Probabilistic planning for participation of virtual power plants in the presence of the thermal power plants in energy and reserve markets

Dashtdar, Masoud; Najafi, Mohammad; Esmaeilbeig, Mostafa

doi:10.1007/s12046-020-01335-z

Cited by 20 publications

(15 citation statements)

References 26 publications

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“…2. Prevent the reconnection of the Microgrid to the main grid when there is a different voltage phase between the distribution network and the distributed generation resources in the Microgrid [16,24]. 3.…”

Section: Discussionmentioning

confidence: 99%

Voltage-Frequency Control (v-f) of Islanded Microgrid Based on Battery and MPPT Control

Dashtdar¹,

Dashtdar²

2020

AJECE

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With the development and increasing influence of the use of distributed generation resources, distribution networks have changed from passive networks to active networks. In these new networks, operation on an island will increase both the reliability of the network in the competitive market and the maximum utilization of distributed generation resources. But despite the various benefits, Microgrids with distributed generation resources also have disadvantages. One of the disadvantages is the increasing complexity of control systems, protection systems and operating systems of the global distribution network. In recent research, various methods have been proposed for controlling the Microgrids, especially voltage and frequency control. This paper presents a method for controlling a photovoltaic (PV) system with maximum power point tracking (MPPT) controller and battery storage to provide voltage-frequency (v-f) support in an islanded microgrid. It introduces a new algorithm for MPPT control that offers control strategies, effective coordinated between v-f control in inverter, MPPT control, and battery storage control. Finally, the proposed scheme is implemented on the IEEE 13-bus distribution feeder in islanded mode using MATLAB software, the results of which clearly demonstrate the efficiency of the control methods.

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Section: Discussionmentioning

confidence: 99%

Voltage-Frequency Control (v-f) of Islanded Microgrid Based on Battery and MPPT Control

Dashtdar¹,

Dashtdar²

2020

AJECE

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“…The dynamic model of a wind turbine for small-signal analysis is expressed by Equation (1), and its characteristic function is defined by Equation (2) [37,38].…”

Section: Wind Turbine Generator (Wtg)mentioning

confidence: 99%

“…The PSO algorithm has been used due to its effective and efficient performance in its effective optimisation and speed compared to other algorithms. The objective function for adjusting the MPC controller's parameters weight related to the microgrid's load-frequency control system is shown by Equation (38) and its constraints by Equation (39). Optimisation aims to minimise the absolute magnitude error of microgrid frequency…”

Section: Optimisation Of the Weight Parameter Of The Mpc Controller B...mentioning

confidence: 99%

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Frequency control of the islanded microgrid based on optimised model predictive control by PSO

Dashtdar

Aymen

El‐Bayeh³

et al. 2022

IET Renewable Power Gen

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In this paper, the amount of microgrid frequency deviation in the dynamic state can be reduced by improving the frequency controller and implementing a new method. The proposed controller is designed for a microgrid including renewable resources, and the proposed control strategy is such that the controller coefficients are adjusted and optimised at all times by the model predictive control (MPC). The weight parameters of the MPC controller have been optimised by the particle swarm optimisation (PSO) algorithm. The proposed controller is located in the secondary frequency control loop, and by applying a control signal to the sources, the frequency perturbations following the power changes in the microgrid are reduced. The simulation results show that the proposed controller performs better than the Ziegler-Nichols PI controller (PI-ZN) method, PI-based controllers that rely on fuzzy logic (PI-Fuzzy), the fractional-order proportional-integral-derivative (FOPID) controller that is based on chaos particle swarm optimisation (FOPID-CPSO) algorithm and the PID controllers based on CPSO algorithm (PID-CPSO). It has been able to effectively reduce the frequency fluctuations in terms of amplitude and number of oscillations is also more resistant to the uncertainty of microgrid parameters and shows better performance when changing parameters than other methods.

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“…In References 13-15, by making changes in the way of chromosome coding and mutation pattern, an improved version of the genetic algorithm is presented, and with the help of it, the reconfiguration problem is solved to reduce losses. References 16,17 provides an improved forbidden search algorithm for reconfigurations distribution networks. In the references 18,19 by reconfigurations particle swarm optimization (PSO) algorithm and with the help of graph theory, reconfiguration has been performed to reduce losses and improve reliability.…”

Section: Introductionmentioning

confidence: 99%

Improving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices

Dashtdar

Bajaj

Hosseinimoghadam

et al. 2021

Int Trans Electr Energ Syst

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Distribution networks have problems such as an increase in active losses, overload on distribution substations, voltage drop, decrease in network reliability, increase in load unbalance and unbalance in line current due to variable characteristics in terms of load consumption. In this article, to reduce losses, improve the voltage profile and increase the reliability of the system, the UPQC (Unified Power Quality Controller) optimal placement and reconfiguration method have been used in the distribution network. The two objective functions of losses and the mean voltage deviation are defined by considering the reliability indices. Since the reconfiguration of distribution networks is a large-scale nonlinear hybrid optimization problem with several constraints, the genetic algorithm combines genes including key numbers and UPQC location, UPQC series power size, UPQC shunt power size used to solve the problem. The proposed method is implemented in three steps on IEEE 33-bus and 69-bus standard networks by considering the load model List of Symbols and Abbreviations: agr, agriculture load; com, commercial load; C i , number of loads connected to the ith bus; D, load coefficient; F1, F2, objective functions; fraci,k, the amount of load lost in the ith bus; gen, general load; I EAF_a , main current component of a phase; Ii, current of feeders; Ii, input current to bus i; ind, industrial load; i p , reference current phase component for active power; i q , reference current phase component for reactive power; I ref_a , current reference of the a phase; I s , source current; n, number of buses; P 0i , Q 0i , active and reactive power at a per-unit voltage of bus i; Pi, Q i , active and reactive power passing through branch i; P ref , reference active power; P rk , probability of losing the ith bus; P total,loss , total active network losses; Q a , reactive power of a phase; Q L , reactive power demand; res, residential load; ri, resistance of branch i; S, tnumber of UPQCs installed in the network; V DC_ref , treference DC voltage; V i , voltage of Bus i; V trans_a , effective value of the voltage of the a phase; V s , source voltage; Y ij , admittance matrix; Z s , source impedance; Δδ i , changes in voltage angle of bus, changes in voltage magnitude of bus i; ΔP i , changes in active power of bus i; ΔQ i , changes in reactive power of bus i; γ, τ, active and reactive charge change coefficient; ACS, ant colony search; ACIFi, average fixed number of each customer (1/a) per year; AENS, average energy not supplied per customer; AI

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Probabilistic planning for participation of virtual power plants in the presence of the thermal power plants in energy and reserve markets

Cited by 20 publications

References 26 publications

Voltage-Frequency Control (v-f) of Islanded Microgrid Based on Battery and MPPT Control

Voltage-Frequency Control (v-f) of Islanded Microgrid Based on Battery and MPPT Control

Frequency control of the islanded microgrid based on optimised model predictive control by PSO

Improving voltage profile and reducing power losses based on reconfiguration and optimal placement of UPQC in the network by considering system reliability indices

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