Reserve constrained dynamic economic dispatch in multi-area power systems: An improved fireworks algorithm

Zare, Mohsen; Narimani, Mohammad Rasoul; Malekpour, Mostafa; Azizipanah‐Abarghooee, Rasoul; Terzija, Vladimir

doi:10.1016/j.ijepes.2020.106579

Cited by 42 publications

(27 citation statements)

References 37 publications

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“…Reference [34] defines the degree of reserve tension caused by wind power stochastic scenarios and establishes a multi-objective optimal scheduling model considering the impact of wind power uncertainty on system reserve risk. Based on the method of scenario analysis, reference [35] established a quantitative analysis model for economic allocation of rotating reserve and non-rotating reserve, which comprehensively considered the loss of abandoned wind and loss of load. About [36], a standby decision-making model considering wind power and smart load prediction error and unit outage rate is established.…”

Section: Overview Of Wind Power Fluctuation and Uncertainty Modeling Based On Scenario Analysis Methodsmentioning

confidence: 99%

Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment

Qian¹,

Chen²,

Chen

et al. 2021

Energies

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Typhoons and other natural disasters affect the normal operation of power systems thus it is an important goal for strong and intelligent power grid construction to improve the ability of power systems to resist typhoons and other natural disasters. Especially, an effective coordinated and optimized dispatching strategy for a multi-source power system is greatly helpful to cope with the impact of typhoons and other natural disasters on power system operation. Given this background, a typhoon wind circle model considering the temporal and spatial distribution of typhoons is established to obtain the input wind speed of the wind farm at first. Second, based on the initial input wind speed of wind farms, a typical scenario set of wind power output is constructed to reflect its fluctuation and uncertainty. Next, an optimal coordinated dispatching model of a multi-source power system with wind, hydro and thermal power based on the conditional value at risk (CVaR) is established with the target of minimizing the total cost of system dispatching, in which a 72 h pre-dispatching mode is studied to optimize the system operation for 72 h on the day before, on and after the typhoon. Finally, a revised 24-node transmission network system in a coastal area with typhoon is served as a case for demonstrating the effectiveness of the proposed model, and the simulation result shows that the proposed model could take the advantages of the coordination and complementarity of multi-sources power system and decrease the total cost of system dispatching and improve the renewable energy consumption level.

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Section: Overview Of Wind Power Fluctuation and Uncertainty Modeling Based On Scenario Analysis Methodsmentioning

confidence: 99%

Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment

Qian¹,

Chen²,

Chen

et al. 2021

Energies

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“…where N refers to power generators numbers. Equation (2) shows the cost hourly non-convex cost function of power generators:…”

Section: Objectives Function Of Deed Problem Objectives Function Of Deed Problem Consists Of Fuel Cost and Emission Functionsmentioning

confidence: 99%

“…With increasing environmental concern, consumer demands high quality power with safe electricity, at lowest possible rates and with lowest possible pollution. Dynamic Economic Emission Dispatch (DEED) provide a solution to these problem by scheduling the renewable and backup power sources based on the forecast load demand to reduce cost and emission of the operating generator [2,3].…”

Section: Introductionmentioning

confidence: 99%

Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function

Mehdi

Ahmad

Haq

et al. 2021

Electrical Engineering & Electromechanics

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Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and emissions as competitive targets for optimal dispatch problems, and to reach a solution it requires some conflict resolution. Novelty. The decision-making method to solve the Dynamic Economic Emission Dispatch problem has a goal for each objective function, for this purpose, the multi-objective problem is transformed into single goal optimization by using the weighted sum method and then control/solve by Whale Optimization Algorithm. Methodology. This paper presents a newly developed metaheuristic technique based on Whale Optimization Algorithm to solve the Dynamic Economic Emission Dispatch problem. The main inspiration for this optimization technique is the fact that metaheuristic algorithms are becoming popular day by day because of their simplicity, no gradient information requirement, easily bypass local optima, and can be used for a variety of other problems. This algorithm includes all possible factors that will yield the minimum cost and emissions of a Dynamic Economic Emission Dispatch problem for the efficient operation of generators in a power network. The proposed approach performs well to perform in diverse problem and converge the solution to near best optimal solution. Results. The proposed strategy is validated by simulating on MATLAB® for 5 IEEE standard test system. Numerical results show the capabilities of the proposed algorithm to establish an optimal solution of the Dynamic Economic Emission Dispatch problem in a several runs. The proposed algorithm shows good performance over the recently proposed algorithms such as Multi-Objective Neural Network trained with Differential Evolution, Particle swarm optimization, evolutionary programming, simulated annealing, Pattern search, multi-objective differential evolution, and multi-objective hybrid differential evolution with simulated annealing technique.

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“…This algorithms are used in several problems such as extraction of photovoltaic parameters using gradient based optimizer [12] and Turbulent flow of water optimization [13]. In addition, solving ELD problem is performed with several al-gorithms such as non dominated sorting genetinc algorithm [14], modified jrill algorithm [15], Whale Optimization Algorithm [16], Henry gas solubility optimization [17], gravitational search algorithm [18], improved Firework Algorithm [19], grasshopper optimization algorithm [20], multi gradient practical swarm optimization [21], Salp Swarm Algorithm [22], Differential Evolution [23], Equilibrium Optimizer [24], reinforcement learning [25], virus colony search algorithm [26], Harmony Search Algorithm [27], improved grey wolf optimization [28], bat algorithm [29], improved class topper optimization algorithm [30], improved bat algorithm [31], Ant Colony Optimization [32], improved Jaya algorithm [33] and artificial cooperative search algorithm [34].…”

Section: Introductionmentioning

confidence: 99%

Performance of Turbulent Flow of Water Optimization on Economic Load Dispatch Problem

et al. 2021

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The economic load dispatch (ELD) problems considering nonlinear characteristics where an optimal combination of power generating units is selected in order to minimize the total cost by economic allocation of power produced and the emission cost. As a consequence, optimal allocation is performed by considering both fuel cost and emission leading to Combined Economic and Emission Dispatch (CEED). This study presents a new Meta-heuristic algorithms (MHs) called the Turbulent Flow of Water Optimization (TFWO), which is based on the behaviour of whirlpools created in turbulent water flow, for solving different variants of ELD and CEED. To verify the robustness of the TFWO, various test network of CEED with effect of valve, and ELD with losses of transmission are incorporated. In comparison with seven well-known MHs such as Cuckoo Search Algorithm (CSA), Grey Wolf Algorithm (GW), Sine Cosine Algorithm (SCA), Earth Worm Optimization Algorithm (EWA), Tunicate Swarm Algorithm (TSA), Moth Search Algorithm (MSA) and Teaching Learning Based Optimization (TLBO), the TFWO provides the minimum fuel cost and significantly robust solutions of ELD problem over all tested networks. The results confirm the potential and effectiveness of the GWO to be a promising technique to solve various ELD problems.INDEX TERMS Turbulent Flow of Water Optimization (TFWO)); Economic Load Dispatch (ELD); Combined Economic and Emission Dispatch (CEED); Metaheuristic Optimization Algorithms.

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Reserve constrained dynamic economic dispatch in multi-area power systems: An improved fireworks algorithm

Cited by 42 publications

References 37 publications

Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment

Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment

Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function

Performance of Turbulent Flow of Water Optimization on Economic Load Dispatch Problem

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