Reliability improvement and loss reduction in radial distribution system with network reconfiguration algorithms using loss sensitivity factor

<p>Studies on load flow in electrical distribution system have always been an area of interest for research from the previous few years. Various approaches and techniques are brought into light for load flow studies within the system and simulation tools are being used to work out on varied characteristics of system. This study concentrates on these approaches and the improvements made to the already existing techniques considering time and the algorithms complexity. Also, the paper explains the network reconfiguration (NR) techniques considered in reconfiguring radial distribution network (RDN) to reduce power losses in distribution system and delivers an approach to how various network reconfiguration techniques support loss reduction and improvement of reliability in the electrical distribution network.</p>

Active Exploration by Chance-Constrained Optimization for Voltage Regulation with Reinforcement Learning

Voltage regulation in distribution networks encounters a challenge of handling uncertainties caused by the high penetration of photovoltaics (PV). This research proposes an active exploration (AE) method based on reinforcement learning (RL) to respond to the uncertainties by regulating the voltage of a distribution network with battery energy storage systems (BESS). The proposed method integrates engineering knowledge to accelerate the training process of RL. The engineering knowledge is the chance-constrained optimization. We formulate the problem in a chance-constrained optimization with a linear load flow approximation. The optimization results are used to guide the action selection of the exploration for improving training efficiency and reducing the conserveness characteristic. The comparison of methods focuses on how BESSs are used, training efficiency, and robustness under varying uncertainties and BESS sizes. We implement the proposed algorithm, a chance-constrained optimization, and a traditional Q-learning in the IEEE 13 Node Test Feeder. Our evaluation shows that the proposed AE method has a better response to the training efficiency compared to traditional Q-learning. Meanwhile, the proposed method has advantages in BESS usage in conserveness compared to the chance-constrained optimization.

Hybrid Bare Bones Fireworks Algorithm for Load Flow Analysis of Islanded Microgrids

In this chapter, a hybrid bare bones fireworks algorithm (HBBFWA) is proposed and its application in solving the load flow problem of islanded microgrid is demonstrated. The hybridization is carried out by updating the positions of generated sparks with the help of grasshopper optimization algorithm (GOA) mimicking the swarming behavior of grasshoppers. The purpose of incorporating GOA with bare bones fireworks algorithm (BBFWA) is to enhance the global searching capability of conventional BBFWA for complex optimization problems. The proposed HBBFWA is applied to perform the load flow analysis of a modified IEEE 37-Bus system. The performance of the proposed HBBFWA is compared against the performance of BBFWA in terms of computational time, convergence speed, and number of iterations required for convergence of the load flow problem. Moreover, standard statistical analysis test such as the independent sample t-test is conducted to identify statistically significant differences between the two algorithms.

Enrichment of Distribution System Stability Through Artificial Bee Colony Algorithm and Artificial Neural Network

In this chapter, an amalgamation of artificial bee colony (ABC) algorithm and artificial neural network (ANN) approach is recommended for optimizing the location and capacity of distribution generations (DGs) in distribution network. The best doable place in the network has been approximated using ABC algorithm by means of the voltage deviation, power loss, and real power deviation of load buses and the DG capacity is approximated by using ANN. In this, single DG and two DGs have been considered for calculation of doable place in the network and capacity of the DGs to progress the voltage stability and reduce the power loss of the system. The power flow of the system is analyzed using iterative method (The Newton-Raphson load flow study) from which the bus voltages, active power, reactive power, power loss, and voltage deviations of the system have been achieved. The proposed method is tested in MATLAB, and the results are compared with particle swarm optimization (PSO) algorithm, ANN, and hybrid PSO and ANN methods for effectiveness of the proposed system.

Voltage Profile Enhancing Using HVDC for 132KV Power System: Kurdistan Case Study

Nowadays power systems are huge networks that consist of electrical energy sources, static and lumped load components, connected over long distances by A.C. transmission lines. Voltage improvement is an important aspect of the power system. If the issue is not dealt with properly, may lead to voltage collapse. In this paper, HVDC links/bipolar connections were inserted in a power system in order to improve the voltage profile. The load flow was simulated by Electrical Transient Analyzer Program (ETAP.16) program in which Newton- Raphson method is used. The load flow simulation studies show a significant enhancement of the power system performance after applying HVDC links on Kurdistan power systems. The bus voltages are significantly increased after connecting High Voltage Direct Current.

Load Flow Analysis After the Entry of Renewable Power Plants in the Sulselrabar System

Power flow analysis in an electric power system is an analysis that reveals the performance of an electric power system and the flow of power (active and reactive) for certain conditions when the system is working. The analysis was carried out using the ETAP 16.00 software, the method used was the newton rapshon by taking a case study of normal conditions. From the results of the study, it can be seen that the power flow that occurs in each channel of the 150 kV system in the South Sulawesi system. The amount of active power (MW) that occurs during normal conditions based on the simulation is 1730.87 MW, where the active power is the largest, which is 171 MW from BUS15_TLASA to BUS13_SGMNSA. For the voltage data, there is a slight comparison of the voltage during the simulation compared to the PLN data.

Constant Voltage Model of DFIG-Based Variable Speed Wind Turbine for Load Flow Analysis

At present, the penetration of wind-driven electric generators or wind power plants (WPPs) in electric power systems is getting more and more extensive. To evaluate the steady state performances of such power systems, developing a valid WPP model is therefore necessary. This paper proposes a new method in modeling the most popular type of WPP, i.e., DFIG (doubly fed induction generator)-based WPP, to be used in power system steady state load flow analysis. The proposed model is simple and derived based on the formulas that calculate turbine mechanical power and DFIG power. The main contribution of the paper is that, in contrast to the previous models where the DFIG power factor has been assumed to be constant at unity, the constant voltage model proposed in this paper allows the power factor to vary in order to keep the voltage at the desired value. Another important contribution is that the proposed model can be implemented in both sub-synchronous and super-synchronous conditions (it is to be noted that most of the previous models use two different mathematical models to represent the conditions). The case study is also presented in the present work, and the results of the study confirm the validity of the proposed DFIG model.

Modeling of SCIG-Based Variable Speed Wind Turbine in Power Factor Control Mode for Load Flow Analysis

As they are more efficient in extracting wind energy, variable speed wind power plants (WPPs) are currently replacing the fixed speed WPPs. One possible way to achieve a variable speed WPP is by using a squirrel cage induction generator (SCIG) with full-scale power electronic converter (PEC). In fact, as its cost is relatively lower, the application of SCIG-based variable speed WPP is gaining popularity nowadays. To be able to perform proper analyses (including the load flow analysis) of an electric power system, valid and accurate modeling of the system components is very important. This paper discusses the steady state model of SCIG-based variable speed WPP in power factor control mode for a load flow analysis of an electric power distribution system. The model was developed based on formulas that calculate the turbine mechanical power input and WPP electrical power output. Integration of the proposed model in load flow analysis is also discussed and presented in this paper.

Simulation Methods for the Analysis of Complex Systems

Everyday systems like communication, transportation, energy and industrial systems are an indispensable part of our daily lives. Several methods have been developed for their reliability assessment—while analytical methods are computationally more efficient and often yield exact solutions, they are unable to account for the structural and functional complexities of these systems. These complexities often require the analyst to make unrealistic assumptions, sometimes at the expense of accuracy. Simulation-based methods, on the other hand, can account for these realistic operational attributes but are computationally intensive and usually system-specific. This chapter introduces two novel simulation methods: load flow simulation and survival signature simulation which together address the limitations of the existing analytical and simulation methods for the reliability analysis of large systems.