Due to the growing developments in advanced metering and digital technologies, smart cities have been equipped with different electronic devices on basis of Internet Things (IoT), therefore becoming smarter than before. The aim this article is that providing a comprehensive review concepts their motivations applications. Moreover, survey describes IoT technologies for main components features city. Furthermore, practical experiences over world challenges are explained.

Home energy management (HEM) systems enable residential consumers to participate in demand response programs (DRPs) more actively. However, HEM confront some practical difficulties due the uncertainty related renewable energies as well of consumers' behavior. Moreover, aim for highest level comfort and satisfaction operating their electrical appliances. In addition, technical limits appliances must be considered. Furthermore, DR providers at keeping participation DRPs minimize "response...

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without to grid is proposed. The charging process modeled as a dynamic linear program instead of the normal day-ahead and regulation strategy, capture advantages both global optimization. Different from conventional forecasting algorithms, vector formation model proposed based on clustering algorithm form an RTP particular day. feasible energy region (DFEDR)...

The optimized operation of a building energy management system (BEMS) is great significance to its security, economy, and efficiency. This paper proposes day-ahead multiobjective optimization model for the BEMS under time-of-use price-based demand response (DR), which integrates integrated photovoltaic with other generations optimize economy occupants' comfort by synergetic dispatch source-load-storage. contains three aspects indoor environment: visual comfort; thermal air quality comfort....

With increasing environmental concerns, the electrification of transportation plays an outstanding role in sustainable development. In this context, plug-in electric vehicle (PEV) and demand response have indispensable impacts on future smart grid. Since integration PEVs into grid is a key element to achieve energy systems, paper presents optimal behavior PEV parking lots reserve markets. To end, model developed derive strategies lots, as responsive demands, both price-based incentive-based...

As a response to rapidly increasing penetration of wind power generation in modern electric grids, accurate prediction models are crucial deal with the associated uncertainties. Due highly volatile and chaotic nature power, employing complex intelligent tools is necessary. Accordingly, this article proposes novel improved version empirical mode decomposition (IEMD) decompose measurements. The decomposed signal provided as input hybrid forecasting model built on bagging neural network (BaNN)...

Most current customer baseline load (CBL) estimation methods for incentive-based demand response (DR) rely heavily on historical data and are unable to adapt the cases when patterns (LPs) in DR event day not similar enough those non-DR days. After error generation mechanism of is revealed, a synchronous pattern matching principle-based residential CBL approach without requirement proposed. All customers split into CONTROL group, including participants customers, respectively. First, all...

Penetration of renewable energy sources (RESs) and electrical storage (EES) systems in distribution is increasing, it crucial to investigate their impact on systems' operation scheme, reliability, security. In this paper, expected not supplied (EENS) voltage stability index (VSI) networks are investigated dynamic balanced unbalanced network reconfiguration, including RESs EES systems. Furthermore, due the high investment cost systems, number charge discharge limited, state-of-health...

Ultra-short-term photovoltaic (PV) power forecasting can support the real-time dispatching of grid. However, PV has great fluctuations due to various meteorological factors, which increase energy prices and cause difficulties in managing This article proposes an ultra-short-term model based on optimal frequency-domain decomposition deep learning. First, frequency demarcation points for components are obtained through analysis. Then, is decomposed into low-frequency high-frequency components,...

This paper presents a pool trading model within local energy community considering home management systems (HEMSs) and other consumers. A transparent mechanism for market clearing is proposed to incentivise active prosumers trade their surplus rule-based in the community. price-based demand response program (PBDRP) considered increase consumers’ willingness modify consumption. The mathematical optimization problem standard mixed-integer linear programming (MILP) allow rapid assessment of...

A recent solution to tackle environmental issues is the electrification of transportation. Effective integration plug-in electric vehicles (PEVs) into grid important in process achieving sustainable development. One key solutions regarding need for charging stations installation PEV parking lots (PLs). However, contrary common parkings, PLs are constrained by various organizations such as municipalities, urban traffic regulators, and electrical distribution systems. Therefore, this paper...

Competitive transactions resulting from recent restructuring of the electricity market, have made achieving a precise and reliable load forecasting, especially probabilistic an important topic. Hence, this paper presents novel hybrid method including generalized extreme learning machine for training improved wavelet neural network, preprocessing bootstrapping. In proposed method, forecasting model data noise uncertainties are taken into account while output is interval. order to validate it...

In this paper, a multi-period integrated framework is developed for generation expansion planning (GEP), transmission (TEP), and natural gas grid (NGGEP) problems large-scale systems. New nodal requirements, new lines, (NG) pipelines are simultaneously obtained in horizon. addition, approach proposed to compute NG load flow by considering compressors. order solve the mixed integer nonlinear problem, based on genetic algorithms. The performance investigated applying it typical electric-NG...

In smart grid, demand response (DR) programs can be deployed to encourage electricity consumers towards scheduling their controllable demands off-peak periods. Motivating the participate in a DR program is challenging task, as they experience confidential discomfort cost by modifying load from desirable pattern scheduled pattern. Meanwhile, balance and generation, independent system operator (ISO) requires motivate suppliers generation profiles follow changes demands. Additionally, protect...