Risk-Based Capacitor Placement in Distribution Networks

In this paper, the problem of sizing and placement of constant and switching capacitors in electrical distribution systems is modelled considering the load uncertainty. This model is formu- lated as a multicriteria mathematical problem. The risk of voltage violation is calculated, and the stability index is modelled using fuzzy logic and fuzzy equations. The instability risk is introduced as the deviation of our fuzzy-based stability index with respect to the stability margin. The capacitor placement objectives in our paper include: (i) minimizing investment and installation costs as well as loss cost; (ii) reducing the risk of voltage violation; and (iii) reducing the instability risk. The proposed mathematical model is solved using a multi-objective version of a genetic algorithm. The model is implemented on a distribution network, and the results of the experiment are discussed. The impacts of constant and switching capacitors are assessed separately and concurrently. Moreo- ver, the impact of uncertainty on the multi-objectives is determined based on a sensitivity analysis. It is demonstrated that the more the uncertainty is, the higher the system cost, the voltage risk and the instability risk are

Capacitor Placement in Distorted Distribution Network Subject to Wind and Load Uncertainty

Utilizing capacitor banks is very conventional in distribution network in order for local compensation of reactive power. This will be more important considering uncertainties including wind generation and loads uncertainty. Harmonics and non-linear loads are other challenges in power system which complicates the capacitor placement problem. Thus, uncertainty and network harmonics have been considered in this paper, simultaneously. Capacitor placement has been proposed as a probabilistic harmonic problem with different objectives and technical constraints in the capacitor placement problem. Minimizing power and energy loss and capacitor prices are considered as objectives. Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms have been used to solve the optimization problem. Loads are subjected to uncertainty with normal probabilistic distribution function (PDF). Auto Regressive and Moving Average (ARMA) time series and two point estimate method have also been utilized to simulate the wind speed and to perform the probabilistic load flow, respectively. Finally, the proposed method has been implemented on standard distorted test cases in different scenarios. Monte Carlo Simulation (MCS) has also been used to verify the probabilistic harmonic power flow. Simulation results demonstrate the efficiency of the proposed method

FAULT INDICATORS EFFECTS ON DISTRIBUTION RELIABILITY INDICES

SUMMAR

Active distribution networks planning with high penetration of wind power

YesIn this paper, a stochastic method for active distribution networks planning within a distribution market environment considering multi-configuration of wind turbines is proposed. Multi-configuration multi-scenario market-based optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand and different operational status of wind turbines (multiple-wind turbine configurations). Scenario-based approach is used to model the abovementioned uncertainties. The method evaluates the impact of multiple-wind turbine configurations and active network management schemes on the amount of wind power that can be injected into the grid, the distribution locational marginal prices throughout the network and on the social welfare. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. It was shown that multi-wind turbine configurations under active network management schemes, including coordinated voltage control and adaptive power factor control, can increase the amount of wind power that can be injected into the grid; therefore, the distribution locational marginal prices reduce throughout the network significantly

Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model

One of the essential aspects of power system planning is generation expansion planning (GEP). The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants. This paper proposes a method based on a genetic algorithm (GA) for GEP in the presence of wind power plants. Since it is desirable to integrate the maximum possible wind power production in GEP, the constraints for incorporating different levels of wind energy in power generation are investigated comprehensively. This will allow the maximum reasonable amount of wind penetration in the network to be obtained. Besides, due to the existence of different wind regimes, the penetration of strong and weak wind on GEP is assessed. The results show that the maximum utilization of wind power generation capacity could increase the exploitation of more robust wind regimes. Considering the growth of the wind farm industry and the cost reduction for building wind power plants, the sensitivity of GEP to the variations of this cost is investigated. The results further indicate that for a 10% reduction in the initial investment cost of wind power plants, the proposed model estimates that the overall cost will be minimized

Environmental/Economic Operation Management of a Renewable Microgrid with Wind/PV/FC/MT and Battery Energy Storage Based on MSFLA

Microgrids (MGs) are local grids consisting of Distributed generators, energy storage systems and dispersed loads which may operate in both grid-connected and islanded modes. This paper aims to optimize the operation of a typical grid-connected MG which comprises a variety of DGs and storage devices in order to minimize both total operation cost and environmental impacts resulted from supplying local demands. Furthermore we will try to achieve an intelligent schedule to charge and discharge storage devices that provides the opportunity to benefit from market price fluctuations. The presented optimization framework is based on multiobjective modified shuffled frog leaping algorithm (MSFLA). To solve environmental/economic operation management (EEOM) problem using MSFLA, a new frog leaping rule, associated with a new strategy for frog distribution into memeplexes, is proposed to improve the local exploration and performance of the ordinary shuffled frog leaping algorithm. The proposed method is examined and tested on a grid-connected MG including fuel cell, wind turbine, photovoltaic, gas-fired microturbine, and battery energy storage devices. The simulation results for three scenarios involving the economic operation management of MG, environmental operation management of MG, and environmental/economic operation management of MG are presented separately. The obtained results compared with results of well-known methods reported in the literature and prove the efficiency of the proposed approach to solve the both single objective and multiobjective operation management of the MG

WIND FARM EFFECTS ON TOTAL TRANSFER CAPABILITY

Available transfer capability (ATC) is a key index to manage future transactions between areas in the open access environment. ATC is a probability index because of the uncertainties related to power system operation. On the other hand, the utilization of wind farm with the stochastic nature as an alternative for electric power generation adds a new probabilistic component to the system and emphasizes employing probabilistic methods to calculate transfer capability. Besides the fluctuating nature of wind farms, other factors such as connection bus of wind farm, its capacity, and wind speed regime can create a considerable impact on transfer capability. This paper uses the Monte Carlo simulation to produce system states and optimal power flow to calculate transfer capability considering operating limits of generating units, voltage and thermal limits. Case studies with the IEEE reliability test system (RTS) discuss about the impact of the mentioned factors on transfer capability

A novel strategy for optimal placement of locally controlled voltage regulators in traditional distribution systems

In this paper, an approach for placement of voltage regulators (VRs) in traditional distribution systems by considering a local controller model is presented. The main aims of this paper are controlling the voltage level in its permitted range and decreasing the costs imposed to the distribution system companies, such as costs that stem from power losses, VRsâ\u80\u99 investment and maintenance. Genetic algorithm (GA) has been used as a tool to determine the number, location and rated power of VRs. Since in traditional distribution systems, tap position determination of VRs is achieved by local controllers, local controller model is established to determine tap operations. A 70-bus distribution system is considered to prove the value of the presented approach. Effectiveness of the proposed approach and ineffectiveness and infeasibility of conventional approaches are presented in numerical studies. The presented approach allowed to eliminate voltage violation in all load conditions and a reduction of power losses of about 6% for the maximum load level