A multi-stage linearized interactive operation model of smart distribution grid with residential microgrids

This paper addresses an interactive energy scheduling model developed between distribution system and residential microgrids (RMGs). To make such concepts, a three-stage mathematical programming framework is proposed. Residential energy management (REM) approach which is in interaction with residential microgrid operator (RMGO) is developed which contains two stages, sequentially. The main goal of these stages is to modify RMGs day-ahead load profile by considering the minimized total daily energy expenses of each home at each RMG. Moreover, in these stages, in addition to existing fixed-loads at each evaluated residential homes, in-home energy management (iHEM) systems are responsible for adjusting the shiftable appliances and small scale distributed energy resources (DERs) commitment. In third stage, besides the interactions between distribution system operator (DSO) and RMG operators (RMGOs), optimal operation cost of the distribution system is determined as well. In this way, optimal scheduling of distribution system active elements namely large scale DERs are considered and the changing trends in energy exchanges, power losses, and voltage profile are addressed. To lower the computational burden of the proposed model, linearization techniques are applied in the proposed model. Simulation studies are reported on modified IEEE 33-bus distribution test system to assess the performance of the proposed model. Results are discussed in depth

An optimal procedure for sizing and siting of DGs and smart meters in active distribution networks considering loss reduction

The presence of responsive loads in the promising active distribution networks (ADNs) would definitely affect the power system problems such as distributed generations (DGs) studies. Hence, an optimal procedure is proposed herein which takes into account the simultaneous placement of DGs and smart meters (SMs) in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Seeking to power loss minimization, the optimization procedure is tackled with genetic algorithm (GA) and tested thoroughly on 69-bus distribution test system. Different scenarios including variations in the number of DG units, adaptive power factor (APF) mode for DGs to support reactive power, and individual or simultaneous placing of DGs and SMs have been established and interrogated in depth. The obtained results certify the considerable effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the lowest value of power losses as well

Data-driven mathematical modeling of the effect of particle size distribution on the transitory reaction kinetics of hot metal desulfurization

Abstract The aim of this work was to develop a prediction model for hot metal desulfurization. More specifically, the study aimed at finding a set of explanatory variables that are mandatory in prediction of the kinetics of the lime-based transitory desulfurization reaction and evolution of the sulfur content in the hot metal. The prediction models were built through multivariable analysis of process data and phenomena-based simulations. The model parameters for the suggested model types are identified by solving multivariable least-squares cost functions with suitable solution strategies. One conclusion we arrived at was that in order to accurately predict the rate of desulfurization, it is necessary to know the particle size distribution of the desulfurization reagent. It was also observed that a genetic algorithm can be successfully applied in numerical parameter identification of the proposed model type. It was found that even a very simplistic parameterized expression for the first-order rate constant provides more accurate prediction for the end content of sulfur compared to more complex models, if the data set applied for the modeling contains the adequate information