Combined heat and power economic dispatch using integrated civilized swarm optimization and Powell’s pattern search method

Economic Power and Heat Dispatch in Cogeneration Energy Systems Using Manta Ray Foraging Optimizer

“…Additionally, Table 3 illustrates detailed comparison between the optimal solution based on MRFOA with those manifested by various optimization techniques. This table illustrates the great effectiveness and superiority of the proposed MRFOA in finding the minimum operational cost compared to EP [10], PSO [10], RCGA [31], RCGA-IMM [18], CSO [25], AIS [32], CSO&PPS [22], LCA [33], IGA-NCM [43], DE [10], BCO [31], CPSO [34], TVAC-PSO [15], TLBO [34], TVAC-PSO [16], WVO [14], and WVO-PSO [14]. It is lucid that the proposed MRFOA achieves 100% accuracy for equality constraints that the summation of power and heat demands are precisely 600 MW and 150 MWth, respectively.…”

“…The proposed MRFOA and other optimization techniques are employed on this case and the related the tabulated solutions in Table 4. This table includes the results of a plethora of optimization techniques, which are TVAC-PSO [15], CPSO [15], TVAC_PSO [15], CSO&PPS [22], TLBO [34], GSO [37], MGSO [37], OTLBO [34], GSA [38], and MPSO [12], as depicted in Table 4 (a), (b), and (c) respectively. Table 5 tabulates the TFC objectives that are related to the recorded operating points in Table 4.…”

“…Also, an invasive weed optimizer (IWO) [21] based on the process of weed colonization/distribution has been applied optimal operation of the CES for small scale EPHD problems. In addition, an integrated technique, which combined the civilized swarm optimization (CSO) and the Powell's pattern search (PPS) method [22], has been carried out to solve the EPHD problem in CES. Furthermore, utilizion and assessment for the available reserve capacity of CHP units is develoloped in [23].…”

Combined Heat and Power Economic Emission Dispatch Using Hybrid NSGA II-MOPSO Algorithm Incorporating an Effective Constraint Handling Mechanism

“…To obtain the solution of the CHPED problem is challenging due to the interdependence of heat and power generation of the CHP unit, and it requires highly efficient algorithms to obtain the optimal solution. The metaheuristic algorithms such as gravitational search algorithm in [34], grey wolf optimization in [35], improved genetic algorithm (GA) in [36], [37], modified PSO in [38], Cuckoo optimization in [39], [40], civilized swarm optimization in [41], exchange market algorithm in [42], the differential algorithm in [43], bee colony optimization in [44], [45], artificial immune system algorithm in [46], oppositional teaching learning based optimization in [47], the harmony search algorithm in [48], [49] and its variants in [50], the squirrel search algorithm in [51], group search optimization in [52] and other methods such as Lagrangian relaxation in [53], benders decomposition approach in [54] are used in literature to obtain the optimal solution of the CHPED problem. The hybrid methods that have been successfully employed to solve the CHPED problem are the hybrid bat and ABC algorithm in [55], hybrid harmony search and PSO algorithm in [56], hybrid harmony search algorithm and Nelder-Mead numerical method in [57].…”

Research on the Economic Benefit Evaluation of Combined Heat and Power (CHP) Technical Renovation Projects Based on the Improved Factor Analysis and Incremental Method in China

“…The advantages of CHP technology for energy savings and emissions reduction have been widely accepted [9]. The boiler of a cogeneration unit has high thermal efficiency [10], a remarkable dust removal effect, and can reduce the emission of smoke into the atmosphere [11], which can effectively improve the environmental quality and save a lot of fuel [12]. According to existing literature, a great number of domestic and overseas scholars have mainly studied the technical route, energy-saving effect, project investment risk and economic benefits of cogeneration.…”