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The accuracy of two calculation algorithms of the Eclipse 8.9 treatment planning system (TPS)—the anisotropic analytic algorithm (AAA) and pencil-beam convolution (PBC)—in modeling the enhanced dynamic wedge (EDW) was investigated. Measurements were carried out for 6 and 18 MV photon beams using a 2D ionization chamber array. Accuracy of the TPS was evaluated using a gamma index analysis with the...
The optimal economic-emission dispatch problem (EED) is addressed in this paper considering the environmental aspects. To solve this multi-objective problem, a modified bacterial foraging algorithm (MBFA) is implemented. In addition to minimizing the cost function, the minimization of NOx, SO2 and CO2 gaseous emissions is also considered using the weighted-sum method. The BFA is an evolutionary optimization...
A modified bacterial foraging algorithm (MBFA) is presented in this paper to solve the short-term generation coordination problem of hydro-thermal systems with multi-chain reservoirs. The short-term hydro-thermal coordination problem (STHTC) is a dynamic nonlinear large-scale optimization problem which requires solving unit commitment and economic power load dispatch problems. The original bacterial...
In this paper, optimum scheduling of hydro-thermal power systems with variable-head hydro plants is considered. The problem is solved using an enhanced bacterial foraging algorithm (EBFA). The short-term hydro-thermal scheduling (STHTS) problem treated is a dynamic large-scale optimization problem. The bacterial foraging algorithm (BFA) is one of the modern evolutionary techniques inspired by the...
In this paper, the short-term hydro-thermal scheduling (STHTS) optimization problem is treated considering the environmental aspects. An improved bacterial foraging algorithm (IBFA) is implemented to solve this bi-objective problem. In addition to minimizing the cost function, the minimization of nitrogen oxides (NOx) is also considered. The environmentally constrained STHTS problem, as it is the...
This paper presents an improved bacterial foraging algorithm (IBFA) to find the optimal short-term hydro-thermal generation scheduling (STHTS). The STHTS problem is a dynamic large-scale nonlinear optimization problem which requires solving the unit commitment and economic power load dispatch problems. The bacterial foraging algorithm (BFA) is a recently developed evolutionary optimization technique...
This paper presents a modified bacterial foraging algorithm (MBFA) to solve the economic dispatch problem (ED) considering valve-point effects and power losses. The basic bacterial foraging algorithm (BFA) is an evolutionary optimization technique inspired by the foraging behavior of the E. coli bacteria. The original BFA has been successfully used for small scale optimization problems. On the other...
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