Large-scale multi-area economic/emission dispatch based on a new symbiotic organisms search algorithm

Secui, Dinu Călin

doi:10.1016/j.enconman.2017.09.075

Cited by 45 publications

(19 citation statements)

References 75 publications

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“…Heuristic techniques, on the other hand, may reach a sub-optimum solution, but their computational time is very competitive, which make them adequate for real-time application. Much progress was made in heuristic techniques that have proven their efficiency as competitive optimization methods in power system [3,5,7,[35][36][37]. The artificial immune algorithm is inspired from the biological process of immune cells defense mechanism.…”

Section: Proposed Algorithm For the Real-time Optimizationmentioning

confidence: 99%

“…In the conventional power system, the problem is modeled as a quadratic cost function which is solved by classical methods such as Lagrange multiplier method, base point participation factor, lambda iteration, Newton's method, gradient method, mixed integer linear programming, and linear programming [3]. Most of previous works presented a power dispatch of thermal generators which makes the cost function considered not suitable for MG optimization [4,5]. Besides, some of those used technics suffer from some limitations such as the assumption that the incremental cost curves of the generation units are monotonically increasing piecewise linear functions and the high dependency on the specific mathematical model.…”

Section: Introductionmentioning

confidence: 99%

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An Optimal Energy Management System for Real-Time Operation of Multiagent-Based Microgrids Using a T-Cell Algorithm

et al. 2019

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The real-time operation of the energy management system (RT-EMS) is one of the vital functions of Microgrids (MG). In this context, the reliability and smooth operation should be maintained in real time regardless of load and generation variations and without losing the optimum operation cost. This paper presents a design and implementation of a RT-EMS based on Multiagent system (MAS) and the fast converging T-Cell algorithm to minimize the MG operational cost and maximize the real-time response in grid-connected MG. The RT-EMS has the main function to ensure the energy dispatch between the distributed generation (DG) units that consist in this work on a wind generator, solar energy, energy storage units, controllable loads and the main grid. A modular multi-agent platform is proposed to implement the RT-EMS. The MAS has features such as peer-to-peer communication capability, a fault-tolerance structure, and high flexibility, which make it convenient for MG context. Each component of the MG has its own managing agent. While, the MG optimizer (MGO) is the agent responsible for running the optimization and ensuring the seamless operation of the MG in real time, the MG supervisor (MGS) is the agent that intercepts sudden high load variations and computes the new optimum operating point. In addition, the proposed RT-EMS develops an integration of the MAS platform with the Data Distribution Service (DDS) as a middleware to communicate with the physical units. In this work, the proposed algorithm minimizes the cost function of the MG as well as maximizes the use of renewable energy generation; Then, it assigns the power reference to each DG of the MG. The total time delay of the optimization and the communication between the EMS components were reduced. To verify the performance of our proposed system, an experimental validation in a MG testbed were conducted. Results show the reliability and the effectiveness of the proposed multiagent based RT-EMS. Various scenarios were tested such as normal operation as well as sudden load variation. The optimum values were obtained faster in terms of computation time as compared to existing techniques. The latency from the proposed system was 43% faster than other heuristic or deterministic methods in the literature. This significant improvement makes this proposed system more competitive for RT applications.

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Section: Proposed Algorithm For the Real-time Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Optimal Energy Management System for Real-Time Operation of Multiagent-Based Microgrids Using a T-Cell Algorithm

et al. 2019

View full text Add to dashboard Cite

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“…Evolutionary algorithms such as genetic algorithm (GA), 4 evolutionary programming (EP), 5 hybrid EP, LP, 6 and improved particle swarm optimization (IPSO) 7 have been used to solve economic load dispatch (ELD) problems with security constraints as alternative techniques to achieve the best solution when compared with conventional techniques. Symbiotic organisms search (SOS) 17 algorithm has been developed with a new procedure in updating the solutions during iterative process and the elimination of parasitism phase. 8 In recent studies, a lot of new algorithms were proposed to solve ELD problems, one of which is backtracking search optimization (BSA) 9 method in which two new crossover and mutation operators were introduced to find a global solution.…”

Section: Introductionmentioning

confidence: 99%

“…"Modified artificial bee colony based on chaos" (CIABC) has been introduced in the literature 16 to solve multiobjective optimization problems (MoPs). Symbiotic organisms search (SOS) 17 algorithm has been developed with a new procedure in updating the solutions during iterative process and the elimination of parasitism phase. Chaotic self-adaptive differential harmony search (CSADHS) algorithm was developed in the earlier study 18 to solve MoPs.…”

Section: Introductionmentioning

confidence: 99%

Chaotic self‐adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

Rajagopalan

Kasinathan²,

Karthik

et al. 2019

Int Trans Electr Energ Syst

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Summary The main goal behind the combined economic emission dispatch (CEED) is to reduce the costs incurred upon fuel and emission for the generating units available without any intention to violate the generator and security constraints. Hence, the CEED must be handled after considering two challenging goals such as the costs involved with emission and fuel. In this paper, chaotic self‐adaptive interior search algorithm (CSAISA) was proposed to solve the CEED problems, considering the nonlinear behavior of generators in terms of valve point effects, prohibited operating zones, and security constraints. The proposed algorithm was tested for its effectiveness using 11‐generating units (without security), IEEE‐30 bus system, and IEEE‐118 bus system with security constraints. The results of the proposed CSAISA were compared with interior search algorithm (ISA), harmony search algorithm (HSA), differential evolution (DE), particle swarm optimization (PSO), and genetic algorithm (GA). To conclude, the proposed CSAISA outperformed all other algorithms in terms of convergence speed, implementation time, and solution quality, which was tested using performance metrics.

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“…In addition, the constraints that need to be addressed in carrying out the MAED study are tie-line. Some mathematical methods such as linear programming [17], [19] or taking into account the stability of index either the strength of the bus or the line power to make the connection [20]. There are studies using expert systems [21] or Dantzig-Wolfe decomposition principles [22] to solve MAED problems.…”

Section: Introductionmentioning

confidence: 99%

Multi-Area Economic Dispatch by Using Differential Evolution Immunized Ant Colony Optimization (DEIANT)

Marzuki

Rahmat²,

Salleh

et al. 2019

IJEAT

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Economic dispatch is an important issue within the electrical system in meeting the lowest cost of the system and is subject to transmission and operating constraints.The power system operation and planning economic dispatch required a reliable technique to achieve minimal cost in economic dispatch otherwise the objective to minimize the generation cost fail. The electrical transmission network does not make complete electricity generation in Single-area economic dispatch. Thus, to complete the economic dispatch for the power transmission system, the multi-area network is proposed. The Multi-Area Economic Dispatch(MAED) connects two or more areas through a tie-line. Each region has a specific cost and load pattern. Tie-lines are used as connectors to enable power switching between regions. 31-Bus test system tested using an algorithm known as Differential Evolution Immunized Ant Colony Optimization (DEIANT) with different case studies with several trials taken to assess the consistency of results. Comparative studies with Pre-Optimization and Newton Rap son revealed that DEIANT technique is more reliable for multi-area power system network.

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Large-scale multi-area economic/emission dispatch based on a new symbiotic organisms search algorithm

Cited by 45 publications

References 75 publications

An Optimal Energy Management System for Real-Time Operation of Multiagent-Based Microgrids Using a T-Cell Algorithm

An Optimal Energy Management System for Real-Time Operation of Multiagent-Based Microgrids Using a T-Cell Algorithm

Chaotic self‐adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

Multi-Area Economic Dispatch by Using Differential Evolution Immunized Ant Colony Optimization (DEIANT)

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