A Hybrid Big Bang–Big Crunch optimization algorithm for solving the different economic load dispatch problems

Labbi, Yacine; Attous, Djilani Ben

doi:10.1007/s13198-016-0432-4

Cited by 19 publications

(11 citation statements)

References 30 publications

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“…The proposed methods are the Big Bang-Big Crunch (BB-BC) optimization algorithm [30,31] and the Genetic Algorithm [32][33][34] for eliminating the offset value (bias cancellation) and optimization, the Kalman Filter [35][36][37] for removing outliers and noise caused by interference:…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…The BC is a concurrence operator, and the word 'mass' indicates the inverse of the objective function value. The center of mass is calculated as follows [30,31]:…”

Section: The Big Bang-big Crunch Algorithm (Bb-bc)mentioning

confidence: 99%

“…These contraction steps are performed until a specified stopping rule. The new candidates around the center of mass are then calculated as [30,31]:…”

Section: The Big Bang-big Crunch Algorithm (Bb-bc)mentioning

confidence: 99%

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Accurate indoor positioning with ultra-wide band sensors

Arsan¹

2020

Turk J Elec Eng & Comp Sci

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Ultra-wide band is one of the emerging indoor positioning technologies. In the application phase, accuracy and interference are important criteria of indoor positioning systems. Not only the method used in positioning, but also the algorithms used in improving the accuracy is a key factor. In this paper, we tried to eliminate the effects of off-set and noise in the data of the ultra-wide band sensor-based indoor positioning system. For this purpose, optimization algorithms and filters have been applied to the raw data, and the accuracy has been improved. A test bed with the dimensions of 7.35 m × 5.41 m and 50 cm × 50 cm grids has been selected, and a total of 27,000 measurements have been collected from 180 test points. The average positioning error of this test bed is calculated as 16.34 cm . Then, several combinations of algorithms are applied to raw data. The combination of Big Bang-Big Crunch algorithm for optimization, and then the Kalman Filter have yielded the most accurate results. Briefly, the average positioning error has been reduced from 16.34 cm to 7.43 cm . Key words: Indoor positioning, ultra-wide band sensors, optimization, big bang-big crunch algorithm, genetic algorithms, the Kalman filter (A-GPS) technology is a navigation system used on mobile devices that helps to identify a user's location via the base station's A-GPS address server [3]. The accuracy provided by the GPS in determining the outdoor location is between 3 m and 15 m , usually around 10 m . The accuracy that A-GPS provides in determining the outdoor location is about 15 m, while the interior is 50 m [3]. As can be seen from the accuracy values, these solutions are sufficient to determine the outdoor position, in other words, the position in the open space.On the other hand, given the fact that people now spend more than 80% of their time indoors, a suitable system for locating interior space is needed. Unfortunately, the use of GPS satellites in indoor location determination is not possible as GPS signals are weaken due to atmospheric delays, multi-paths, steel structures, roofs and building walls [1][2][3]. For this reason, efforts have been made to develop new technologies that allow reliable indoor location determination with high accuracy, low average positioning error over the past two decades.

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Section: The Proposed Methodsmentioning

confidence: 99%

“…The BC is a concurrence operator, and the word 'mass' indicates the inverse of the objective function value. The center of mass is calculated as follows [30,31]:…”

Section: The Big Bang-big Crunch Algorithm (Bb-bc)mentioning

confidence: 99%

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Accurate indoor positioning with ultra-wide band sensors

Arsan¹

2020

Turk J Elec Eng & Comp Sci

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“…Gravitational Search Algorithm used optimal scheduling of building users electricity consumption in [31] and unit commitment problem solved for electric vehicles using GSA in [32]. Economic load dispatch (ELD) problem solved by using a hybrid BBBO [33] and optimality in power for residential consumers discussed using Lyapunov optimization approach in [34]. The remaining portions of the paper have been arranged in the given way: In section 2 gives the brief discussion about DSM Techniques and strategies: problem formulation and BBO and its variants have discussed in section 3, information about the smart grid is given in section 4, simulations…”

Section: Introductionmentioning

confidence: 99%

Impact of Divergence in BBO on Efficient Energy Strategy of Demand Side Management

Sharma

Saxena²,

Palwalia

2022

Technol Econ Smart Grids Sustain Energy

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Demand Response (DR) keeps up an important character in the growth of electricity generation with transmission and distribution in the phase of advanced grid automation. For future smart grid, basically two types of Demand Side Management strategies have been used with a number of shiftable or controllable devices. In this research article, two new variants of Biogeography Based Optimization (BBO) algorithm named as Iteration Control BBO and Pandemic BBO are proposed for solving the minimization problem and definitions of these variants have been made by change in migration control � ⃗ a vector. These two variants are indirectly support the principle of No Free Lunch theorem. The beauty of these variants is that they are reported the impact of divergence in BBO on efficient energy strategy of DSM. The simulation results reported in this paper claims that the used DSM techniques acquire financial savings, while lowering and shifting peak load.

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“…Evolutionary and metaheuristic techniques are potential solution methodologies for non-convex ED problem due to their inherent ability to be independent of differentiability and continuity of the objective function. Recent Evolutionary approaches which have been widely utilized to address ED problem are: Differential Evolution (DE) [7], Particle Swarm Optimization (PSO) [8], Modified Artificial Bee Colony (MABC) [9], Hybrid GA-PS-SQP [10], New Global Particle Swarm Optimization (NGPSO) [11], Shuffled Differential Evolution (SDE) [12], Moth-Flame Optimizer [13], Harmony Search (HS) [14], Hybrid Big Bang-Big Crunch (HBB-BC) [15], Quasi-Oppositional Teaching Learning Based Optimization (QOSLTLBO) [16], Chaotic Krill-Herd algorithm (CKH) [17], Modified Water Cycle approach [18], Hybrid Cuckoo Search technique [19], Hybrid DE-FA algorithm [20], Chaotic Teacher Learner Based Optimization (CTLBO) [21], Modified Symbiotic Organisms Search Algorithm (MSOSA) [22], Tournament-based Harmony Search (THS) [23], Improved Grey Wolf optimizer (IGWO) [24], Hybrid Chemical Reaction Optimization (HCRO) [25], Diffusion Particle Optimization (DPO) [26], Chaotic Bat Algorithm (CBA) [27], Kinetic Gas Molecular Optimization (KGMO) [28], Orthogonal Learning Competitive Swarm Optimizer (OLCSO) [29].…”

Section: Introductionmentioning

confidence: 99%

Artificial Algae Algorithm with Multi-Light Source Movement for Economic Dispatch of Thermal Generation

Awais

Malik

Ahmad

2020

Mehran Univ. res. j. eng. technol.

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Economic Dispatch (ED) is one of the major concerns for the efficient and economical operation of the modern power system. Actual ED problem is non-convex in nature due to Ramp Rate Limits (RRL), Valve-Point Loading Effects (VPLE), and Prohibited Operating Zones (POZs). It is generally converted into a convex problem as mathematical programming based approaches cannot handle the non-convex cost functions except dynamic programming, which also suffers from the curse of dimensionality. Heuristic techniques are potential solution methodologies for solving the non-convex ED problem. Artificial Algae Algorithm (AAA), a recent meta-heuristic optimization approach showed remarkable results on certain MATLAB benchmark functions but its application on industrial problem such as ED is yet to be explored. In this paper, AAA is used to investigate convex and non-convex ED problem due to valve-point effects and POZs while considering the transmission losses. The robustness and effectiveness of the proposed approach are validated by implementing it on IEEE standard test systems (3, 6, 13 and 40 unit Test Systems), which are widely addressed in the literature. The simulation results are promising when compared with other well-known evolutionary algorithms, showing the potential and stability of this algorithm.

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A Hybrid Big Bang–Big Crunch optimization algorithm for solving the different economic load dispatch problems

Cited by 19 publications

References 30 publications

Accurate indoor positioning with ultra-wide band sensors

Accurate indoor positioning with ultra-wide band sensors

Impact of Divergence in BBO on Efficient Energy Strategy of Demand Side Management

Artificial Algae Algorithm with Multi-Light Source Movement for Economic Dispatch of Thermal Generation

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