Transient stability assessment of hybrid distributed generation using computational intelligence approaches

Includes bibliographical references.Due to increasing integration of new technologies into the grid such as hybrid electric vehicles, distributed generations, power electronic interface circuits, advanced controllers etc., the present power system network is now more complex than in the past. Consequently, the recent rate of blackouts recorded in some parts of the world indicates that the power system is stressed. The real time/online monitoring and prediction of stability limit is needed to prevent future blackouts. In the last decade, Distributed Generators (DGs) among other technologies have received increasing attention. This is because DGs have the capability to meet peak demand, reduce losses, due to proximity to consumers and produce clean energy and thus reduce the production of CO₂. More benefits can be obtained when two or more DGs are combined together to form what is known as Hybrid Distributed Generation (HDG). The challenge with hybrid distributed generation (HDG) powered by intermittent renewable energy sources such as solar PV, wind turbine and small hydro power is that the system is more vulnerable to instabilities compared to single renewable energy source DG. This is because of the intermittent nature of the renewable energy sources and the complex interaction between the DGs and the distribution network. Due to the complexity and the stress level of the present power system network, real time/online monitoring and prediction of stability limits is becoming an essential and important part of present day control centres. Up to now, research on the impact of HDG on the transient stability is very limited. Generally, to perform transient stability assessment, an analytical approach is often used. The analytical approach requires a large volume of data, detailed mathematical equations and the understanding of the dynamics of the system. Due to the unavailability of accurate mathematical equations for most dynamic systems, and given the large volume of data required, the analytical method is inadequate and time consuming. Moreover, it requires long simulation time to assess the stability limits of the system. Therefore, the analytical approach is inadequate to handle real time operation of power system. In order to carry out real time transient stability assessment under an increasing nonlinear and time varying dynamics, fast scalable and dynamic algorithms are required. Transient Stability Assessment Of Hybrid Distributed Generation Using Computational Intelligence Approaches These algorithms must be able to perform advanced monitoring, decision making, forecasting, control and optimization. Computational Intelligence (CI) based algorithm such as neural networks coupled with Wide Area Monitoring System (WAMS) such as Phasor Measurement Unit (PMUs) have been shown to successfully model non-linear dynamics and predict stability limits in real time. To cope with the shortcoming of the analytical approach, a computational intelligence method based on Artificial Neural Networks (ANNs) was developed in this thesis to assess transient stability in real time. Appropriate data related to the hybrid generation (i.e., Solar PV, wind generator, small hydropower) were generated using the analytical approach for the training and testing of the ANN models. In addition, PMUs integrated in Real Time Digital Simulator (RTDS) were used to gather data for the real time training of the ANNs and the prediction of the Critical Clearing Time (CCT)

Feasibility and optimal design of a hybrid power system for rural electrification for a small village

A hybrid renewable energy system is at present accepted globally, as the best option for rural electrification particularly in areas where grid extension is infeasible. However, the need for hybrid design to be optimal in terms of operation and component selection serves as a challenge in obtaining reliable electricity at a minimum cost. In this work, the feasibility of installing a small hydropower into an existing water supply dam and the development of an optimal sizing optimization model for a small village-Itapaji, Nigeria were carried out. The developed hybrid power system (HPS) model consists of solar photovoltaic, small hydropower, battery and diesel generator. The optimal sizing of the system’s components for optimum configuration was carried out using Genetic Algorithm. The hybrid model’s results were compared with hybrid optimization model for electric renewable (HOMER) using correlation coefficient (r) and root mean square error (RMSE) to verify its validity. The results of the simulation obtained from the developed model showed better correlation coefficient (r) of 0.88 and root mean square error (RMSE) of 0.001 when compared to that of HOMER. This will serve as a guide for the power system engineers in the feasibility assessment and optimal design of HPS for rural electrification

MODELING AND SIMULATION OF SMALL HYDRO-SOLAR PV HYBRID GENERATING SYSTEM FOR COMPLEMENTARY POWER SUPPLY IN A METROPOLITAN CITY

In this work, a grid-connected small hydro-solar PV hybrid power system (HPS) was modeled to complement electricity supply in Ado-Ekiti metropolis in Nigeria, and hence, investigated the steady state stability of the distribution networks with and without HPS integration. Consumers’ load audit was carried out through measurement of apparent load at peak periods on each outgoing cable riser from the low voltage circuit of the distribution transformer using clamp-on ammeter which represents loads on respective 11 kV feeders. The solar PV system employed the use of JAP6-72-30/4BB solar PV module and average solar radiation intensity of 4.95 w/m 2 was considered when sizing the solar PV power system. The designed and modeled HPS was integrated into the grid through a hydro inverter and five numbers of parallel-connected 2000 kVA grid-tie solar PV inverters. Simulation analysis of the distribution networks with and without renewable energy integration was carried out using DigSILENT power factory. This work analyzed two scenarios for each of the distribution networks. Simulation results indicated that the networks were stable as evident in the analyses of the renewable grid integration and notable improvement on profile voltage (pu) of all the 11 kV distribution networks were observed

An overview on reliability assessment in power systems using CI approaches

A Computational Intelligence (CI) approach is one of the main trending and potent data dealing out and processing instruments to unravel and resolve difficult and hard reliability crisis and it takes an important position in intelligent reliability analysis and management of data. Nevertheless, just few little broad reviews have recapitulated the current attempts of Computational Intelligence (CI) in reliability assessment in power systems. There are many methods in reliability assessment with the aim to prolong the life cycles of a system, to maximize profit and predict the life cycle of assets or systems within an organization especially in electric power distribution systems. Sustaining an uninterrupted electrical energy supply is a pointer of affluence and nationwide growth. The general background of reliability assessment in power system distribution using computational intelligence, some computational intelligence techniques, reliability engineering, literature reviews, theoretical or conceptual frameworks, methods of reliability assessment and conclusions was discussed. The anticipated and proposed technique has the aptitude to significantly reduce the needed period for reliability investigation in distribution networks because the distribution network needs an algorithm that can evaluate, assess, measure and update the reliability indices and system performance within a short time. It can also manage outages data on assets and on the entire system for quick and rapid decisions making as well as can prevent catastrophic failures. Those listed above would be taken care of if the proposed method is utilized. This overview or review may be deemed as valuable assistance for anybody doing research