Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
A systematic review of building electricity use profile models
The building sector contributes significantly to overall energy consumption and carbon
emissions. Improving renewable energy utilization in buildings is of considerable …
emissions. Improving renewable energy utilization in buildings is of considerable …
Risk-averse storage planning for improving RES hosting capacity under uncertain siting choices
X Cao, T Cao, F Gao, X Guan - IEEE transactions on …, 2021 - ieeexplore.ieee.org
This paper presents a trilevel risk-averse strategy to configure the grid-scale energy storage
systems (ESS) in active distribution network. Unlike the traditional planning framework …
systems (ESS) in active distribution network. Unlike the traditional planning framework …
Electric load clustering in smart grid: Methodologies, applications, and future trends
With the increasingly widespread of advanced metering infrastructure, electric load
clustering is becoming more essential for its great potential in analytics of consumers' …
clustering is becoming more essential for its great potential in analytics of consumers' …
Federated fuzzy k-means for privacy-preserving behavior analysis in smart grids
Better understanding the behavior of various participants in smart grids, such as electricity
consumers and generators, is important and beneficial for flexibility exploration and …
consumers and generators, is important and beneficial for flexibility exploration and …
Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming
W Yuan, X Wang, C Su, C Cheng, Z Liu, Z Wu - Energy, 2021 - Elsevier
Integrating photovoltaic (PV) power into large-capacity hydropower plants is considered as
an efficient and promising approach for large-scale PV power accommodation. To improve …
an efficient and promising approach for large-scale PV power accommodation. To improve …
A two-stage framework for demand-side management and energy savings of various buildings in multi smart grid using robust optimization algorithms
Advances in technology and population growth are two factors responsible for increasing
electricity consumption, which directly increases the production of electrical energy. Also …
electricity consumption, which directly increases the production of electrical energy. Also …
[HTML][HTML] Residential consumer preferences to demand response: Analysis of different motivators to enroll in direct load control demand response
Demand Response (DR) is a potential tool to help reduce the network and market stress
with the ever-increasing renewable energy in the electricity system. This study aims to …
with the ever-increasing renewable energy in the electricity system. This study aims to …
Digital twin-driven decision making and planning for energy consumption
The Internet of Things (IoT) is revolutionising how energy is delivered from energy producers
and used throughout residential households. Optimising the residential energy consumption …
and used throughout residential households. Optimising the residential energy consumption …
Impact of demand response on optimal sizing of distributed generation and customer tariff
Due to the surge in load demand, the scarcity of fossil fuels, and increased concerns about
global climate change, researchers have found distributed energy resources (DERs) to be …
global climate change, researchers have found distributed energy resources (DERs) to be …