Abstract: This paper presents a novel algorithm for modeling
photovoltaic based distributed generators for the purpose of optimal
planning of distribution networks. The proposed algorithm utilizes
sequential Monte Carlo method in order to accurately consider the
stochastic nature of photovoltaic based distributed generators. The
proposed algorithm is implemented in MATLAB environment and
the results obtained are presented and discussed.
Abstract: Due to the continuous increment of the load demand,
identification of weaker buses, improvement of voltage profile and
power losses in the context of the voltage stability problems has
become one of the major concerns for the larger, complex,
interconnected power systems. The objective of this paper is to
review the impact of Flexible AC Transmission System (FACTS)
controller in Wind generators connected electrical network for
maintaining voltage stability. Wind energy could be the growing
renewable energy due to several advantages. The influence of wind
generators on power quality is a significant issue; non uniform power
production causes variations in system voltage and frequency.
Therefore, wind farm requires high reactive power compensation; the
advances in high power semiconducting devices have led to the
development of FACTS. The FACTS devices such as for example
SVC inject reactive power into the system which helps in maintaining
a better voltage profile. The performance is evaluated on an IEEE 14
bus system, two wind generators are connected at low voltage buses
to meet the increased load demand and SVC devices are integrated at
the buses with wind generators to keep voltage stability. Power
flows, nodal voltage magnitudes and angles of the power network are
obtained by iterative solutions using MIPOWER.
Abstract: The problem of optimal planning of multiple sources
of distributed generation (DG) in distribution networks is treated in
this paper using an improved Ant Colony Optimization algorithm
(ACO). This objective of this problem is to determine the DG
optimal size and location that in order to minimize the network real
power losses. Considering the multiple sources of DG, both size and
location are simultaneously optimized in a single run of the proposed
ACO algorithm. The various practical constraints of the problem are
taken into consideration by the problem formulation and the
algorithm implementation. A radial power flow algorithm for
distribution networks is adopted and applied to satisfy these
constraints. To validate the proposed technique and demonstrate its
effectiveness, the well-know 69-bus feeder standard test system is
employed.cm.
Abstract: This paper shows the results obtained in the analysis
of the impact of distributed generation (DG) on distribution losses
and presents a new algorithm to the optimal allocation of distributed
generation resources in distribution networks. The optimization is
based on a Hybrid Genetic Algorithm and Particle Swarm
Optimization (HGAPSO) aiming to optimal DG allocation in
distribution network. Through this algorithm a significant
improvement in the optimization goal is achieved. With a numerical
example the superiority of the proposed algorithm is demonstrated in
comparison with the simple genetic algorithm.
Abstract: Distributed Power generation has gained a lot of
attention in recent times due to constraints associated with
conventional power generation and new advancements in DG
technologies .The need to operate the power system economically
and with optimum levels of reliability has further led to an increase
in interest in Distributed Generation. However it is important to place
Distributed Generator on an optimum location so that the purpose of
loss minimization and voltage regulation is dully served on the
feeder. This paper investigates the impact of DG units installation on
electric losses, reliability and voltage profile of distribution networks.
In this paper, our aim would be to find optimal distributed
generation allocation for loss reduction subjected to constraint of
voltage regulation in distribution network. The system is further
analyzed for increased levels of Reliability. Distributed Generator
offers the additional advantage of increase in reliability levels as
suggested by the improvements in various reliability indices such as
SAIDI, CAIDI and AENS. Comparative studies are performed and
related results are addressed. An analytical technique is used in order
to find the optimal location of Distributed Generator. The suggested
technique is programmed under MATLAB software. The results
clearly indicate that DG can reduce the electrical line loss while
simultaneously improving the reliability of the system.