相关论文: Large-Scale Demonstration of Precise Demand Respon…

The flexible power consumption feature of thermostatically controlled loads (TCLs) such as heating, ventilation, and air-conditioning (HVAC) systems makes them attractive targets for demand response (DR). TCLs possess a brief period where…

In coming years residential consumers will face real-time electricity tariffs with energy prices varying day to day, and effective energy saving will require automation - a recommender system, which learns consumer's preferences from her…

Load points are one of the most vital parts of power systems. Due to the new load forms and programs introduced in the demand side, the load-serving entities (LSEs) no longer deal with lump loads, but rather with more dynamic, rational and…

Linear programming is used as a standard tool for optimising unit commitment or power flows in energy supply systems. For heat supply systems, however, it faces a relevant limitation: For them, energy yield depends on the output…

Collective adaptive systems are an emerging class of networked computational systems, particularly suited in application domains such as smart cities, complex sensor networks, and the Internet of Things. These systems tend to feature large…

Smart buildings are the need of the day with increasing demand-supply ratios and deficiency to generate considerably. In any modern non-industrial infrastructure, these demands mainly comprise of thermostatically controlled loads (TCLs),…

Flow and storage volume regulation is essential for the adequate transport and management of energy resources in district heating systems. In this letter, we propose a novel and suitably tailored -- decentralized -- adaptive control scheme…

In this paper, we investigate the feasibility, robustness and optimization of introducing personal comfort systems (PCS), apparatuses that promises in energy saving and comfort improvement, into a broader range of environments. We report a…

Participation in residential energy demand response programs requires an active role by the consumers. They contribute flexibility in how they use their appliances as the means to adjust energy consumption, and reduce demand peaks, possibly…

In this paper, an energy conservation measure that optimizes the planning of heating and cooling systems for tertiary sector buildings is proposed. It consists of a model-based predictive control approach that employs a grey-box model built…

Demand response management has become one of the key enabling technologies for smart grids. Motivated by the increasing demand response incentives offered by service operators, more customers are subscribing to various demand response…

The smart grid with its two-way communication and bi-directional power layers is a cornerstone in the combat against global warming. It allows for the large scale adoption of distributed (individually-owned) renewable energy resources such…

The thermal characterisation of a building envelope is usually best performed from on site measurements with controlled heating power set points. Occupant-friendly measurement conditions provide on the contrary less informative data.…

The increasing integration of renewable energy into the power grid has highlighted the critical importance of demand-side flexibility. Among flexible loads, heating, ventilation, and air-conditioning (HVAC) systems are particularly…

Building operations represent a significant percentage of the total primary energy consumed in most countries due to the proliferation of Heating, Ventilation and Air-Conditioning (HVAC) installations in response to the growing demand for…

With the ongoing energy transition, demand-side flexibility has become an important aspect of the modern power grid for providing grid support and allowing further integration of sustainable energy sources. Besides traditional sources, the…

Many loads have flexibility in demand that can be used to provide ancillary services to power grids. A large body of literature exists on designing algorithms to coordinate actions of many loads to provide such a service. The topic of…

Understanding and predicting the electricity demand responses to prices are critical activities for system operators, retailers, and regulators. While conventional machine learning and time series analyses have been adequate for the routine…

Distribution system residential load modeling and analysis for different geographic areas within a utility or an independent system operator territory are critical for enabling small-scale, aggregated distributed energy resources to…

The electrical generation and transmission infrastructures of many countries are under increased pressure. This partially reflects the move towards low carbon economies and the increased reliance on renewable power generation systems. There…