Abstract: In this paper static scheme of under-frequency based load shedding is considered for chemical and petrochemical industries with islanded distribution networks relying heavily on the primary commodity to ensure minimum production loss, plant downtime or critical equipment shutdown. A simplistic methodology is proposed for in-house implementation of this scheme using underfrequency relays and a step by step guide is provided including the techniques to calculate maximum percentage overloads, frequency decay rates, time based frequency response and frequency based time response of the system. Case study of FFL electrical system is utilized, presenting the actual system parameters and employed load shedding settings following the similar series of steps. The arbitrary settings are then verified for worst overload conditions (loss of a generation source in this case) and comprehensive system response is then investigated.
Abstract: The distribution networks are often exposed to harmful
incidents which can halt the electricity supply of the customer. In this
context, we studied a real case of a critical zone of the Tunisian
network which is currently characterized by the dysfunction of its
plan of protection. In this paper, we were interested in the
harmonization of the protection plan settings in order to ensure a
perfect selectivity and a better continuity of service on the whole of
the network.
Abstract: Researches and concerns in power quality gained
significant momentum in the field of power electronics systems over
the last two decades globally. This sudden increase in the number of
concerns over power quality problems is a result of the huge increase
in the use of non-linear loads. In this paper, power quality evaluation
of some distribution networks at Misurata - Libya has been done
using a power quality and energy analyzer (Fluke 437 Series II). The
results of this evaluation are used to minimize the problems of power
quality. The analysis shows the main power quality problems that
exist and the level of awareness of power quality issues with the aim
of generating a start point which can be used as guidelines for
researchers and end users in the field of power systems.
Abstract: Generally, distributed generation units refer to small-scale electric power generators that produce electricity at a site close to the customer or an electric distribution system (in parallel mode). From the customers’ point of view, a potentially lower cost, higher service reliability, high power quality, increased energy efficiency, and energy independence can be the key points of a proper DG unit. Moreover, the use of renewable types of distributed generations such as wind, photovoltaic, geothermal or hydroelectric power can also provide significant environmental benefits. Therefore, it is of crucial importance to study their impacts on the distribution networks. A marked increase in Distributed Generation (DG), associated with medium voltage distribution networks, may be expected. Nowadays, distribution networks are planned for unidirectional power flows that are peculiar to passive systems, and voltage control is carried out exclusively by varying the tap position of the HV/MV transformer. This paper will compare different DG control methods and possible network reconfiguration aimed at assessing their effect on voltage profiles.
Abstract: This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.
Abstract: Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. The distribution feeder reconfiguration (DFR) is one of the most important control schemes in the distribution networks, which can be affected by DGs. This paper presents a new approach to DFR at the distribution networks considering wind turbines. The main objective of the DFR is to minimize the deviation of the bus voltage. Since the DFR is a nonlinear optimization problem, we apply the Adaptive Modified Firefly Optimization (AMFO) approach to solve it. As a result of the conflicting behavior of the single- objective function, a fuzzy based clustering technique is employed to reach the set of optimal solutions called Pareto solutions. The approach is tested on the IEEE 32-bus standard test system.
Abstract: Technological developments in industrial innovations have currently been related to interconnected system assistance and distribution networks. This important in order to enable an electrical load to continue receive power in the event of disconnection of load from the main power grid. This paper represents a method for reliability assessment of interconnected power systems based. The multi-agent system consists of four agents. The first agent was the generator agent to using as connected the generator to the grid depending on the state of the reserve margin and the load demand. The second was a load agent is that located at the load. Meanwhile, the third is so-called "the reverse margin agent" that to limit the reserve margin between 0 - 25% depend on the load and the unit size generator. In the end, calculation reliability Agent can be calculate expected energy not supplied (EENS), loss of load expectation (LOLE) and the effecting of tie line capacity to determine the risk levels Roy Billinton Test System (RBTS) can use to evaluated the reliability indices by using the developed JADE package. The results estimated of the reliability interconnection power systems presented in this paper. The overall reliability of power system can be improved. Thus, the market becomes more concentrated against demand increasing and the generation units were operating in relation to reliability indices.
Abstract: This paper presents the techniques for voltage control in distribution system. It is integrated in the distribution management system. Voltage is an important parameter for the control of electrical power systems. The distribution network operators have the responsibility to regulate the voltage supplied to consumer within statutory limits. Traditionally, the On-Load Tap Changer (OLTC) transformer equipped with automatic voltage control (AVC) relays is the most popular and effective voltage control device. A static synchronous compensator (STATCOM) may be equipped with several controllers to perform multiple control functions. Static Var Compensation (SVC) is regulation slopes and available margins for var dispatch. The voltage control in distribution networks is established as a centralized analytical function in this paper.
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 presents a simple three phase power flow
method for solution of three-phase unbalanced radial distribution
system (RDN) with voltage dependent loads. It solves a simple
algebraic recursive expression of voltage magnitude, and all the data
are stored in vector form. The algorithm uses basic principles of
circuit theory and can be easily understood. Mutual coupling between
the phases has been included in the mathematical model. The
proposed algorithm has been tested with several unbalanced radial
distribution networks and the results are presented in the article. 8-
bus and IEEE 13 bus unbalanced radial distribution system results
are in agreements with the literature and show that the proposed
model is valid and reliable.
Abstract: This paper presents a multi-objective formulation for
optimal siting and sizing of distributed generation (DG) resources in
distribution systems in order to minimize the cost of power losses
and energy not supplied. The implemented technique is based on
particle swarm optimization (PSO) and weight method that employed
to obtain the best compromise between these costs. Simulation
results on 33-bus distribution test system are presented to
demonstrate the effectiveness of the proposed procedure.
Abstract: An effective approach for unbalanced three-phase
distribution power flow solutions is proposed in this paper. The
special topological characteristics of distribution networks have been
fully utilized to make the direct solution possible. Two matrices–the
bus-injection to branch-current matrix and the branch-current to busvoltage
matrix– and a simple matrix multiplication are used to
obtain power flow solutions. Due to the distinctive solution
techniques of the proposed method, the time-consuming LU
decomposition and forward/backward substitution of the Jacobian
matrix or admittance matrix required in the traditional power flow
methods are no longer necessary. Therefore, the proposed method is
robust and time-efficient. Test results demonstrate the validity of the
proposed method. The proposed method shows great potential to be
used in distribution automation applications.
Abstract: In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.
Abstract: In this paper, the problem of finding the optimal
topological configuration of a deregulated distribution network is
considered. The new features of this paper are proposing a multiobjective
function and its application on deregulated distribution
networks for finding the optimal configuration. The multi-objective
function will be defined for minimizing total Energy Supply Costs
(ESC) and energy losses subject to load flow constraints. The
optimal configuration will be obtained by using Binary Genetic
Algorithm (BGA).The proposed method has been tested to analyze a
sample and a practical distribution networks.
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: A multiphase harmonic load flow algorithm is developed based on backward/forward sweep to examine the effects of various factors on the neutral to earth voltage (NEV), including unsymmetrical system configuration, load unbalance and harmonic injection. The proposed algorithm composes fundamental frequency and harmonic frequencies power flows. The algorithm and the associated models are tested on IEEE 13 bus system. The magnitude of NEV is investigated under various conditions of the number of grounding rods per feeder lengths, the grounding rods resistance and the grounding resistance of the in feeding source. Additionally, the harmonic injection of nonlinear loads has been considered and its influences on NEV under different conditions are shown.
Abstract: This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.
Abstract: This paper proposes a new methodology for the
optimal allocation and sizing of Embedded Generation (EG)
employing Real Coded Genetic Algorithm (RCGA) to minimize the
total power losses and to improve voltage profiles in the radial
distribution networks. RCGA is a method that uses continuous
floating numbers as representation which is different from
conventional binary numbers. The RCGA is used as solution tool,
which can determine the optimal location and size of EG in radial
system simultaneously. This method is developed in MATLAB. The
effect of EG units- installation and their sizing to the distribution
networks are demonstrated using 24 bus system.
Abstract: This paper reports a new and accurate method for load-flow solution of radial distribution networks with minimum data preparation. The node and branch numbering need not to be sequential like other available methods. The proposed method does not need sending-node, receiving-node and branch numbers if these are sequential. The proposed method uses the simple equation to compute the voltage magnitude and has the capability to handle composite load modelling. The proposed method uses the set of nodes of feeder, lateral(s) and sub lateral(s). The effectiveness of the proposed method is compared with other methods using two examples. The detailed load-flow results for different kind of load-modellings are also presented.
Abstract: This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.