8,577 research outputs found
Smart Grid Technologies in Europe: An Overview
The old electricity network infrastructure has proven to be inadequate, with respect to modern challenges such as alternative energy sources, electricity demand and energy saving policies. Moreover, Information and Communication Technologies (ICT) seem to have reached an adequate level of reliability and flexibility in order to support a new concept of electricity networkāthe smart grid. In this work, we will analyse the state-of-the-art of smart grids, in their technical, management, security, and optimization aspects. We will also provide a brief overview of the regulatory aspects involved in the development of a smart grid, mainly from the viewpoint of the European Unio
Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings
Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort by combining predictive control with demand controlled ventilation (DCV). First, we show that the problem of maintaining IAQ, thermal comfort and optimal energy is a multi-objective optimization problem with competing objectives, and a predictive control approach is required to smartly control the system. This leads to many implementation challenges which are addressed by designing a hybrid ventilation scheme supported by predictive control and soft-sensors. The main idea of the hybrid ventilation system is to achieve thermal comfort by varying the ON/OFF times of the air conditioners to maintain the temperature within user-defined bands using a predictive control and IAQ is maintained using Healthbox 3.0, a DCV device. Furthermore, this study also designs soft-sensors by combining the Internet of Things (IoT)-based sensors with deep-learning tools. The hardware realization of the control and IoT prototype is also discussed. The proposed novel hybrid ventilation system and the soft-sensors are demonstrated in a real research laboratory, i.e., Center for Research in Automatic Control Engineering (C-RACE) located at Kalasalingam University, India. Our results show the perceived benefits of hybrid ventilation, predictive control, and soft-sensors
Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains
We consider using a battery storage system simultaneously for peak shaving
and frequency regulation through a joint optimization framework which captures
battery degradation, operational constraints and uncertainties in customer load
and regulation signals. Under this framework, using real data we show the
electricity bill of users can be reduced by up to 15\%. Furthermore, we
demonstrate that the saving from joint optimization is often larger than the
sum of the optimal savings when the battery is used for the two individual
applications. A simple threshold real-time algorithm is proposed and achieves
this super-linear gain. Compared to prior works that focused on using battery
storage systems for single applications, our results suggest that batteries can
achieve much larger economic benefits than previously thought if they jointly
provide multiple services.Comment: To Appear in IEEE Transaction on Power System
A novel bidding method for combined heat and power units in district heating systems
We propose a bidding method for the participation of combined heat and power
(CHP) units in the day-ahead electricity market. More specifically, we consider
a district heating system where heat can be produced by CHP units or heat-only
units, e.g., gas or wood chip boilers. We use a mixed-integer linear program to
determine the optimal operation of the portfolio of production units and
storages on a daily basis. Based on the optimal production of subsets of units,
we can derive the bidding prices and amounts of electricity offered by the CHP
units for the day-ahead market. The novelty about our approach is that the
prices are derived by iteratively replacing the production of heat-only units
through CHP production. This results in an algorithm with a robust bidding
strategy that does not increase the system costs even if the bids are not won.
We analyze our method on a small realistic test case to illustrate our method
and compare it with other bidding strategies from literature, which consider
CHP units individually. The analysis shows that considering a portfolio of
units in a district heating system and determining bids based on replacement of
heat production of other units leads to better results
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