Smart grid and energy district mutual interactions with demand response programs

Abstract

The bi-directional energy flow between prosumers (wind energy) and smart grid (SG) provides pertinent benefits, such as (i) load-sharing, (ii) peak-load shaving, (iii) load reduction with energy market programs, (iv) ancillary services-based energy transactions, and (v) mutual beneficial frameworks based on rewards and penalties. However, the load variations of SG, intermittent wind speed in energy district (ED) of prosumers, and stochastic energy price are the major constraints that must be considered in wind energy prosumers (WEPs) interaction with utility. Further, the interfacing and interactions of WEPs with SG incur an enormous volume of data to be processed, stored, accessed, and managed. Therefore, the authors proposed a stochastic bi-directional energy management model (BEMM) to manage the aforementioned constraints. Moreover, the BEMM is empowered with cloud-based service level agreement (C-SLA) that provides massive storage capabilities to the enormous data incurred due to WEPs interactions with SG. Two sub-models of BEMM are incorporated, namely stochastic wind estimation model and stochastic energy pricing model. The wind estimation model deals the stochasticity of wind speed for energy generation, while energy price model manages and controls the uncertainty of pricing tariffs based on real-time pricing and daya-head pricing mechanisms for efficient energy trade between SG and WEPs under the principle of C-SLA.

Incentive Based Demand Response Program for Power System Flexibility Enhancement

“…Ali et al [6] demonstrate a centralized cloud-based protocol for regulating interactions between prosumers in an energy district, and a smart grid. The A multi-objective optimization problem aims to: maximize grid revenue, maximize the amount of prosumer energy sold to the smart grid, and minimize prosumer energy cost.…”

“…The start of a curtailment event is indicated by the binary variable v curt (t) in (6). Curtailment occurring on the very first period u curt (1) = 1 is treated as a special case where v curt (1) = 1, represented by (7).…”

Optimized Economic Load Dispatch with Multiple Fuels and Valve-Point Effects Using Hybrid Genetic–Artificial Fish Swarm Algorithm

“…Genetic algorithm (GA) is an optimization algorithm that simultaneously works on several solutions (also called population), as opposed to other optimization methods that work on one solution at a time [25,26]. It is an iterative optimization algorithm and comprises several steps, briefly described below.…”

Coordinated Operation and Planning of Integrated Electricity and Gas Community Energy System With Enhanced Operational Resilience

“…Heating state of the ith HWP at time t W CT t , W HT t , W IT t Energy stored in the CTs, HTs and IT at time t (kWh) P GT t , H GT Upper power limit of the CWP collateral to the CT (kW) P GT Upper power limit of the GT (kW) P TL,max , F GT,max Maximum allowed tie-line power and gas power (kW) ε WT , ε IT Heat loss rates of the WT and IT C HP u , C WC u , C DC u , Due to the increasing environmental concerns, optimizing the energy structure and building clean and efficient energy systems have become an urgent task for sustainable development [1]. At the meantime, natural gas has been playing an important role in energy consumption because of the merits of cleanliness and high-efficiency [2].…”