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An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview
Current power networks and consumers are undergoing a fundamental shift in the way
traditional energy systems were designed and managed. The bidirectional peer-to-peer (P …
traditional energy systems were designed and managed. The bidirectional peer-to-peer (P …
A systematic survey on demand response management schemes for electric vehicles
The unprecedented proliferation of electric vehicles is envisioned to revolutionize the
Intelligent Transportation System as an energy-efficient and environment-friendly alternative …
Intelligent Transportation System as an energy-efficient and environment-friendly alternative …
Machine learning based PV power generation forecasting in alice springs
The generation volatility of photovoltaics (PVs) has created several control and operation
challenges for grid operators. For a secure and reliable day or hour-ahead electricity …
challenges for grid operators. For a secure and reliable day or hour-ahead electricity …
ARIMA models in solar radiation forecasting in different geographic locations
The increasing demand for clean energy and the global shift towards renewable sources
necessitate reliable solar radiation forecasting for the effective integration of solar energy …
necessitate reliable solar radiation forecasting for the effective integration of solar energy …
Recent progress towards photovoltaics' circular economy
Massive expansions in the global population and the global digitalization throughout the
industrial revolution are causing energy security issues that are no longer environmentally …
industrial revolution are causing energy security issues that are no longer environmentally …
Graph deep-learning-based retail dynamic pricing for demand response
Designing customized dynamic pricing is a promising way to incent consumers to adjust
their daily energy consumption behaviors. It helps manage flexible demand response …
their daily energy consumption behaviors. It helps manage flexible demand response …
高比例可再生能源电力系统调峰问题综述
和萍, 宫智杰, 靳浩然, 董杰, 云磊 - 电力建设, 2022 - epjournal.csee.org.cn
随着可再生能源在电力系统中所占的比例日益提高, 电力系统的电源结构发生了巨大变化,
可再生能源的高渗透性, 出力的随机性和不确定性, 使得电源侧, 负荷侧对电力系统调峰资源需求 …
可再生能源的高渗透性, 出力的随机性和不确定性, 使得电源侧, 负荷侧对电力系统调峰资源需求 …
[HTML][HTML] artificial intelligence control system applied in smart grid integrated doubly fed induction generator-based wind turbine: A review
Wind-driven turbines utilizing the doubly-fed induction generators aligned with the
progressed IEC 61400 series standards have engrossed specific consideration as of their …
progressed IEC 61400 series standards have engrossed specific consideration as of their …
Load forecasting based on genetic algorithm–artificial neural network-adaptive neuro-fuzzy inference systems: a case study in Iraq
AMM AL-Qaysi, A Bozkurt, Y Ates - Energies, 2023 - mdpi.com
This study focuses on the important issue of predicting electricity load for efficient energy
management. To achieve this goal, different statistical methods were compared, and results …
management. To achieve this goal, different statistical methods were compared, and results …
[HTML][HTML] Residential PV-battery scheduling with stochastic optimization and neural network-driven scenario generation
Residential end-users have increasingly been attracted to installing behind-the-meter (BTM)
photovoltaic (PV) and battery energy storage systems (BESS). The inherent stochastic …
photovoltaic (PV) and battery energy storage systems (BESS). The inherent stochastic …