A novel algorithm for economic load dispatch of power systems

He, Xiangzhu; Rao, Yunqing; Huang, Jida

doi:10.1016/j.neucom.2015.07.107

Cited by 81 publications

(41 citation statements)

References 51 publications

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“…The unit commitment layer of the blockchain is extended based on the traditional unit commitment model [22]. According to the load generation plan issued by the power dispatching center, the model of centralized optimal dispatching of each unit is adopted.…”

Section: Analysis Of Demand Contractmentioning

confidence: 99%

Research on Bidding Mechanism for Power Grid with Electric Vehicles Based on Smart Contract Technology

et al. 2020

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To promote coordinated development of electric vehicles (EVs) and power grid under open power selling, a bidding mechanism using blockchain smart contract technology was proposed. By demand respone management (DRM) on and off the blockchain, based on different driving characteristics of EV subgroups, various charging–discharging demands and constraints were fully considered between EV user subgroups and agent. Purchase–sale transaction relationship and unit commitment plan were fully considered between the EV agent and power dispatching center under economic dispatching. Aiming at the lowest power purchase cost of EV users, the highest profit of EV agent and the lowest cost of power economic dispatching, smart contract models with optimal benefits were established among the three. The smart contract models were solved by combining the internal and external optimization relationship of particle swarm and genetic algorithms. The charging–discharging price was optimized by DRM to realize the reasonable allocation of charging–discharging resources of EVs. An example analysis shows that this bidding mechanism can achieve peak–cutting and valley–filling for power load. At the same time, it can effectively protect the benefits of EV users, agent, and power dispatching center. This result can provide a reference for the application of smart contract in bidding of EVs to the power grid.

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Section: Analysis Of Demand Contractmentioning

confidence: 99%

Research on Bidding Mechanism for Power Grid with Electric Vehicles Based on Smart Contract Technology

et al. 2020

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“…The ELD problem is described as an objective function to minimize the total fuel cost while satisfying different constraints, we adopt the problem formulation described in [16,42].…”

Section: Problem Formulationmentioning

confidence: 99%

A Novel Multi-Population Based Chaotic JAYA Algorithm with Application in Solving Economic Load Dispatch Problems

Kim

Wadood

et al. 2018

Energies

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Abstract:The economic load dispatch (ELD) problem is an optimization problem of minimizing the total fuel cost of generators while satisfying power balance constraints, operating capacity limits, ramp-rate limits and prohibited operating zones. In this paper, a novel multi-population based chaotic JAYA algorithm (MP-CJAYA) is proposed to solve the ELD problem by applying the multi-population method (MP) and chaotic optimization algorithm (COA) on the original JAYA algorithm to guarantee the best solution of the problem. MP-CJAYA is a modified version where the total population is divided into a certain number of sub-populations to control the exploration and exploitation rates, at the same time a chaos perturbation is implemented on each sub-population during every iteration to keep on searching for the global optima. The proposed MP-CJAYA has been adopted to ELD cases and the results obtained have been compared with other well-known algorithms reported in the literature. The comparisons have indicated that MP-CJAYA outperforms all the other algorithms, achieving the best performance in all the cases, which indicates that MP-CJAYA is a promising alternative approach for solving ELD problems.

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“…Banerjee et al [31] have proposed Teaching learning based optimization (TLBO) to find the solution of ELD. Chaotic teaching-learning based optimization with Levy flight (CTLBO) has been proposed by He et al [32] in order to solve ELD problems.…”

Section: Oppositional Real Coded Chemical Reaction Optimization (Orccmentioning

confidence: 99%

Quasi-Oppositional Symbiotic Organisms Search Algorithm for Different Economic Load Dispatch Problems

2018

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In this paper, an effective meta-heuristic technique called Quasi-Oppositional Symbiotic Organisms Search is applied for solving non-convex economic dispatch problems. Symbiotic Organisms Search is a soft computing technique, inspired by organisms in the ecosystem. This technique is implemented for improving the solution quality in minimum time. In order to improve convergence rate, quasi-reflected numbers are used here instead of pseudo-random numbers. Different equality and inequality constraints such as transmission loss, load demand, prohibited operating zone, generator operating limits and boundary of ramp rate are considered here. Presence of multiple fuels and valve point are also considered in some cases. This algorithm is applied to four different test systems. Simulation results are compared with many recently developed optimization techniques to show the superiority and consistency of this method. Simulation results also show that the computational efficiency of this algorithm is much better than the other meta-heuristic methods available in the literature.

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A novel algorithm for economic load dispatch of power systems

Cited by 81 publications

References 51 publications

Research on Bidding Mechanism for Power Grid with Electric Vehicles Based on Smart Contract Technology

Research on Bidding Mechanism for Power Grid with Electric Vehicles Based on Smart Contract Technology

A Novel Multi-Population Based Chaotic JAYA Algorithm with Application in Solving Economic Load Dispatch Problems

Quasi-Oppositional Symbiotic Organisms Search Algorithm for Different Economic Load Dispatch Problems

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