The paper describes an ongoing work to define a framework to support monitoring procedures for distribution systems in smart cities. Specific use cases, involving data driven methods for energy monitoring, benchmarking and forecasting in urban scenarios are analysed. The objective is to identify services required in such framework to define the requirements of a reference architecture to suppor...

Commercial buildings are responsible for a large fraction of energy consumption in developed countries, and therefore are targets of energy efficiency programs. Motivated by the large inherent thermal inertia of buildings, the power consumption can be flexibly scheduled without compromising occupant comfort. This temporal flexibility offers opportunities for the provision of frequency regulatio...

Innovative technologies such as ICTs are recognized as being a key player against climate change and the use of sensors and actuators can efficiently control the whole energy chain in the Smart Thermal Grids at district level. On the other side, advances on 3D modelling, visualization and interaction technologies enable user profiling and represent part of the holistic approach which aims at in...

Considerable efforts have been made to reduce the energy consumption of buildings due to the energy crisis, and, the Korean government has supported the use of renewable energy through various grants. Among the possible renewable energy sources, geothermal energy can be used regardless of the outside weather. Therefore, energy consumption can be reduced considerably in summer and winter. Despit...

Software energy consumption of mobile terminal plays an important role in the continuous duty and stability of mobile business. Here an energy management model is built based on a multi-layer software structure and is described as a multivariable function of energy consumption. The relation between software characteristics and energy consumption is discussed and analysed. Moreover the paper pre...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

these days, limited energy resources, and also the cost of investment in new and renewable energy is very costly and uneconomical. in the industrial sector, especially energy-intensive industries such as steel, finding appropriate solutions to update the technology, production and reduce energy consumption in this sector is very important. the main aim of this study is the identification and ra...

Significant effort has been exerted on the study of economic variables such as absolute energy prices to understand energy consumption and economic growth. However, this approach ignores general inflation effects, whereby the prices of baskets of goods may rise or fall at different rates from those of energy prices. Thus, it may be the relative energy price, not the absolute energy price, that ...

Dynamic partial adjustment models of residential electricity demand account for the fact that households may not adjust electricity consumption immediately in response to changes in prices, income, and other relevant factors, because of behavioral habits or adjustment costs for the capital stock of appliances. However, forward-looking behavior is generally neglected. Expectations about future p...

: In this paper, the operation of a future distribution network is discussed under the assumption of a multi-carrier microgrid (MCMG) concept. The new model considers a modern energy management technique in electricity and natural gas networks based on a novel demand side management (DSM) which the energy tariff for responsive loads are correlated to the energy input of the network and changes ...