M. Keshavarz, A. Doroudi, M. H. Kazemi, N. Mahdian Dehkordi,
Volume 17, Issue 2 (6-2021)
Abstract
The droop control strategy is the most common approach for microgrids control but its application is limited due to frequency deviation following a load change. Complementary control strategy has then been proposed to solve the problem using a communication network. However, under this strategy, regular loads profile produces a continuous change of output power of all distributed generators (DGs) and their generation changes seem to be permanent. This also causes continuous data exchange between DGs through communication links. This paper shows the possibility of adapting the droop/isochronous control methodology used by synchronous generators in conventional power systems to provide frequency control and power balance to inverter-based distributed generation power systems. To this end, this paper presents a centralized complementary control framework for the management of power-sharing and sustaining frequency in its nominal range in microgrids using a hybrid droop-isochronous control system. The proposed method is event-triggered based and communication between DGs is only needed when the output power of the isochronous generator exceeds its power limits. The method provides an efficient and reliable control system and has a simple concept, easy, and cost-effective implementation. Simulations in MATLAB/SimPower are performed on a typical microgrid under various conditions to evaluate the performance of the proposed controller.
T. Agheb, I. Ahmadi, A. Zakariazadeh,
Volume 17, Issue 3 (9-2021)
Abstract
Optimal placement and sizing of distributed renewable energy resources (DER) in distribution networks can remarkably influence voltage profile improvement, amending of congestions, increasing the reliability and emission reduction. However, there is a challenge with renewable resources due to the intermittent nature of their output power. This paper presents a new viewpoint at the uncertainties associated with output powers of wind turbines and load demands by considering the correlation between them. In the proposed method, considering the simultaneous occurrence of real load demands and wind generation data, they are clustered by use of the k-means method. At first, the wind generation data are clustered in some levels, and then the associated load data of each generation level are clustered in several levels. The number of load levels in each generation level may differ from each other. By doing so the unrealistic generation-load scenarios are omitted from the process of wind turbine sizing and placement. Then, the optimum sizing and placement of distributed generation units aiming at loss reduction are carried out using the obtained generation-load scenarios. Integer-based Particle Swarm Optimization (IPSO) is used to solve the problem. The simulation result, which is carried out using MATLAB 2016 software, shows that the proposed approach causes to reduce annual energy losses more than the one in other methods. Moreover, the computational burden of the problem is decreased due to ignore some unrealistic scenarios of wind and load combinations.
R. Kalyan, M. Venkatakirthiga, P. Raja,
Volume 19, Issue 2 (6-2023)
Abstract
The Direct power control and vector control of DFIG has known advantages, but certain disadvantages like steady state performance and transient performance of the system still persist. In order to overcome these, a novel technique based on Improved Sensorless Rotor Position Computational Algorithm with Integrated Direct Power and Vector Control (IDPVC) for S-VSC interfaced DFIG is proposed in this work. The advantages of both vector control and direct power control techniques are addressed in this method. This proposed IDPVC control minimizes the real and reactive power ripples at steady state and total harmonic distortion in stator current. In the proposed control, data acquired from sensorless rotor position computation makes the system more stable and avoids the sensor maintenance and feedback errors. The proposed system is tested for a 3.73 kW DFIG and compared with a benchmark DPC control of single VSC based DFIG. The results show the effectiveness of the approach under various wind speed conditions and found to be satisfactory.
A. O. Issa, A. I. Abdullateef, A. Sulaiman, A. Y. Issa, M. J. E. Salami, M. A. Onasanya ,
Volume 19, Issue 3 (9-2023)
Abstract
Grid-connected photovoltaic (PV) system is often needed whenever utilities fail to provide consumers with a reliable, sufficient and quality power supply. It provides more effective utilization of power, however, there are technical requirements to ensure the safety of the PV installation and utility grid reliability. In solar systems there is often excessive use of components, resulting in high installation costs. Consequently, appropriate measures must be taken to develop a cost-effective grid-connected PV system. An optimally sized PV system incorporated into an existing unreliable grid-connected commercial load for Mount Olive food processing is presented in this paper. The study focused on providing a reliable electricity supply which is cost-effective and environment-friendly. The techno-economic analysis of grid-connected PV/Diesel/Battery Storage systems was carried out using HOMER Pro software. Results showed that Grid/PV/BSS are technically, economically and environmentally feasible with the cost of energy at 0.136$/kWh and net present cost at $254,469. Also, the excess electricity produced by this combination is 13,264kWh/year, which generates income for the company by selling excess generated energy back to the grid if net metering were to be implemented. Furthermore, the CO2 emissions for these combinations decreased to 10,081.6 kg/year as compared to the existing systems (Grid/Diesel Generator) with emissions of 124,480 kg/year. This is an additional advantage in that it improves the greenhouse effect. A sensitivity analysis was carried out on the variation of load change, grid power price and schedule outages for the optimal system.
Hamid Karimi,
Volume 20, Issue 1 (3-2024)
Abstract
This paper proposes a stochastic optimization problem for local integrated hydrogen-power energy systems. In the proposed model, the integrated system tries to reduce the day-ahead operation costs using dispatchable resources, renewable energy resources, battery energy storage systems, demand response programs, and energy trading with the upstream network. Also, the integrated system is able to transact electricity with the upstream network to get more benefits. When the generation of renewable resources is high, the integrated system can convert the surplus electricity to hydrogen by power-to-gas units. The generated hydrogen can be sold to different industries or stored in the hydrogen tank storage. During peak hours, the stored hydrogen can be imported into the gas-to-power unit to generate the required electricity. The sector coupling between electricity and hydrogen provides more flexibility for integrated systems and is an effective solution to control the uncertainty of renewable energy resources in order to increase the power and energy flexibilities. The simulation results show that the proposed sector coupling provides the opportunity for electricity and hydrogen trading for integrated system. The benefit of the integrated system by electricity and hydrogen trading with the upstream network and different industries are $ 88.39, and $ 6846, respectively.
Majid Najjarpour, Behrouz Tousi, Shahaboddin Yazdandoust Moghanlou,
Volume 20, Issue 1 (3-2024)
Abstract
In recent decades, because of the rapid population growth of the world, considerable changes in climate, the reduction of fossil fuel sources to consume the traditional power plants and their high depreciation, and the increase in fuel prices. Due to the increased penetration of DG units which have a random nature into the power system, the ordinary equations of power flow must be changed. For the power system to operate in a stable condition estimating future demand and calculating the important and operational indexes such as losses of the power system is an important duty that must be done precisely and rapidly. In this paper, the Improved Taguchi method and phasor measurement unit are used to model the uncertainties of DGs and estimate the error of voltage, respectively. The results show that the magnitude error and the angle error of voltage are decreased using PMU. The applied optimal power flow and state estimations are analyzed and verified using standard IEEE 30-bus and 14-bus test power systems by MATLAB, and MINITAB softwares. The Made Strides Taguchi strategy appears to have modeled the DG units precisely and successfully, and using the PMU, the mistake of the point and greatness estimation is exceptionally moot. The values that were evaluated are very close to the values that were done by the Newton-Raphson stack stream.
Nguyen Cong Chinh,
Volume 20, Issue 3 (9-2024)
Abstract
This paper presents an intelligent meta-heuristic algorithm, named improved equilibrium optimizer (IEO), for addressing the optimization problem of multi-objective simultaneous integration of distributed generators at unity and optimal power factor in a distribution system. The main objective of this research is to consider the multi-objective function for minimizing total power loss, improving voltage deviation, and reducing integrated system operating costs with strict technical constraints. An improved equilibrium optimizer is an enhanced version of the equilibrium optimizer that can provide better performance, stability, and convergence characteristics than the original algorithm. For evaluating the effectiveness of the suggested method, the IEEE 69-bus radial distribution system is chosen as a test system, and simulation results from this method are also compared fairly with many previously existing methods for the same targets and constraints. Thanks to its ability to intelligently expand the search space and avoid local traps, the suggested method has become a robust stochastic optimization method in tackling complex optimization tasks.
