Nur Azzammudin Rahmat

Economic load dispatch with valve-point loading effect by using Differential Evolution Immunized Ant Colony optimization technique

Economic load dispatch is conducted by the utilities in order to determine the best generation level at the most feasible operating cost. In order to guarantee satisfying energy delivery to the consumer, a precise calculation of generation level is required. In order to achieve accurate and practical solution, several considerations such as prohibited operating zones, valve-point effect and ramp-rate limit need to be taken into account. However, these considerations cause the optimization to become complex and difficult to solve. This research focuses on the valve-point effect that causes ripple in the fuel-cost curve. This paper also proposes Differential Evolution Immunized Ant Colony Optimization (DEIANT) in solving economic load dispatch problem with valve-point effect. Comparative studies involving DEIANT, EP and ACO are conducted on IEEE 30-Bus RTS for performance assessments. Results indicate that DEIANT is superior to the other compared methods in terms of calculating lower operating cost and power loss.

Fuzzy unit commitment for cost minimization in power system planning

Unit commitment is among of the key elements in power system planning. Unit commitment is extensively applied by the power utilities to plan the optimal dispatch of generating units in the system. In the deregulated power system industry, it is important to consider several uncertainty constraints during the planning process. This research proposes the application of fuzzy set modeling to determine the uncertainty constraints. Several intelligence techniques including Particle Swarm Optimization, Ant Colony Optimization, and Differential Evolution Immunized Ant Colony Optimization approaches have been used to optimize the fuzzy unit commitment problem. The verification process was performed on IEEE 30-Bus Reliable Test System (RTS). Comparative studies among PSO, ACO and DEIANT indicate the superiority of DEIANT in solving the fuzzy unit commitment problem.

Multi-Objective Optimization for Sizing of Distributed Generation Using Cuckoo Search Algorithm

This paper presents multi-objective optimization for sizing of distributed generation using cuckoo search algorithm. The study involved the development of cuckoo search optimization engine. Prior to the development of multi-objective for cuckoo algorithm, a pre-developed voltage stability index termed as FVSI for location identification is used in this study. Weighted sum technique is used as the fitness for the problem formulation. Objectives of the study are to minimize the total real power and improve its voltage stability condition. Test is done on IEEE 69-Bus Radial Distribution System. Results obtained from the study indicated that the proposed technique is feasible for further implementation in power system.

Differential Evolution Immunized Ant Colony Optimization Technique (DEIANT) in solving economic dispatch by considering prohibited operating zones

In energy industry, generating the correct amount of electrical power is crucial. Economic load dispatch is used to compute the necessary amount of power among the generators. However, each generator in a system is limited by its physical properties that will limit its maximum potential. This prohibited zone divides the actual operation limits of a particular generator into several subdivisions. This paper proposes Differential Evolution Immunized Ant Colony Optimization (DEAINT) technique in solving economic dispatch by considering prohibited operating zones. The optimization process was conducted on IEEE 30-Bus Reliable Test System (RTS). Verification of DEIANT technique was performed by comparing it with Evolutionary Programming (EP) and Ant Colony Optimization (ACO) technique. The comparative studies indicate that DEIANT outperformed EP and ACO in terms of achieving lower operating cost and power loss.

Developed cluster of SVC installation in power system network via hybrid meta-heuristic method

This paper introduces a new approach of meta-heuristic based method for clustering the optimal location of SVC installation in power system. The algorithm is based on evolutionary particle swarm optimization (EPSO) technique with the objective to minimize the transmission loss in power system. With the formation of cluster decision can be made by power system operators to perform power compensation scheme considering selected loading conditions and loaded buses. Experiments were performed on the IEEE 30-bus RTS to realize the effectiveness of the proposed method. Comparison with respect to conventional PSO was conducted which eventually resulted superiority in terms of loss minimization.

Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique in solving economic emission dispatch

Emission dispatch is a topic that discusses on the discharge of polluting substance by fossil-fuelled generators. The arising concerns towards environmental quality arouse new trend in power flow studies. Emission dispatch has become a vital consideration during load dispatch scheduling and the power utilities are urged to reduce the pollutant volume to the least. Numerous approaches have been employed to solve emission dispatch. This research highlights the implementation of Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique in solving economic emission dispatch. DEIANT algorithm was compared with several approaches including the conventional method, PSO, and ACO algorithm in order to verify the performance of the algorithm. To apprehend the effectiveness of the new algorithm, IEEE 30-Bus Reliable Test System (RTS) was utilized as the sample. The obtained results revealed that DEIANT is more superior to the traditional method, PSO, and ACO, and effectively minimize the emission level.

Solving Fuzzy Combined Economic Load–Emission Dispatch by Using Differential Evolution Immunized Ant Colony Optimization Technique

The fluctuating load demand with respect to time requires thorough analysis by the energy providers. Nowadays, the utilities need to include emission control during energy dispatch planning. The practically accurate economic dispatch solution is achieved by considering it as a dynamic or time-varying problem. Therefore, this research proposes Fuzzy Combined Economic Load-Emission Dispatch (Fz-CELED) to solve dynamic economic dispatch problem. Fuzzy Logic is used to predict the future load demand and fuel pricing. Moreover, this paper proposed the Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique to optimize Fz-CELED problem. The research was conducted on IEEE 57-Bus Systems. Comparative studies are also conducted among DEIANT, ACO and EP to assess their performance.

Optimization of Hybrid Renewable Energy System (HRES) Using Modified Evolutionary Strategy for Cost Minimization

Recently, renewable energy has been in place to cater the depreciation of main energy. The presence of renewable energy sources can be made in hybrid to satisfy the demand in the distribution system. Nevertheless, the growth in number for renewable energy could lead to cost increment. This paper presents the optimization process of Hybrid Renewable Energy System (HRES) using Modified Evolutionary Strategy (ES) technique for cost minimization. The study involves the development of optimization engine for modified ES in order to solve the cost minimization of HRES. The improved version of ES is expected to address the computation burden experienced by the traditional ES technique. Results obtained from the implementation of the modified ES managed to reveal that its implementation is worth in terms of minimizing the cost

Cuckoo Search Algorithm in Loss Minimization via Capacitor Placement in Distribution System

Improper placement of capacitor as one of the compensating devices will lead to under-compensation or over-compensation which may lead to possible monetary losses. Thus optimization process has become a priori to address this problem. This paper presents cuckoo search algorithm in loss minimization via capacitor placement in distribution system. Implementation of sensitivity analysis for location identification; followed by optimal sizing determination via cuckoo search is a remarkable effort for the compensating scheme. Validation on a reliability test model, namely the IEEE 33-bus radial distribution system has indicated promising results. With the development of optimization engine, an attempt to assess its feasibility can be done through the implementation on larger test system. This is demonstrated by the simulation results, which revealed that cuckoo is feasible in ensuring loss has been minimized while maintaining voltage level within the acceptable range

Solving Emission Dispatch Problem with Multiple Fuel Option by Using Differential Evolution Immunized Ant Colony Optimization Technique

Emission dispatching is conducted to calculate the lowest amount of emission while generating satisfying output to the load demand. The utilities are restricted by emission regulation that limits the emission level to a certain amount. This paper proposes emission dispatch with multiple fuel option (EDMFO) to determine the optimal emission level. The EDMFO allows the operators to select different type of fuel according to the generation level and requirement. The emission dispatch problem is optimized by using Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique. Validation process is conducted by comparing DEIANT with several optimization approaches including ACO and EP. The comparison took places in IEE 57-Bus RTS. Results indicate that DEIANT is superior in terms of calculating the lowest emission level, lower operating cost and the best selection of fuel according to the generation requirement.