Power Oscillation Damping Control using Robust Coordinated Smart Devices

The lack of damping of the electromechanical oscillation modes usually causes severe problems of low frequency oscillations in interconnected power systems. In the extreme operating conditions, PSS may fail to damp power oscillation. This paper presents a robust coordinated design of power system stabilizer (PSS) and thyristor controlled series capacitor (TCSC) to damp power oscillation in an interconnected power system. The inverse additive perturbation is applied to represent unstructured uncertainties in the power system such as variations of system parameters, system generating and loading conditions. In addition, genetic algorithm is employed to search a robust tuning to the controller parameters of both PSS and TCSC simultaneously. Simulation studies have been done in a single machine infinite bus system to confirm that the performance and robustness of the proposed controller are superior to that of the conventional controller

Integrated Gas – Electricity Network - Combined Heat and Power Optimization with Associated Petroleum and Wet Gas Utilization Constraint

Aside from liquid hydrocarbon, oil exploration also produces associated petroleum gas and wet gas. The use of associated petroleum and wet gas adversely affects gas turbine performance and gas line operation in several ways such as low gas quality, unstable heating value, and high H2S content. This research develops an integrated gas – combined heat and power optimal power flow with associated petroleum and wet gas utilization constraint.  Thermodynamic equations are used to model gas turbine and gas network operation when subjected to low-quality fuels. To meet the fuel quality standard, additional constraints are considered. These constraints include the Modified Wobbe Index, a critical parameter for gas turbines, and H2S content, a critical parameter for pipelines. The results show that the proposed model can optimize combined heat and power cost by determining the most efficient power – steam dispatch, optimal fuel mixture and gas line pressure settings, while still meeting operational constraints

The Solution for Optimal Power Flow (OPF) Method Using Differential Evolution Algorithm

Optimal Power Flow (OPF) is one of techniques used to optimize the cost of power plant production while maintaining the limit of system reliability. In this paper, the application of differential evolution (DE) method is used to solve the OPF problem with variable control such as the power plant output, bus voltage tension, transformer tap, and injection capacitor. The effectiveness of the method was tested using IEEE 30 buses. The result shows that this method is better than generic algorithm (GA), particle swarm optimized (PSO), fuzzy GA, fuzzy PSO, and bat-algorithm. The simulation of the power plant systems of 500 kV Java-Bali with the proposed method can reduce the total cost of generation by 13.04% compared to the operating data PT. PLN (Persero)

Role Analysis of Distributed Generation Towards Transmission Expansion Planning Using MILP

Electricity demand increase as function of population and economic activity growth. To meet the demand growth, one kind of approaches to expand electrical system is to calculate the need of generating unit and the result will be used to determine the needs of transmission line. In this research, a model was developed with focused on transmission line expansion based on Mix Integer Linear Programming method. The objective function was to minimize overall investment cost for transmission and operating cost of all generating units. The developed model was implemented in 6-bus Garver’s test system. Distributed generation implementation impact is also studied in this study in term of network configuration and overall expansion cost. The results show that distributed generation implementation will differ the network configuration and reduce the overall system cost, with overall system cost with and without distributed generation implementation was $106.4 million and$103.18 million respectively

Electricity Demand and Supply Planning Analysis for Sumatera Interconnection System using Integrated Resources Planning Approach

The Sumatra interconnection system, which is the second-largest electricity system in Indonesia, is often experiencing rolling blackouts. That caused by a lack of supply from the power generating system of Sumatra. The Government has planned to develop new power plants through the fast track program (FTP). Until 2015, either power outages and supply shortages are still common. Therefore, an analysis of long-term electricity planning needed to support energy security in Sumatra. The Sumatra electricity system was modelled using integrated resource planning as a framework and the long-range energy alternative planning (LEAP) software as a tool to build and simulate the model. Three groups of scenarios will be compared are the fast track program (FTP) scenario, the biofuel mandatory (BM) scenario and optimization (OPT) scenario. The results show that the implementation of DSM programs through energy conservation scenario would be able to reduce the electricity demand in the future. On the other side, the alternative scenario shows that the electricity deficit could be resolved in 2022, while the optimization scenario shows that energy diversity would resolve the electricity crisis in the Sumatra interconnection system

Optimal Sizing and Placement of Wind-Based Distributed Generation to Minimize Losses Using Flower Pollination Algorithm

Penempatan DG dapat mempengaruhi aliran daya dan tegangan pada bus di sistem distribusi. Oleh karena itu, penempatan DG harus diperhitungkan dan direncanakan secara detail agar dapat bekerja secara optimal. Penempatan DG yang tidak optimal dapat meningkatkan losses pada sistem, sehingga berpengaruh terhadap profil tegangan yang akan menurun. Penempatan dan kapasitas DG yang optimal dapat berpengaruh kepada peningkatan profil tegangan, mengurangi losses, peningkatkan kapasitas distribusi, dan peningkatkan keandalan pada sistem. Beberapa metode optimisasi banyak yang bermunculan mulai dari optimisasi klasikal, pendekatan analitis, sampai yang terbaru yaitu metaheuristik. Salah satu metode optimisasi metaheuristik terbaru adalah Flower Pollination Algorithm (FPA) yang merupakan metode optimisasi yang terinspirasi dari proses penyerbukan bunga. FPA lebih efisien dengan menghasilkan hasil yang lebih baik dan memiliki kecepatan konvergen yang lebih tinggi jika dibandingakan dengan metode metaheuristik lainnya. Pada penelitian ini, FPA digunakan untuk menentukan lokasi dan kapasitas wind-based DG yang optimal dengan single DG dan multi DG untuk meminimalkan rugi-rugi daya pada sistem tes IEEE 33-bus dan meningkatkan profil tegangan. Untuk mengetahui kinerja dari FPA, akan dibandingkan dengan metode optimasi lain. Selain itu, jumlah dan kapasitas wind-based DG yang dipasang pada bus terpilih akan diperhitungkan. Hasil simulasi menunjukkan bahwa metode yang diusulkan telah berhasil dengan baik menentukan lokasi dan kapasitas DG

Performance of MPSO-MPPT on PV-Based DC Microgrid in Partial Shading Conditions

Microgrid is a controllable decentralized group of energy resources and loads with the ability to operate both in grid-connected or island modes. Photovoltaic (PV) is one of the sources that are commonly used in microgrid. PV has a good ability to convert solar irradiation into electrical energy, especially under ideal condition, namely uniform irradiation or non-shading condition. However, PV often has some problems when facing partial shading condition. In this condition, PV does not produce optimal power because it stucks at the local maximum power point (MPP), thus it unables to track the global MPP. For this reason, it is necessary to implement a smart maximum power point tracker (MPPT) that can solve this problem. Furthermore, MPPT will be implemented in pulse width modulation (PWM) to control the buck converter. This study is focused on designing a laboratory scaled microgrid system with PV sources and controlled by modified particle swarm optimization (MPSO)-based MPPT. The 360 Wp PV array used consisted of two strings of three series modules Solarex MSX-60. The performance of the proposed method was compared with perturb and observe (P&O)-based MPPT, which was the commonly used method on MPPT. Furthermore, it was found that P&O and MPSO performed relatively similar accuracy (with difference of 0.04%) in non-shading condition. However, in partial shading condition, MPSO could perform better by producing greater output power so that it delivers better accuracy (98.74% to 99.11%) compared to P&O (57.95% to 71.87%). However, MPSO required a slightly longer time to converge because it had more complicated method and more computational load

Optimizing the Preventive and Corrective Control Scheme in Integrated Variable Renewable Energy Generation

Variable renewable energy integration makes the revolution in modern power system operation and control which lead to perform the preventive and corrective control for maintaining the system continuity againts the voltage security and instability. On the other hand, the power system utility should maintain the economical aspect for its operation, which is hard to be obtained in the system prioring the preventive and corrective scheme. This paper proposes the optimal management between preventive and corrective scheme for achieving the most economical operating cost to solve a stochastic security-constrained optimal power flow for the upcoming time-slot considering voltage stability, line contingency occurence and renewable energy source fluctuation by controlling the generation power, compensator and load shedding scheme while maintaining the computation speed. The main contribution of the proposed method is the active control between preventive and corrective schemes simultaneously for achieving the most economical solution. Scenarios developed in modified IEEE 57-bus test system are used to demonstrate the effectiveness of the proposed method. The simulations show that the proposed method can make a significant contribution for achieving more economical solution while maintaining the computation speed.

Maximum Power Point Tracking using Particle Swarm Optimization Algorithm for Hybrid Wind-Tidal Harvesting System on the South Coast of Java

This paper proposes a hybrid wind-tidal harvesting system (HWTHS). To extract maximum power from the wind and tidal, HWTHS implements particle swarm optimization (PSO) algorithm in maximum power point tracking (MPPT) method. The proposed HWTHS had been tested on the range of possible input appropriate to the characteristics of the southern coast of Java. The presented result shows that by using PSO-based MPPT algorithm, maximum power point can be achieved. Thus the efficiency of HWTHS is 92 %, 94 % in wind section and 91 % in tidal section. By using PSO-based MPPT, HWTHS can respond well to changes in wind and tidal speed, whether it's a change from low speed to a higher speed or change from high speed to lower speed wherein time to reach new steady state is ± 0.1 s. At varied wind and tidal speed, PSO algorithm can maintain Cp of the system in the range of 0.47 - 0.48 so that power can be extracted to the maximum

Studi Optimal Power Flow Sistem Kelistrikan 500 KV Jawa Bali Dengan Metode Algoritma Genetika

Salah satu solusi untuk mengurangi kenaikan harga listrik adalah dengan melakukan optimisasi biaya pada proses produksi energi listrik. Optimal Power Flow (OPF) adalah salah satu metode untuk meminimilisasi biaya bahan bakar pembangkit dengan tetap menjaga batasan keandalan sistem. Pada penelitian ini diaplikasikan metode Genetic Algorithm with tournament selection untuk menyelesaikan masalah OPF. Efektifitas metode diuji pada kasus sistem IEEE 30 bus. Hasil menunjukkan lebih baik dari metode differential evolution dan evolutionary programming. Simulasi pada sistem tenaga Jawa-Bali 500 kV dengan metode yang diusulkan dapat mengurangi biaya pembangkitan sebesar 12,19% dibanding dengan data operasi PLN