Combined heat and power economic dispatch using an adaptive cuckoo search with differential evolution mutation

Yang, Qiangda; Liu, Peng; Zhang, Jie; Dong, Ning

doi:10.1016/j.apenergy.2021.118057

Cited by 39 publications

(10 citation statements)

References 59 publications

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“…In literature [32], the modified grasshopper optimization algorithm and the improved harris hawks optimizer were applied to the economic scheduling of cogeneration system. In literature [33], an adaptive cuckoo search with differential evolution mutation was proposed to solve the economic scheduling problem of the cogeneration system. Among the many intelligent algorithms, the memetic algorithm combined global evolution with local search and had been successfully applied to many fields because of its excellent optimization ability and wide applicability.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Li¹,

Wang²,

Pang³

et al. 2023

Energy Engineering

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Electric-heat coupling characteristics of a cogeneration system and the operating mode of fixing electricity with heat are the main reasons for wind abandonment during the heating season in the Three North area. To improve the wind-power absorption capacity and operating economy of the system, the structure of the system is improved by adding a heat storage device and an electric boiler. First, aiming at the minimum operating cost of the system, the optimal scheduling model of the cogeneration system, including a heat storage device and electric boiler, is constructed. Second, according to the characteristics of the problem, a cultural gene algorithm program is compiled to simulate the calculation example. Finally, through the system improvement, the comparison between the conditions before and after and the simulation solutions of similar algorithms prove the effectiveness of the proposed scheme. The simulation results show that adding the heat storage device and electric boiler to the scheduling optimization process not only improves the wind power consumption capacity of the cogeneration system but also reduces the operating cost of the system by significantly reducing the coal consumption of the unit and improving the economy of the system operation. The cultural gene algorithm framework has both the global evolution process of the population and the local search for the characteristics of the problem, which has a better optimization effect on the solution.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Li¹,

Wang²,

Pang³

et al. 2023

Energy Engineering

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“…This scenario have 30 number of variables, 32 number of constraints and is solved by implementing HBO and IHBO techniques. The optimal output of TGUs, CGUs and HGUs obtained by the proposed IHBO and HBO algorithms are presented in Table 6 and are compared with TVAC‐PSO [23], TLBO [48], JADE [23], ACS [23], HTS [43] and BLPSO [46]. The best cost is achieved by IHBO approach and found to be 57841.4831$/h, which is less among 58122.75$/h, 58014.58$/h, 57919.4365$/h, 57842.99$/h, 57853.39$/h and 57843.2853$/h attained by TVAC‐PSO, TLBO, JADE, ACS, HTS, BLPSO and HBO techniques, respectively.…”

Section: Case Studiesmentioning

confidence: 99%

“…In [22], a squirrel search algorithm is suggested for solving the multi-region generating units dispatch problem with integration of solar and wind power. The valve-point loading with certain impact on optimal dispatch of generating units were analysed by the authors in [23][24][25]. But feasible operating region and complexity in constraints associated with the generating units are the main obstacles [17].…”

Section: Introductionmentioning

confidence: 99%

Optimal dispatch of combined heat and power generating units with prohibited operating zones using improved heap‐based optimizer

Sahoo,

Sahu,

Hota

et al. 2023

IET Generation Trans & Dist

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In the present market scenario, energy cost has been increased and also restrictions have been faced in fossil fuels energy sources. This leads to evolvement of combined heat and power generating units having higher efficiency as compared to the existing systems. The optimal dispatch of CGUs involves a number of intricate constraints, making it a practical optimization problem. So, an improved heap‐based optimizer algorithm has been implemented in this work for solving optimal dispatch problem by accomplishing a proper balance between initial and final stages of global search and convergence, respectively. This problem provides optimal scheduling of heat and power generating units and seeks to minimize the overall fuel cost supply of combined units considering their operational limits. Here, three test systems, that is, 7‐units, 24‐units and 48 units system have been taken into consideration to verify the performance of proposed IHBO algorithm. The impact of prohibited zones on power dispatch has been analysed for both the system in an electricity market. In addition, the valve‐point loading effect, mutual dependency of produced heat and power of combined units and also transmission power losses in transmission lines have been studied. Comparisons among different methods have been made based on their respective solutions obtained and from that it manifests the robustness and superior performance of the proposed technique. Verification studies showed that impact of prohibited zones on generating units, increases the production cost with respect to without prohibited zones. However the proposed technique yields least production cost among other techniques.

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“…In Ref. [21], the combined heat and power economic dispatch problem is solved by an adaptive CSO. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Clustering Cuckoo Search Optimization Implemented in Optimal Setting of Directional Overcurrent Relays

Ma¹,

2022

Mathematical Problems in Engineering

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This study has proposed a hierarchical clustering cuckoo search optimization (HCSO) to solve the optimal setting problems of directional overcurrent relays (DOCRs) in the power system. Different from the randomly generated stepsize θ in traditional CSO, stepsize θ in HCSO is updated by a hierarchical clustering mechanism, which can balance the searching priority of exploration and exploitation for each solution. The superiority of HCSO is evaluated by solving the DOCRs coordination problem with the 3-bus, 8-bus, and 9-bus system, presented by linear programming (LP), nonlinear programming (NLP), and mixed integer nonlinear programming (MINLP) forms. Results show that under the same parameter setting conditions, the minimum value of the objective function by HCSO has reduced by 10.93 % , 2.93 % , and 0.46 % , respectively, compared to that of CSO in the experimented cases 2, 3, and 4. It verifies that HCSO is more competitive than CSO in solving the DOCRs optimal setting problem irrespective of the DOCRs number and formulation type.

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Combined heat and power economic dispatch using an adaptive cuckoo search with differential evolution mutation

Cited by 39 publications

References 59 publications

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Optimal dispatch of combined heat and power generating units with prohibited operating zones using improved heap‐based optimizer

Hierarchical Clustering Cuckoo Search Optimization Implemented in Optimal Setting of Directional Overcurrent Relays

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