Incentive Mechanisms for Smart Grid: State of the Art, Challenges, Open Issues, Future Directions

Abstract

Smart grids (SG) are electricity grids that communicate with each other, provide reliable information, and enable administrators to operate energy supplies across the country, ensuring optimized reliability and efficiency. The smart grid contains sensors that measure and transmit data to adjust the flow of electricity automatically based on supply/demand, and thus, responding to problems becomes quicker and easier. This also plays a crucial role in controlling carbon emissions, by avoiding energy losses during peak load hours and ensuring optimal energy management. The scope of big data analytics in smart grids is huge, as they collect information from raw data and derive intelligent information from the same. However, these benefits of the smart grid are dependent on the active and voluntary participation of the consumers in real-time. Consumers need to be motivated and conscious to avail themselves of the achievable benefits. Incentivizing the appropriate actor is an absolute necessity to encourage prosumers to generate renewable energy sources (RES) and motivate industries to establish plants that support sustainable and green-energy-based processes or products. The current study emphasizes similar aspects and presents a comprehensive survey of the start-of-the-art contributions pertinent to incentive mechanisms in smart grids, which can be used in smart grids to optimize the power distribution during peak times and also reduce carbon emissions. The various technologies, such as game theory, blockchain, and artificial intelligence, used in implementing incentive mechanisms in smart grids are discussed, followed by different incentive projects being implemented across the globe. The lessons learnt, challenges faced in such implementations, and open issues such as data quality, privacy, security, and pricing related to incentive mechanisms in SG are identified to guide the future scope of research in this sector.

Energy Theft Detection in Smart Grids with Genetic Algorithm-Based Feature燬election

“…The user trends would also help predict future power consumption and would be helpful to set out the SG upgradation targets. Several challenges, open questions, and advancement voids still exist towards the advancement of smart grids [39], as our proposed methodology requires user data for training and testing the system. In the future, we plan to integrate a data encryption module using the available state-of-the-art data encryption techniques [40][41][42][43].…”

A Levenberg–Marquardt Based Neural Network for Short-Term Load Forecasting

“…We have used the USA power industry's publicly available electrical hourly load dataset 1 . The period of the dataset used in this work is from January 1, 2019, to December 31, 2021.…”

“…Electric load generation, transmission, and distribution utilities heavily depend on load forecast. Therefore, these utilities need accurate methods to forecast electrical load to use their infrastructure effectively, safely, and economically [1,2]. Typically, load forecasting is categorized into four categories, i.e., very short-term (VSTLF), short-term (STLF), medium-term (MTLF), and longterm (LTLF) load forecasting.…”

A Review on Frequency Stability Enhancement and Effective Energy Storage through Various Optimization Techniques

“…In a battery, an organic process takes place, converting chemical energy to electrical energy. e electrolyte substance is soaked into the electrodes, allowing leading electricity; ion exchange is being used [19]. e discharge process in lead-acid batteries converts electrodes to crystals of lead sulphate, whereas the sulfuric acid (electrolyte) is transformed to water as shown in Table 1.…”

“…e CSA is a newly developed metaheuristic optimization technique for solving optimization problems. Levy flights random walks and brood parasitism in various cuckoo species are used in this nature-inspired metaheuristic algorithm [18,19]. To boost the chances of their eggs hatching, cuckoos of certain varieties hurl eggs from the actual parent at the nest.…”