Abstract: In this paper, an approach combining analytical method for the distributed generator (DG) sizing and meta-heuristic search for the optimal location of DG has been presented. The optimal size of DG on each bus is estimated by the loss sensitivity factor method while the optimal sites are determined by Particle Swarm Optimization (PSO) based optimal reactive power dispatch for minimizing active power loss. To confirm the proposed approach, it has been tested on IEEE-30 bus test system. The adjustments of operating constraints and voltage profile improvements have also been observed. The obtained results show that the allocation of DGs results in a significant loss reduction with good voltage profiles and the combined approach is competent in keeping the system voltages within the acceptable limits.
Abstract: This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.
Abstract: In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO2, NOx, and SO2. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.
Abstract: The objective of the Economic Dispatch(ED) Problems
of electric power generation is to schedule the committed generating
units outputs so as to meet the required load demand at minimum
operating cost while satisfying all units and system equality and
inequality constraints. This paper presents a new method of ED
problems utilizing the Max-Min Ant System Optimization.
Historically, traditional optimizations techniques have been used,
such as linear and non-linear programming, but within the past
decade the focus has shifted on the utilization of Evolutionary
Algorithms, as an example Genetic Algorithms, Simulated Annealing
and recently Ant Colony Optimization (ACO). In this paper we
introduce the Max-Min Ant System based version of the Ant System.
This algorithm encourages local searching around the best solution
found in each iteration. To show its efficiency and effectiveness, the
proposed Max-Min Ant System is applied to sample ED problems
composed of 4 generators. Comparison to conventional genetic
algorithms is presented.
Abstract: Ancillary services are support services which are
essential for humanizing and enhancing the reliability and security of
the electric power system. Reactive power ancillary service is one of
the important ancillary services in a restructured electricity market
which determines the cost of supplying ancillary services and finding
of how this cost would change with respect to operating decisions.
This paper presents a new formation that can be used to minimize the
Independent System Operator (ISO)’s total payment for reactive
power ancillary service. The modified power flow tracing algorithm
estimates the availability of reserve reactive power for ancillary
service. In order to find optimum reactive power dispatch,
Biogeography based optimization method (BPO) is proposed. Market
Reactive Clearing Price (MRCP) is then estimated and it encourages
generator companies (GENCOs) to participate in an ancillary service.
Finally, optimal weighting factor and real time utilization factor of
reactive power give the minimum ISO’s total payment. The
effectiveness of proposed design is verified using IEEE 30 bus
system.
Abstract: Distributed generation units (DGs) are grid-connected or stand-alone electric generation units located within the electric distribution system at or near the end user. It is generally accepted that centralized electric power plants will remain the major source of the electric power supply for the near future. DGs, however, can complement central power by providing incremental capacity to the utility grid or to an end user. This paper presents an efficient power dispatching model for hybrid wind-Solar power generation system, to satisfy some essential requirements, such as dispersed electric power demand, electric power quality and reducing generation cost and so on. In this paper, presented some elements of the main parts in the hybrid system; and then made fundamental dispatching strategies according to different situations; then pointed out four improving measures to improve genetic algorithm, such as: modify the producing way of selection probability, improve the way of crossover, protect excellent chromosomes, and change mutation range and so on. Finally, propose a technique for solving the unit's commitment for dispatching problem based on an improved genetic algorithm.
Abstract: Optimal Power Flow (OPF) problem in electrical power system is considered as a static, non-linear, multi-objective or a single objective optimization problem. This paper presents an algorithm for solving the voltage stability objective reactive power dispatch problem in a power system .The proposed approach employs cat swarm optimization algorithm for optimal settings of RPD control variables. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. CSO algorithm is tested on standard IEEE 30 bus system and the results are compared with other methods to prove the effectiveness of the new algorithm. As a result, the proposed method is the best for solving optimal reactive power dispatch problem.
Abstract: This paper describes an efficient and practical method
for economic dispatch problem in one and two area electrical power
systems with considering the constraint of the tie transmission line
capacity constraint. Direct search method (DSM) is used with some
equality and inequality constraints of the production units with any
kind of fuel cost function. By this method, it is possible to use several
inequality constraints without having difficulty for complex cost
functions or in the case of unavailability of the cost function
derivative. To minimize the number of total iterations in searching,
process multi-level convergence is incorporated in the DSM.
Enhanced direct search method (EDSM) for two area power system
will be investigated. The initial calculation step size that causes less
iterations and then less calculation time is presented. Effect of the
transmission tie line capacity, between areas, on economic dispatch
problem and on total generation cost will be studied; line
compensation and active power with reactive power dispatch are
proposed to overcome the high generation costs for this multi-area
system.
Abstract: In this paper, an Interactive Compromise Approach
with Particle Swarm Optimization(ICA-PSO) is presented to solve the
Economic Emission Dispatch(EED) problem. The cost function and
emission function are modeled as the nonsmooth functions,
respectively. The bi-objective including both the minimization of cost
and emission is formulated in this paper. ICA-PSO is proposed to
solve EED problem for finding a better compromise solution. The
solution methodology can offer a global or near-global solution for
decision-making requirements. The effectiveness and efficiency of
ICA-PSO are demonstrated by a sample test system. Test results can
be shown that the proposed method provide a practical and flexible
framework for power dispatch.
Abstract: This paper solves the environmental/ economic dispatch
power system problem using the Non-dominated Sorting Genetic
Algorithm-II (NSGA-II) and its hybrid with a Convergence Accelerator
Operator (CAO), called the NSGA-II/CAO. These multiobjective
evolutionary algorithms were applied to the standard IEEE 30-bus
six-generator test system. Several optimization runs were carried out
on different cases of problem complexity. Different quality measure
which compare the performance of the two solution techniques were
considered. The results demonstrated that the inclusion of the CAO
in the original NSGA-II improves its convergence while preserving
the diversity properties of the solution set.