abu-Siada. "A Cloud Associated Smart Grid Admin Dashboard." Engineering, Technology & Applied Science Research 8, no. 1 (February 20, 2018): 2499–507. http://dx.doi.org/10.48084/etasr.1702.
Full textAbstract:
Intelligent smart grid system undertakes electricity demand in a sustainable, reliable, economical and environmentally friendly manner. As smart grid involves, it has the liability of meeting the changing consumer needs on the day-to-day basis. Modern energy consumers like to vivaciously regulate their consumption patterns more competently and intelligently than current provided ways. To fulfill the consumers’ needs, smart meters and sensors make the grid infrastructure more efficient and resilient in energy data collection and management even with the ever-changing renewable power generation. Though cloud acts as an outlet for the energy consumers to retrieve energy data from the grid, the information systems available are technically constrained and not user-friendly. Hence, a simple technology enabled utility-consumer interactive information system in the form of a dashboard is presented to cater the electric consumer needs.
18
Dhawale, Dinesh, and Vikram Kumar Kamboj. "Scope of Intelligence Approcahes for Unit Commitment Under Uncertain Sustainable Energy Environment For Effective Vehicle To Grid Operations-A Comprehensive Review." E3S Web of Conferences 184 (2020): 01034. http://dx.doi.org/10.1051/e3sconf/202018401034.
Full textAbstract:
Electric vehicles are getting popularity as these are eco-friendly and could be a part of power sector in the future. Electric Vehicles are the smart hybrid vehicles, which stores electric power during their operation, which could be stored in storage cells. These electric vehicles may be plug-in electric vehicles or battery operated electric vehicles. The concept of aggregators may be utilized, wherein the stored energy in vehicles could be supplied to grid during parking hours .This also facilitate the consumers to sale power during the high power demand and purchase power during low power demand. Thus, a bi-directional flow of power could be possible either from vehicle to grid or vice-versa. A large penetration of electric vehicles could result in increase in power demand which could be compensated by proper coordinated unit commitment and optimization techniques. The increasing load on grid by the impact of demand and trends in small generating units which require proper selection of number of generating units to put in line and other units in off condition calls for the concept of unit commitment. It is the selection of more efficient units to be in service and shutting down the other unit while maintaining all the other constraint constant. This would result in effective power flow in an economic manner, simultaneously maintaining the adequacy and reliability of the system. The proposed research represents the scope of intelligence algorithm for unit commitment problem with effective solution of vehicle to grid operations along with sustainable energy for realistic power system.
19
Boriratrit, Sarunyoo, Chitchai Srithapon, Pradit Fuangfoo, and Rongrit Chatthaworn. "Metaheuristic Extreme Learning Machine for Improving Performance of Electric Energy Demand Forecasting." Computers 11, no. 5 (April 27, 2022): 66. http://dx.doi.org/10.3390/computers11050066.
Full textAbstract:
Electric energy demand forecasting is very important for electric utilities to procure and supply electric energy for consumers sufficiently, safely, reliably, and continuously. Consequently, the processing time and accuracy of the forecast system are essential to consider when applying in real power system operations. Nowadays, the Extreme Learning Machine (ELM) is significant for forecasting as it provides an acceptable value of forecasting and consumes less computation time when compared with the state-of-the-art forecasting models. However, the result of electric energy demand forecasting from the ELM was unstable and its accuracy was increased by reducing overfitting of the ELM model. In this research, metaheuristic optimization combined with the ELM is proposed to increase accuracy and reduce the cause of overfitting of three forecasting models, composed of the Jellyfish Search Extreme Learning Machine (JS-ELM), the Harris Hawk Extreme Learning Machine (HH-ELM), and the Flower Pollination Extreme Learning Machine (FP-ELM). The actual electric energy demand datasets in Thailand were collected from 2018 to 2020 and used to test and compare the performance of the proposed and state-of-the-art forecasting models. The overall results show that the JS-ELM provides the best minimum root mean square error compared with the state-of-the-art forecasting models. Moreover, the JS-ELM consumes the appropriate processing time in this experiment.
20
Aizenberg, Natalia, and Nikolai Voropai. "The Optimal Mechanism Design of Retail Prices in the Electricity Market for Several Types of Consumers." Mathematics 9, no. 10 (May 19, 2021): 1147. http://dx.doi.org/10.3390/math9101147.
Full textAbstract:
In this paper, we discuss the demand side management (DSM) problem: how to incentivize a consumer to equalize the load during the day through price-dependent demand. Traditionally, the retail market offers several electricity payment schemes. A scheme is effective when the different tariffs satisfy different consumers. At the same time, the existing and generally accepted retail pricing schemes can lead to an "adverse selection" problem when all consumers choose the same price, thereby, reducing the possible general welfare. We propose an optimal design of pricing mechanisms, taking into account the interests of the electricity supplier and different types of consumers. The results of our work are that the optimal mechanism is implemented simultaneously for several periods, including the case when the ratio of types of consumers in periods changes. In addition, the mechanism proposed by us, in contrast to the studies of other researchers, provides an equilibrium close to the socially optimal maximum. We describe the implementation algorithm of the mechanism and provide examples of its action in the electric power system with different types and numbers of consumers.
21
Ogorodnikov, Nikita. "Electricity demand management within the retail electricity market in Russia." E3S Web of Conferences 289 (2021): 01006. http://dx.doi.org/10.1051/e3sconf/202128901006.
Full textAbstract:
Demand side management is an important tool for ensuring the flexibility of the electric power systems, as it maintains and regulates the balance of generation and consumption of electric energy and has a system-wide effect, which is formed by lowering electricity prices for consumers and optimizing the load and structure of generating and electric grid capacities. The article is devoted to the problem of managing the demand for electricity consumption within the framework of the retail electricity market in Russia. The author identifies and summarizes the existing demand management tools. The article substantiates the need for the development and implementation of innovative tools and mechanisms for managing the demand for electricity consumption.
22
Zhuo, Yang, Wang Ju, and Tang Jie. "Research on Supply Chain Cooperation Optimization Model of Electric Heating Market Replacing Traditional Coal Power Generation." Tobacco Regulatory Science 7, no. 6 (November 3, 2021): 5824–35. http://dx.doi.org/10.18001/trs.7.6.64.
Full textAbstract:
Objectives: The rapid development of central heating service in China mostly uses fossil fuels such as coal for production. The market competitiveness of new energy such as wind and solar energy to replace coal to produce heat energy for heating is relatively poor. Under the multiple requirements of energy security, ambient air quality and low carbon, electric heating is practicable because of its flexible use, adapts to the differential demand of consumers for heat, which energy supply can improve efficiency with the progress of power generation technology and so on. On the basis of case study data and results of residential users, companies and public buildings adopting electric heating technology, the analysis of consumer demand, supply chain structure and market relationship in China's electric heating market, this paper discusses the supply chain cooperation model by using revenue sharing contract mode. The results show that the performance of the benefit sharing ratio in the data simulation is acceptable when the revenue sharing contract is used in the supply chain. This model can promote the spontaneous and effective operation of the market, and help the local government in China to get rid of the embarrassment of the continuous subsidy.
23
Khederzadeh, Mojtaba, and Mohammad Khalili. "High Penetration of Electrical Vehicles in Microgrids: Threats and Opportunities." International Journal of Emerging Electric Power Systems 15, no. 5 (October 1, 2014): 457–69. http://dx.doi.org/10.1515/ijeeps-2014-0083.
Full textAbstract:
Abstract Given that the microgrid concept is the building block of future electric distribution systems and electrical vehicles (EVs) are the future of transportation market, in this paper, the impact of EVs on the performance of microgrids is investigated. Demand-side participation is used to cope with increasing demand for EV charging. The problem of coordination of EV charging and discharging (with vehicle-to-grid (V2G) functionality) and demand response is formulated as a market-clearing mechanism that accepts bids from the demand and supply sides and takes into account the constraints put forward by different parts. Therefore, a day-ahead market with detailed bids and offers within the microgrid is designed whose objective is to maximize the social welfare which is the difference between the value that consumers attach to the electrical energy they buy plus the benefit of the EV owners participating in the V2G functionality and the cost of producing/purchasing this energy. As the optimization problem is a mixed integer nonlinear programming one, it is decomposed into one master problem for energy scheduling and one subproblem for power flow computation. The two problems are solved iteratively by interfacing MATLAB with GAMS. Simulation results on a sample microgrid with different residential, commercial and industrial consumers with associated demand-side biddings and different penetration level of EVs support the proposed formulation of the problem and the applied methods.
24
Talwariya, Akash, Pushpendra Singh, and Mohan Kolhe. "Non-cooperative game theory based stepwise power tariff model using Monte-Carle simulation for agricultural consumers." Open Agriculture 4, no. 1 (August 21, 2019): 418–25. http://dx.doi.org/10.1515/opag-2019-0041.
Full textAbstract:
AbstractIn the present study the concept of non-cooperative game theory is proposed in the retail electricity market for introducing stepwise power tariff model (SPT) for agricultural consumers. The objective of the paper is to increase the energy generation through green energy generation sources (GEGS), introduction of plug-in hybrid electric vehicles, education of families, standard wiring and appliance efficiency in tariffs for agricultural consumers with non-cooperative game theory. Agricultural consumers are able to generate a huge amount of electricity through GEGS and are able to control the consumption in their own way, and the non-cooperative game theory is introduced. Energy consumption pattern varies with respect to time during off-peak load period to peak load period; during the peak load period the demand is high as compared to off peak load hour duration energy consumption for the consumers and policy makers interrupting the energy supply during peak hours for agricultural consumers. To maintain the balance between generation and consumption, energy saving is essentially required and needs to maintain the consumption patterns and increase the penetration level of distributed generation at the agricultural consumer end due to availability of land. This paper proposes an algorithm for a demand response methodology using SPT with non-cooperative game theory model based on monthly energy consumption to maintain the balance. The uncertainty about energy generation through GEGS taken in consideration using Monte-Carlo simulation (MCS). Simulation results obtained by the proposed methodology are compared with the conventional methodology of energy tariff used in India and provide better results for active consumers and generate a considerable amount of electricity through GEGS.
25
Cahyo, Mukti Dwi, Sri Heranurweni, and Harmini Harmini. "PREDIKSI BEBAN ENERGI LISTRIK APJ KOTA SEMARANG MENGGUNAKAN METODE RADIAL BASIS FUNCTION (RBF)." Elektrika 11, no. 2 (October 8, 2019): 21. http://dx.doi.org/10.26623/elektrika.v11i2.1699.
Full textAbstract:
Electric power is one of the main needs of society today, ranging from household consumers to industry. The demand for electricity increases every year. So as to achieve adjustments between power generation and power demand, the electricity provider (PLN) must know the load needs or electricity demand for some time to come. There are many studies on the prediction of electricity loads in electricity, but they are not specific to each consumer sector. One of the predictions of this electrical load can be done using the Radial Basis Function Artificial Neural Network (ANN) method. This method uses training data learning from 2010 - 2017 as a reference data. Calculations with this method are based on empirical experience of electricity provider planning which is relatively difficult to do, especially in terms of corrections that need to be made to changes in load. This study specifically predicts the electricity load in the Semarang Rayon network service area in 2019-2024. The results of this Artificial Neural Network produce projected electricity demand needs in 2019-2024 with an average annual increase of 1.01% and peak load in 2019-2024. The highest peak load in 2024 and the dominating average is the household sector with an increase of 1% per year. The accuracy results of the Radial Basis Function model reached 95%.
26
El Gharbi, A. "A Distributed Control Approach for Demand Response in Smart Grids." Engineering, Technology & Applied Science Research 12, no. 1 (February 12, 2022): 8129–35. http://dx.doi.org/10.48084/etasr.4634.
Full textAbstract:
The smart grid is a new concept that has been developed during recent years to improve the intelligence and efficiency of electric power system management. Traditional electricity systems are combined and integrated with information technology, communication technology, and intelligent control technology in the smart grid. Demand Response (DR) refers to the changes in consumers' electricity consumption behavior in response to dynamic pricing or financial incentives. Based on the control manner, DR methods are classified as centralized or distributed. In distributed techniques, customers communicate with the other consumers and provide data to the power utility about the overall use. In this paper, we focus on the distributed approach of DR using the shifting method for a short-term horizon. To be more specific, three well-known solutions were studied: the Resource Allocation with Legitimate Claims, the Constrained Fair-Splitting Dispatch, and Real-Time Pricing. Finally, we compare the different techniques of DR distributed approaches based on the control mechanism.
27
Strielkowski, Wadim, Lubomír Civín, Elena Tarkhanova, Manuela Tvaronavičienė, and Yelena Petrenko. "Renewable Energy in the Sustainable Development of Electrical Power Sector: A Review." Energies 14, no. 24 (December 7, 2021): 8240. http://dx.doi.org/10.3390/en14248240.
Full textAbstract:
The electrical power sector plays an important role in the economic growth and development of every country around the world. Total global demand for electric energy is growing both in developed and developing economies. The commitment to the decarbonization of economies, which would mean replacing fossil fuels with renewable energy sources (RES) as well as the electrification of transport and heating as a means to tackle global warming and dangerous climate change, would lead to a surge in electricity consumption worldwide. Hence, it appears reasonable that the electric power sector should embed the principles of sustainable development into its functioning and operation. In addition, events such as the recent European gas crisis that have emerged as a result of the massive deployment of renewables need to be studied and prevented. This review aims at assessing the role of the renewable energy in the sustainable development of the electrical power sector, focusing on the energy providers and consumers represented both by businesses and households that are gradually becoming prosumers on the market of electric energy. Furthermore, it also focuses on the impact of renewables on the utility side and their benefits for the grid. In addition, it identifies the major factors of the sustainable development of the electrical power sector.
28
Korepanov, Vsevolod, and Tatiana Vaskovskaya. "Analysis of pricing mechanisms in a microgrid with active electric energy storages." E3S Web of Conferences 209 (2020): 02017. http://dx.doi.org/10.1051/e3sconf/202020902017.
Full textAbstract:
A model of power market with a simple market clearing price mechanism on microgrid is considered. Market participants are consumers, prosumers with energy storage systems (ESS), and the power company as a guaranteed supplier. Prosumers charge their ESS in the first off-peak period with low prices from the power company and can decrease their demand or sell energy in the market through discharging the ESS in the second peak period. The strategic behavior of participants and their influences on a system state are postulated as the goal of work. Some use cases and model elements are discussed.
29
Rušeljuk, Pavel, Kertu Lepiksaar, Andres Siirde, and Anna Volkova. "Economic Dispatch of CHP Units through District Heating Network’s Demand-Side Management." Energies 14, no. 15 (July 28, 2021): 4553. http://dx.doi.org/10.3390/en14154553.
Full textAbstract:
Optimisation of heat and electrical load distribution, where the objective function is the maximum efficiency of the CHP unit for a given load range, can be done considering the limitations of electrical power and the heat load. Simulating a real CHP unit with a district heating network shows that demand-side management can improve the overall economic efficiency of the CHP plant and increase the unit’s operating range in the electricity spot market. Economic dispatch makes it possible to determine a reasonable additional increase in the electric power of the CHP unit, and to optimise the supply temperature and mass flow of the district heating network. The results obtained and the analysis performed indicate that the proposed methodology provides logical results and can be used to calculate the efficiency indicators of the cogeneration of electrical and thermal energy. The problem of optimising the operating mode of the CHP unit was solved, which allows us to determine the optimal additional increase in the unit’s electrical load at a given heat load of consumers, which on average increases the CHP unit’s efficiency up to an additional 1.5%.
30
Naser, Beate, Franziska Schäfer, and Jörg Franke. "An Energy Ontology Focusing on Demand Side Management in Smart Homes." Advanced Engineering Forum 19 (October 2016): 124–31. http://dx.doi.org/10.4028/www.scientific.net/aef.19.124.
Full textAbstract:
By increasing the share of renewable energy sources, the volatility of available energy is rising. More and more fluctuating power generation by solar power plants and wind turbines has to be integrated into the power grid. Demand side management (DSM) represents one possible solution to achieve this goal by including energy production and energy consumption simultaneously. In this paper, we especially focus on the field of electric energy in smart homes. Considering the implementation of different DSM devices, an ontology-based approach can serve as a conceptual foundation for a necessary knowledge base. We propose an advanced energy ontology for smart homes, integrating important aspects for a successful DSM. We describe how power producers, storages and consumers are represented in our ontology. Finally, we show the scenario-based utilization of our approach.
31
Lim, Keumju, Justine Jihyun Kim, and Jongsu Lee. "Forecasting the future scale of vehicle to grid technology for electric vehicles and its economic value as future electric energy source: The case of South Korea." Energy & Environment 31, no. 8 (January 7, 2020): 1350–66. http://dx.doi.org/10.1177/0958305x19898283.
Full textAbstract:
With the world seeking ways to cope with climate change, the interest in and demand for electric vehicles are increasing as part of the efforts to resolve the issue of fine dust, especially in South Korea. The Korean government has consistently announced plans to promote electric vehicles as a means of transportation by providing benefits such as subsidies for electric vehicle purchase and expansion of charging infrastructure. Meanwhile, as electric vehicles continue to grow in number, the energy industry has become attentive to its role as a resource for power generation through vehicle to grid technology. This study analyzes electric vehicle consumer preferences using the discrete choice experiment (DCE) and found that there exists a clear nested structure in Korean consumers’ choice of vehicle. The study also estimates the amount of vehicle to grid electricity supply in the power market and calculates not only national but also individual economic benefit of electric vehicle owners participating in vehicle to grid services based on the estimated amount of electricity supplied. The results of scenario analysis indicate that the estimated electric vehicle supply in Korea will be about 560,000 units cumulatively and that the vehicle to grid electric vehicle power supply scale will reach 1.81 GW by 2030. The estimation shows that the economic benefit of vehicle to grid at the national power market level is 50.9 billion KRW per year, while the economic benefit at an individual level (per vehicle) is 104,151 KRW.
32
Roy, Souvik. "ENERGY MANAGEMENT SYSTEMS FOR ELECTRIC VEHICLES AND MICROGRIDS." International Journal of Students' Research in Technology & Management 6, no. 1 (January 3, 2018): 01–05. http://dx.doi.org/10.18510/ijsrtm.2018.611.
Full textAbstract:
The purpose of study Smart Grid is the evolutions of our electric grid.Our electric components are developing day by day. The purpose of research on Microgrid systems are the integration of renewable energy sources (RES),Enhanced reliability, Reduce peak demand, Smarter consumers, Lower total energy consumption, which outlines power systems interconnection differentVitalityera components (supplyside)with vitality utilization components (request side) and capacity gadgets problem. The integration of RESs and ESSs in a microgrid is studied and analyzed by several authors for different purposes.Create and apply regular cost and advantages technique over all Smart Grid field ventures.
The method employs including underlying algorithms and assumptions.Ensure that this methodology can easily accommodate algorithms and assumptions .Develop business case for investors, regulators and customers.
This project has some limitations like it takes more time to configure all over the worlds, so expensive for the consumers. The objective is to keep end-user with more reliable and increased power availability and hence keeping higher priority load connected.
This study never been done before. This study also was provided current information about smart grid and electric vehicles.
33
Chukreyev, Mikhail. "Power price in the conditions of market relations UES of Russia." E3S Web of Conferences 216 (2020): 01047. http://dx.doi.org/10.1051/e3sconf/202021601047.
Full textAbstract:
In modern conditions of market relations in the electric power industry, a mechanism is needed to regulate the purchase and sale of power, which should not lead to a deterioration in the EPS reliability. Competitive power take-off became the main component of this mechanism. Within its framework, nuclear power plants, hydroelectric power plants, new power units, as well as thermal power plants, which are necessary for heat supply to consumers, are mandatory selected. The article examines the process of price formation for capacity, its relationship with demand, shows the main features that affect its final indicators.
34
Veloso, Artur Felipe da Silva, José Valdemir Reis Júnior, Ricardo de Andrade Lira Rabelo, and Jocines Dela-flora Silveira. "HyDSMaaS: A Hybrid Communication Infrastructure with LoRaWAN and LoraMesh for the Demand Side Management as a Service." Future Internet 13, no. 11 (October 26, 2021): 271. http://dx.doi.org/10.3390/fi13110271.
Full textAbstract:
Seeking to solve problems in the power electric system (PES) related to exacerbated and uncontrolled energy consumption by final consumers such as residences, condominiums, public buildings and industries, electric power companies (EPC) are increasingly seeking new information and communication technologies (ICTs) to transform traditional electric power distribution networks into smart grids (SG). With this implementation, PES will be able to remotely control electric power consumption as well as monitor data generated by smart meters (SM). However, Internet-of-Things (IoT) technologies will enable all this to happen quickly and at low cost, since they are low-cost devices that can be deployed quickly and at scale in these scenarios. With this in mind, this work aimed to study, propose, and implement a hybrid communication infrastructure with LoRaWAN and LoraMesh for the demand-side management as a service (HyDSMaaS) using IoT devices such as long range (LoRa) to provide an advanced metering infrastructure (AMI) capable of performing all these applications as a service offered by EPC to end consumers. Additionally, services such as demand-side management (DSMaaS) can be used in this infrastructure. From the preliminary results it was found that the LoRaWAN network achieved a range of up to 2.35 km distance and the LoRaMESH one of 600 m; thus, the latter is more suitable for scenarios where there is little interference and the SMs are at long distances, while the other is used for scenarios with greater agglomeration of nearby SMs. Considering the hybridized scenario between LoraWAN and LoRaMESH, it can be seen that the implementation possibilities increase, since its range was approximately 3 km considering only one hop, and it can reach 1023 devices present in a mesh network. Thus, it was possible to propose the actual implementation of LoRaWAN and LoRaMESH protocols as well as the hybridization of the two protocols for HyDSMaaS. Additionally, the results obtained are exclusively from Radioenge’s LoRa technology, which can be further improved in the case of using more powerful equipment.
35
Senchenko, V. A., and T. T. Kaverzneva. "PROBLEMS OF COMMUNICATION LINES AND ELECTRIC TRANSMISSION LINES ON GENERAL SUPPORT IN CITY CONDITIONS." Construction and Geotechnics 10, no. 3 (December 15, 2019): 76–86. http://dx.doi.org/10.15593/2224-9826/2019.3.08.
Full textAbstract:
In the development of the energy industry in Russia, there has been a steady growth in the demand for electrical energy. Moreover, a significant increase in electricity consumption accounts for large cities. In rural areas, electricity consumption is mainly decreasing, which can be explained by the tendency of the outflow of the working-age population from the village and villages to the cities due to the lack of permanent work. However, when investing in the agro-industrial complex, with the development of farms, the demand for electricity also increases in villages. In addition, it is necessary to note the large-scale introduction of digital television and modern means of communication in holiday villages and villages. Thus, in the last decade, the demand for electricity throughout the country has increased significantly, which has led to an increase in communications and communications services, as well as consumers of these services. Since the easiest and most cost-effective way to provide consumer services and power supply is to lay down overhead lines and overhead power lines, it often happens that new customers are connected to already existing old (sometimes heavily worn out) lines. In addition to possible overloads of lines, a “tangle” of wires is formed at the intersections of overhead communication lines (VLS) and overhead transmission lines (VLE), which makes it difficult to carry out subsequent installation and repair work. The appearance of such a "tangle" creates an additional risk of injury to the worker when working at height. In order to reduce the complexity of maintenance and increase safety during operation, installation and maintenance of communication lines and power lines, a constructive solution has been proposed in junction intersections in the form of a traverse, which allows, firstly, to provide a greater number of attachment points and, secondly, to separate communication lines and power lines on different planes.
36
Bons, Pieter C., Aymeric Buatois, Guido Ligthart, Frank Geerts, Nanda Piersma, and Robert van den Hoed. "Impact of Smart Charging for Consumers in a Real World Pilot." World Electric Vehicle Journal 11, no. 1 (March 6, 2020): 21. http://dx.doi.org/10.3390/wevj11010021.
Full textAbstract:
A smart charging profile was implemented on 39 public charging stations in Amsterdam on which the current level available for electric vehicle (EV) charging was limited during peak hours on the electricity grid (07:00–08:30 and 17:00–20:00) and was increased during the rest of the day. The impact of this profile was measured on three indicators: average charging power, amount of transferred energy and share of positively and negatively affected sessions. The results are distinguished for different categories of electric vehicles with different charging characteristics (number of phases and maximum current). The results depend heavily on this categorisation and are a realistic measurement of the impact of smart charging under real world conditions. The average charging power increased as a result of the new profile and a reduction in the amount of transferred energy was detected during the evening hours, causing outstanding demand which was solved at an accelerated rate after limitations were lifted. For the whole population, 4% of the sessions were positively affected (charged a larger volume of energy) and 5% were negatively affected. These numbers are dominated by the large share of plug-in hybrid electric vehicles (PHEVs) in Amsterdam which are technically not able to profit from the higher current levels. For new generation electric vehicles, 14% of the sessions were positively affected and the percentage of negatively affected sessions was 5%.
37
Alhasnawi, Bilal, and Basil Jasim. "Adaptive Energy Management System for Smart Hybrid Microgrids." 3D SCEEER Conference sceeer, no. 3d (July 1, 2020): 73–85. http://dx.doi.org/10.37917/ijeee.sceeer.3rd.11.
Full textAbstract:
The energy management will play an important role in the future smart grid by managing loads in an intelligent way. Energy management programs, realized via House Energy Management systems (HEMS) for smart cities, provide many benefits; consumers enjoy electricity price savings, and utility operates at reduced peak demand. This paper proposed an adaptive energy management system for islanded mode and grid-connected mode. In this paper, a hybrid system that includes distribution electric grid, photovoltaics, and batteries are employed as energy sources in the residential of the consumer in order to meet the demand. The proposed system permits coordinated operation of distributed energy resources to concede necessary active power and additional service whenever required. This paper uses home energy management system which switches between the distributed energy and the grid power sources. The home energy management system incorporates controllers for maximum power point tracking, battery charge and discharge and inverter for effective control between different sources depending upon load requirement and availability of sources at maximum powerpoint. Also, in this paper, the Maximum Power Point Tracking (MPPT) technique is applied to the photovoltaic station to extract the maximum power from hybrid power system during variation of the environmental conditions. The operation strategy of energy storage systems is proposed to solve the power changes from photovoltaics and houses loads fluctuations locally, instead of reflecting those disturbances to the utility grid. Furthermore, the energy storage systems energy management scheme will help to achieve the peak reduction of the houses daily electrical load demand. The simulation results have verified the effectiveness and feasibility of the introduced strategy and the capability of the proposed controller for a hybrid microgrid operating in different modes.
38
Apena, Waliu Olalekan. "A Knowledge-Based Demand Side Management: Interruptible Direct Load Approach." European Journal of Engineering Research and Science 2, no. 6 (June 30, 2017): 71. http://dx.doi.org/10.24018/ejers.2017.2.6.399.
Full textAbstract:
The study focussed on managing electrical energy supplied to consumers from distribution end through initial knowledge on data acquisition and embedded system. It was achieved by controlling the inductive loads at the consumer premise. The study re-shaped the load and energy demand curve by cycling customers’ inductive loads which are prone to drawing high currents such as air conditioner and water heaters. Data from power utilities were gathered and analysed using tools to generate waveform pattern for energy consumption. Mathematical models for air conditioners and water heaters were derived in order to remotely control the appliances with the aids of embedded system implemented on the consumer premise.
39
Apena, Waliu Olalekan. "A Knowledge-Based Demand Side Management: Interruptible Direct Load Approach." European Journal of Engineering and Technology Research 2, no. 6 (June 30, 2017): 71–73. http://dx.doi.org/10.24018/ejeng.2017.2.6.399.
Full textAbstract:
The study focussed on managing electrical energy supplied to consumers from distribution end through initial knowledge on data acquisition and embedded system. It was achieved by controlling the inductive loads at the consumer premise. The study re-shaped the load and energy demand curve by cycling customers’ inductive loads which are prone to drawing high currents such as air conditioner and water heaters. Data from power utilities were gathered and analysed using tools to generate waveform pattern for energy consumption. Mathematical models for air conditioners and water heaters were derived in order to remotely control the appliances with the aids of embedded system implemented on the consumer premise.
40
Molla1, Tesfahun, Baseem Khan1*, and Pawan Singh2. "A comprehensive analysis of smart home energy management system optimization techniques." Journal of Autonomous Intelligence 1, no. 1 (October 14, 2018): 15. http://dx.doi.org/10.32629/jai.v1i1.14.
Full textAbstract:
Development of smart grid technology provides an opportunity to various consumers in context for scheduling their energy utilization pattern by themselves. The main aim of this whole exercise is to minimize energy utilization and reduce the peak to average ratio (PAR) of power. The two way flow of information between electric utilities and consumers in smart grid opened new areas of applications. The main component is this management system is energy management controller (EMC), which collects demand response (DR) i.e. real time energy price from various appliances through the home gateway (HG). An optimum energy scheduling pattern is achieved by EMC through the utilization of DR information. This optimum energy schedule is provided to various appliances via HG. The rooftop photovoltaic system used as local generation micro grid in the home and can be integrated to the national grid. Under such energy management scheme, whenever solar generation is more than the home appliances energy demand, extra power is supplied back to the grid. Consequently, different appliances in consumer premises run in the most efficient way in terms of money. Therefore this work provides the comprehensive review of different smart home appliances optimization techniques, which are based on mathematical and heuristic one.
41
Zotova, Elizaveta, Vladimir Anisimov, Evgenii Anisimov, Daria Melnik, and Anatoly Chernysh. "A model for setting up development programs for logistics systems in the electric power industry to achieve electric power security." E3S Web of Conferences 258 (2021): 02027. http://dx.doi.org/10.1051/e3sconf/202125802027.
Full textAbstract:
The electric power security of the Russian Federation is one of the most important factors influencing the economy and social sphere, as well as the living conditions and activities of Russian citizens. Thus, one of the global issues concerning electric power security is to keep a balance between the demand for resources and the lack of ability of the corresponding logistic systems to provide continuity and synchronize the processes of production, distribution and delivery of enough electric power to consumers. The urgent need for purposeful development of logistics systems in the electric power industry and to ensure electric power security determines the relevance of improving the methodological tools for taking rational decisions in planning and managing this process. This paper is aimed at improving these tools. It proposes a generalized structure of the model and an algorithm for solving the problem related to forming the best variant of the logistics system development program in the electric power industry. The minimization of financial costs is used as a criterion of optimality in the model. To take into account the uncertainty inherent in the development of the logistics system in the electric power industry, the it is necessary to set the intervals of the possible costs of the project components. To resolve this problem an iterative algorithm is proposed so that an expedient variant of the project is formed consistently.
42
G. A, Dr Raghu, and Dr Mala K. M. "Transition in Automotive Sector from Fuel-Based Engines to Electric Vehicles: A Study on Consumer Attitude towards Electric Vehicles." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 568–87. http://dx.doi.org/10.22214/ijraset.2022.40606.
Full textAbstract:
Abstract: Electric Vehicles have advanced significantly in quite your time, owing partially to decreasing battery costs. Yet EVs remain more costly than gasoline fueled vehicles over their useful life .This research paper analyzes the additional advances which can be needed ,if electric vehicles are to significantly penetrate the passenger vehicle fleet during this low pricing market. This has further been divided into 3sub parts: 1) Battery Prices 2) Will Declining Battery Costs Make EVs competitive? 3) EV’s Charging Infrastructure challenges Battery Prices- Cell costs have fell down drastically to $100 kwh or 7500RS approximately or lower and are even expected to continue falling with technological improvements and returns to large-scale production. While cells are just one component of the value of an installed battery, the price of installed battery, the value of installed batteries has declined from around $1000 per kwh in 2010 to an estimated $250 -350 per kwh in 2018.Total Battery costs are falling more slowly as consumers demand EVs with longer ranges and thus larger batteries. Meanwhile, governments are finding it difficult to fiscally justify large subsidies to draw in buyers. Keywords: Costs, Gasoline, Battery costs, Consumer Attitude, Automotive industry
43
Lal, Avisekh, Ravitesh Kumar, Utkal Mehta, and Gancho Vachkov. "Fuzzy energy distribution to a variable consumer load." South Pacific Journal of Natural and Applied Sciences 32, no. 2 (2014): 37. http://dx.doi.org/10.1071/sp14006.
Full textAbstract:
The paper demonstrates the fuzzy logic based smart distributed system to utilize the available energy optimally. We study the power system with two distributed sources of renewable energy like wind and solar together with normal power grid supply. Through the suitable allotter of the generation ratio from power sources, the distribution generation system, combined with battery bank, can provide user with reliable and constant electric power. Therefore a smart energy distributor is useful to supply energy to consumers such that their demand is supplied optimally depending available energy and battery status. In this work, a new distributor system is tested with fuzzy logic theory to satisfy the load demand constantly at the same time to keep the charging state of the battery at a safe level. Simulation results are also presented to illustrate the potential benefits of the smart distributor by maximizing the usage of renewable energy and depending less on the supply grid.
44
Alcayde, Alfredo, Raul Baños, Francisco Arrabal-Campos, and Francisco G. Montoya. "Optimization of the Contracted Electric Power by Means of Genetic Algorithms." Energies 12, no. 7 (April 2, 2019): 1270. http://dx.doi.org/10.3390/en12071270.
Full textAbstract:
An adequate selection of an energy provider and tariff requires us to analyze the differentalternatives to choose one that satisfies your needs. In particular, choosing the right electricity tariff isessential for reducing company costs and improving competitiveness. This paper analyzes the energyconsumption of large consumers that make intensive use of electricity and proposes the use of geneticalgorithms for optimizing the tariff selection. The aim is to minimize electricity costs including twofactors: the cost of power contracted and the heavy penalties for excess of power demand over thepower contracted in certain time periods. In order to validate the proposed methodology, a casestudy based on the real data of energy consumption of a large Spanish university is presented. Theresults obtained show that the genetic algorithm and other bio-inspired approaches are able to reducethe costs associated to the electricity bill.
45
Mukundufite, Fabien, Jean Marie Vianney Bikorimana, Etienne Ntagwirumugara, and Alex Kyaruzi. "CO2 emission reduction and energy management for an integrated smart grid — Case of study: Rwandan electrical network." E3S Web of Conferences 181 (2020): 03002. http://dx.doi.org/10.1051/e3sconf/202018103002.
Full textAbstract:
Many scholars have been focusing on the energy management by Integrating a smart grid into a conventional electrical grid. They have showed that to meet a certain power demand of the consumers, using energy management, the electric utility can turn on some generators, which may have the least operation cost, while the generators with high operation cost are left to supply extra load demand in specific peak periods. Henceforth, the operation cost of its generation units is minimized. The issue remains at a level of relating the energy management to CO2 emission. The present paper briefly discusses the Rwandan electrical network that still integrates the use of diesel generators. It estimates the amount of CO2 emission that can be avoided once a PV system is integrated into the electrical network. The paper as well proposes an algorithm for energy management with consideration of CO2 emission.
46
Braun, Lars, Minh Le, Jürgen Motz, and Kai Peter Birke. "Novel Approach to Ensure Safe Power Supply for Safety-Relevant Consumers." Batteries 8, no. 5 (May 19, 2022): 47. http://dx.doi.org/10.3390/batteries8050047.
Full textAbstract:
The 12 V powernet in vehicles must fulfill certain safety requirements due to the safety demand of consumers. A potential risk is undervoltage for a safety-relevant consumer, which leads to its fault. Therefore, a novel approach is presented in this study, which can predict the minimum terminal voltage for consumers. This consists of diagnostics of the wiring harness and of the lead-acid battery as well as predefined consumer currents. Using simulation, first the beginning of a drive cycle is simulated to determine the state of the powernet, and afterwards a critical driving maneuver is simulated to validate the predicted minimum terminal voltage. It demonstrates that the novel approach is able to predict a fault due to undervoltage. In addition to fulfilling safety requirements, the novel approach could be used to achieve additional availability and miniaturization of powernet components compared to the state of the art.
47
Andoh, Prince Yaw Andoh, Charles Kofi Kafui Sekyere, L. D. Mensah, and D. E. K. Dzebre. "Forecasting Electricity Demand In Ghana With The Sarima Model." Journal of Applied Engineering and Technological Science (JAETS) 3, no. 1 (December 23, 2021): 1–9. http://dx.doi.org/10.37385/jaets.v3i1.288.
Full textAbstract:
Demand forecasting is a challenging subject of interest to many organizations whose main focus is to improve their steady growing customer request/demand, and help in increasing their revenue generation. The story is no different in the power industry. It is quite difficult for power or electrical producers to store high quantum of the energy produced, hence this poses a challenge in estimating precisely the quantum of electrical energy in order to equate demand and supply of powers as well as reducing or eliminating the rising transmission losses. This study explores potential time series models in electricity demand prediction or forecasting for the Western Regions of Ghana. Secondary data was sourced formally from the regional headquarters of ECG to aid in research design to be able to estimate the quantum of electricity needed by consumers in the region. This was done using time series data analysis toolpak software. Results show that the models formulated are viable for future consumption forecasts and other investment in alternative power source projects in meeting these future demands. Since there are up-surging energy demand patterns in the region, the flexibility of the formulated models can be very useful and supplementary to framing effective and efficient energy policies.
48
Wang, Weijuan, Zhanhui Lu, and Quanxin Zhu. "The Interval Stability of an Electricity Market Model." Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/547485.
Full textAbstract:
Combined with the electric power market dynamic model put forward by Alvarado, an interval model of electricity markets is established and investigated in this paper pertaining to the range of demand elasticity with suppliers and consumers. The stability of an electricity market framework with demand elasticity interval is analyzed. The conclusions characterizing the interval model provided are derived by constructing a suitable Lyapunov function and using the theory of interval dynamical system in differential equations and matrix inequality theory and so forth. Applying the corollary obtained can judge the system stability by available data about demand elasticity. The obtained results are validated and illustrated by a case example.
49
Masood, Bilal, Song Guobing, Jamel Nebhen, Ateeq Ur Rehman, Muhammad Naveed Iqbal, Iftikhar Rasheed, Mohit Bajaj, Muhammad Shafiq, and Habib Hamam. "Investigation and Field Measurements for Demand Side Management Control Technique of Smart Air Conditioners located at Residential, Commercial, and Industrial Sites." Energies 15, no. 7 (March 28, 2022): 2482. http://dx.doi.org/10.3390/en15072482.
Full textAbstract:
This paper investigates the response and characteristics of the narrowband power line communication (NB-PLC) technique for the effective control of electric appliances such as smart air conditioners (SACs) for demand side management (DSM) services. The expression for temperature sensitivity by examining the influence of atmospheric temperature variations on power consumption profile of all possible types of loads, i.e., residential, commercial, and industrial loads is derived and analyzed. Comprehensive field measurements on these power consumers are carried out in Lahore, Pakistan. The responses of low voltage channels, medium voltage channels, and transformer bridge for a 3–500 kHz NB-PLC frequency range are presented for DSM services. The master control room transmits control commands for the thermostat settings of SACs over power lines, crossing the transformer bridge to reach the SACs of power consumers by using communication protocol smart energy profile 1.0. The comparison of hourly and daily power consumption profiles under evaluation loads, by analyzing typical and variable frequency air conditioners on setting thermostat temperature at 25 °C and 27 °C conventionally and then by using DSM control technique, is analyzed. A prominent reduction in power consumption is found with the implementation of the DSM control technique.
50
Zahid, Hassan, Farhana Umer, Zeeshan Rashid, Abdur Raheem, Rabia Shakoor, and G. Amjad Hussain. "Critical Analysis and Application of Net-Metering Practice in MEPCO." International Journal of Photoenergy 2020 (June 13, 2020): 1–13. http://dx.doi.org/10.1155/2020/4135860.
Full textAbstract:
The electrical infrastructure around the globe is expanding at a rapid rate for the sake of fulfilling power demands in the domestic, commercial and entertainment industries aiming to boost the living standards. In this regard, renewable energy sources (RES) are globally accepted potential candidates for maintaining inexhaustible, clean, and reliable electricity with a supplementary feature of economic prospect. The efficiency of power distribution at reduced cost to the consumers can be further enhanced by introducing a two-way billing system so-called net-metering which has the potential to overcome issues such as voltage regulation, power blackouts, overstressed grid and need for expensive storage systems thereby making it beneficial for the grid and the end user. This envisioning has encouraged the Government of Pakistan to install net-metering infrastructure at places which accommodate surplus renewable energy reserves. According to the Electric Power Act 1997, the National Electric Power Regulatory Authority (NEPRA) issued the net-metering rules and regulations in September 2015 by the endorsement of Federal Government which allowed the distribution companies in Pakistan to buy surplus electricity units generated by the consumers in order to partly reimburse the units imported from the utility grid. The aim behind this research work is to promote renewable energy utilization through net-metering mechanism in order to achieve maximum power. The export of units from consumer side to utility grid and vice versa can be made through bidirectional energy meter. In this paper, a solar net-metering analysis has been carried out on ETAP software to determine its benefits in a distribution network. Different scenarios have been investigated, and it is concluded that solar net-metering technique has multiple influential benefits, e.g., improvement in voltage regulation, reduction in transmission and distribution losses, increase in power availability, less billing to consumers, and reduction of loading on utility grid.