Integration Of Distributed Generation Units Research Articles

Impacts of Distributed Generation on Power System Protection

Distributed generation (DG) offers huge benefits to the power system network to cater to the rapidly growing demand for electric power. The integration of DG units into existing power networks is beneficial to both utilities and consumers. However, the installation of DG units in distribution networks might impose some operational, technical, and economic impacts. Increased short-circuit level and changes in load flow direction are examples of the technical issues arising from the high penetration of DG. Such issues will affect the existing protection system, mainly overcurrent relays. Thus, to ensure reliable and selective operation of protection relays, the impacts of DG should be considered. This paper discusses the impacts of DG on the protection systems by identifying various protection problems. The paper is complemented by a simulation case study on the impacts of DG on fault levels, protection coordination, and distance relays. The simulated system was modeled using DIgSILENT PowerFactory® software.

Sizing and Siting of Types I–IV DG Units using Chaos-assisted Gravitational Search Algorithm

Distributed generation (DG) units are generally categorized in four types depending on their deployment for generation and consumption of active and reactive power. Integration of DG units into an electrical distribution system results in several planning and operational challenges. This work proposes a methodology based on a chaos-assisted gravitational search algorithm for optimal sizing and simultaneous placement of DG units of multiple types. The objective of optimization is to minimize the power loss and voltage deviation while abiding by the constraints of the power system. The proposed methodology is tested on three standard test systems (12-, 33-, 69-bus test system) and a practical feeder of Lahore Electric Supply Company (LESCO), Pakistan. The results confirm that optimal sizing and placement of multi-DG units results in better system performance as compared to placement of any one type of DG. Further, the proposed algorithm for optimal sizing and location of DG units outperforms when compared with an analytical and a heuristic search algorithm.

A Review on Optimal Allocation and Sizing Techniques for DG in Distribution Systems

Distributed Generation (DG) offers the reliable and economic source of electricity to consumers. These are connected directly to the distribution system at consumer load points. Integration of DG units into an existing system has significantly high importance due to its innumerable advantages. However, Optimal DG (ODG) allocation and sizing is always a challenging task for utilities as well as consumers. The major objective of ODG allocation and sizing is to improve system overall efficiency with minimum power loss, maximum system security, voltage stability, and reliability. Analytical techniques are performing well for small and simple systems, not suitable for a system with large and complex networks. However, various meta-heuristic techniques are performing better in terms of accuracy and convergence for extensively large and complex networks. A hybrid optimization is a combination of two or more optimization techniques. This technique offers efficient and reliable global optimum solutions for complex multi-objective problems. In this context, a comprehensive literature review of DG fundamentals and the different technical approaches for DG integration into the distribution system are analyzed here. Furthermore, an attempt has been made for comparison of analytical, classical (non-heuristic), meta-heuristic and hybrid optimization techniques with respect to objective function, test system, advantages, and disadvantages. This present study will give in-depth knowledge and acts as a forthright reference for imminent investigators and investors for ODG allocation and sizing in a distribution system.Â

Integration of renewable distributed generators into the distribution system: a review

Recent advances in renewable energy technologies and changes in the electric utility infrastructures have increased the interest of the power utilities in utilisation of distributed generation (DG) resources to generate electricity. The recent trends in the development and utilisation of DG resources for power generation application are subject to the deregulation of the electric power sector and technical constraints to extend distribution and transmission networks to some areas. The electric power system planners, regulators and the policy makers have derived many benefits from integration of DG units into the distribution networks. These benefits depend on the characteristics of DG units such as photovoltaic (PV), wind system and reciprocating engines, characteristics of the loads, local renewable resources and network configuration. This study comprehensively reviews various research works on the technical, environmental and economic benefits of renewable DG integration such as line-loss reduction, reliability improvement, economic benefits and environmental pollution optimisation. These benefits can be optimised if all the renewable DG units are optimally sized, located and configured. This study also reviews the current status of renewable DG technologies based on different characteristics and the operational issues of integration of renewable DG into the electric power systems.

Efficient immune‐GA method for DNOs in sizing and placement of distributed generation units

AbstractThis paper proposes a hybrid heuristic optimization method based on genetic algorithm and immune systems to maximize the benefits of Distribution Network Operators (DNOs) accrued due to sizing and placement of Distributed Generation (DG) units in distribution networks. The effects of DG units in reducing the reinforcement costs and active power losses of distribution network have been investigated. In the presented method, the integration of DG units in distribution network is done considering both technical and economical aspects. The strength of the proposed method is evaluated by applying it on a small and a realistic large scale distribution network and the results are compared with analytical classic and other heuristic methods and discussed. Copyright © 2010 John Wiley & Sons, Ltd.