Dynamic economic dispatch of Micro-grid using Harmony Search Algorithm

Jha, Ritesh Kumar; Meena, Nand K.; Swarnkar, Anil; Gupta, Nikhil; Niazi, K. R.

doi:10.1109/indicon.2015.7443330

Cited by 9 publications

(13 citation statements)

References 17 publications

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“…where L is the average of all variable solutions in the iteration T ; sb is the number of scout bee population and 2 N is the total number of scout bee. The population size for employed bees, onlooker bees, and scout bees are total population 40%, 40%, and 20%, respectively and total population size is set to 100.…”

Section: Scout Beesmentioning

confidence: 99%

“…A number of approaches have been developed for solving the DED problem. The two-step method is proposed to solve the DED with valve-point effect in [1] and the harmony search algorithm employed to solve the DED problem for Micro-grid in [2]. Recently, some artificial intelligent techniques have been presented to solve the DED problem and have shown their effectiveness in [3][4].…”

Section: Introductionmentioning

confidence: 99%

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Bee colony optimization with Taguchi method for solving the dynamic economic dispatch

Huang

Tsai

et al. 2018

MATEC Web Conf.

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Abstract. Dynamic economic dispatch is to minimize the cost of power production of all the participating generators over a time horizon of 24 hours in one day. The dynamic economic dispatch with non-smooth cost functions, for which is formulated the optimal dispatch model of generations by considering the ramp up/down scheduling of power. This paper presents a Bee Colony Optimization (BCO) that applies the Taguchi Method (TM) to solve the Dynamic Economic Dispatch problem. The Taguchi method that involves the use of orthogonal arrays in estimating of the non-smooth cost function and Bee Colony Optimization is used to find the objective function under the operational of system constraints. The Taguchi method can global optimization for fast local convergence by minimizing the cost function in a few iterations. The effectiveness and efficiency of the TM-BCO is demonstrated by using a 10 unit of IEEE case with non-smooth fuel cost functions and is more effective than other previously developed algorithms. Moreover, the proposed approach presents significant computational benefits than traditional random search method especially for multi-unit systems with larger numbers of nonsmooth cost functions and more complicated dynamic economic dispatch.

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Section: Scout Beesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bee colony optimization with Taguchi method for solving the dynamic economic dispatch

Huang

Tsai

et al. 2018

MATEC Web Conf.

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“…Optimal operation of MG means effectively controlling the output power of each MG source with the objective of minimizing total cost, minimizing emission, improving energy utilization, or maximizing profits while ensuring that load is met and certain limits are satisfied . Significant research work has already been conducted in the area of optimal operation of MG. Jha et al discussed dynamic grid pricing‐based dynamic load dispatch (DLD) problem for a photovoltaic (PV), wind turbine (WT), fuel cell (FC), and diesel engine (DE)‐based grid‐connected MG comparing different scheduling strategies using harmony search algorithm. To get the advantage of fluctuating market prices, intelligent scheduling of battery charging and discharging while simultaneously minimizing both cost and emission is achieved .…”

Section: Introductionmentioning

confidence: 99%

“…The uncertainties are handled using 2 m point estimate method (PEM), 2 m + 1 PEM, and scenario‐based stochastic programming, respectively. Aforementioned work from the literature has considered only grid‐connected MG operation.…”

Section: Introductionmentioning

confidence: 99%

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Impact assessment of electric vehicle charging/discharging strategies on the operation management of grid accessible and remote microgrids

et al. 2019

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This article deals with impact analysis of different electric vehicle (EV) charging/discharging strategies (CDS) on the operation and pollutant treatment cost of both grid accessible and remote microgrid (MG) modes. In this regard, EV demand is developed under four different scenarios, namely, uncoordinated charging model (UCM), load leveling model (LLM), maximum renewable model (MRM), and charging discharging model (CDM). A comprehensive study is performed to see the effect of these different EV charging/discharging behaviors in optimizing MG's operation. A 2m scheme of Hong's point estimate method (PEM) is applied to examine the effect of uncertainties linked with the forecasted errors in load demand, solar energy, wind energy, and grid price respectively on MG operation problem. Finally, a sensitivity analysis is performed to investigate the effect of variations in battery parameters on economics of remote MG. The study results indicate that controlled charging of EVs can substantially improve operation of MG. KEYWORDS distributed generators, electric vehicle, microgrid, point estimate methodNomenclature: L avg , average load; L base , base load of MG (without EV); BC b , battery capacity; BC EV,n , battery capacity of EV n; η bc , battery charging efficiency; P bc , battery charging power; η bd , battery discharging efficiency; P bd , battery discharging power; SOC b , battery SOC; v, binary variable, 1 when battery is charging; w, binary variable, 1 when battery is discharging; cf, capacity factor; t cd,n , charging duration of EV n; η EVc,n , charging efficiency of EV n; P EVc,n , charging power of EV n; C grid , cost of power integration between main grid and MG; C DC,i , depreciation cost of DG i; ADCC i , depreciation cost per kwh of DG i; T EVde,n , discharging end time of EV n; T EVds,n , discharging start time of EV n; d n , distance travelled by an EV n; EP GRID , electricity price of grid; e 100,n , energy consumption per 100 km of EV n; k fc,i , fuel consumption coefficient of DG i; C fuel,i , fuel cost of DG i; Incost i , installation cost per capacity of DG i; d, interest rate; l i , lifetime of DG i; P LC , load curtailed; C LC , load curtailment cost; μ LC , load curtailment cost; r down,i , lower ramp rate limit of DG i; SOC b,max , maximum battery SOC; P bc,max , maximum charging limit of battery; P EVcmax,n , maximum charging rate of EV n; P bd,max , maximum discharging limit of battery; P EVdmax,n , maximum discharging power of EV n; T EVddmax,n , maximum duration for which EV n can discharge; P grid,max , maximum power MG can take from main grid under contractual scheme; P i,max , maximum power of DG i; SOC EVmax,n , maximum SOC of battery of EV n; SOC b,min , minimum battery SOC; P i,min , minimum power of DG i; SOC EVmin,n , minimum SOC of battery of EV n; N DG , number of DGs in MG; k OM,i , operation and maintenance coefficient of DG i; C OM,i , operation and maintenance cost of DG i; P PV , output power from PV; P WT , output power from WT; P i , output power of DG i; P grid , output ...

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Improvement of Voltage Profile and Loss Reduction Based on Optimal Placement and Sizing of Renewable Distributed Generations Using 4-Rule Harmony Search Algorithm

Sadollah

Nasir

Al-Shamiri

et al. 2020

Advances in Intelligent Systems and Computing

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Dynamic economic dispatch of Micro-grid using Harmony Search Algorithm

Cited by 9 publications

References 17 publications

Bee colony optimization with Taguchi method for solving the dynamic economic dispatch

Bee colony optimization with Taguchi method for solving the dynamic economic dispatch

Impact assessment of electric vehicle charging/discharging strategies on the operation management of grid accessible and remote microgrids

Improvement of Voltage Profile and Loss Reduction Based on Optimal Placement and Sizing of Renewable Distributed Generations Using 4-Rule Harmony Search Algorithm

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