Using an intelligent method for microgrid generation and operation planning while considering load uncertainty

The integration of distributed generation (DG), energy storage systems (ESS), and controllable loads near the place of consumption has led to the creation of microgrids. However, the uncertain nature of renewable energy sources (wind and photovoltaic), market prices, and loads have caused issues with guaranteeing power quality and balancing generation and consumption. To solve these issues, microgrids should be managed with an energy management system (EMS), which facilitates the minimization of operating (performance) costs, the emission of pollutants, and peak loads while meeting technical constraints. To this effect, this research attempts to adjust parameters by defining indicators related to the best possible conditions of the microgrid. Generation planning, the storage of generated power, and exchange with the main grid are carried out by defining a dual-purpose objective function, which includes reducing the operating cost of power generation, as well as the pollution caused by it in the microgrid, by means of the SALP optimization algorithm. Moreover, in order to make the process more realistic and practical for microgrid planning, some parameters are considered as indefinite values, as they do not have exact values in their natural state. The results show the effect of using the introduced intelligent optimization method on reducing the objective function value (cost and pollution)

Optimized Two-Level Control of Islanded Microgrids to Reduce Fluctuations

The main problem in the operation of micro-grids is controlling the voltage and frequency. The inertia of the whole grid is low, so the operation of the system is interrupted by sudden changes in load or incidence in the absence of a proper control system. In order to solve this issue, various control structures have been proposed. In this paper, an optimal distributed control strategy for coordinating multiple distributed generation instances is presented in an islanded microgrid. A secondary frequency control method is implemented in order to eliminate voltage deviation and reduce the small signal error. In this layer, an optimized PID controller is used. PID controller optimization is carried out via the Honey Badger Algorithm, and results are obtained using the MATLAB software. According to the results, inadequate adjustment of a secondary loop leads to poor and unacceptable outcomes, and the necessary power quality is not achieved. However, by using the proposed method, a proper performance of the microgrid in the face of disturbances is achieved

Electricity retail market and accountability-based strategic bidding model with short-term energy storage considering the uncertainty of consumer demand response

Electricity retailers participate in electricity markets as intermediaries between wholesale and retail markets. They acquire energy on the wholesale side by participating in next-day markets and the pool of power. On the retail side, they make contracts with consumers in order to meet their energy demand at a fixed price for a set period of time –generally a year. To maximize profit in planning, a retailer must choose the best strategy, which should be able to reduce the cost of purchasing energy in the wholesale market while simultaneously determining the best selling price for consumers. Customers may choose a different retailer if the selling price is too high, and the retailer may take a loss if the price is too low. One of the issues that complicate retailers’ decision is the uncertain demand response parameters that affect profit. This paper contributes with a strategic bidding model for planning with short-term energy storage while considering the uncertainty of consumer demand response and load response programs simultaneously. GAMS and MATLAB are implemented in this research to analyze the data and review the results, which indicate that an increase in profit is expected to be greater than when the retailer uses only a load response program or a short-term energy storage system. As uncertainty grows, so does local price sensitivity, and, as a result, so does the predicted rate of profit. Profits from participatory reservation, energy, and regulation markets increase in the robust model, while profits from the common participatory market decrease, i.e., according to this study, which looked at both probabilistic and robust models of retail market participation. When a robust model is used, the overall profit is higher than that obtained from a probabilistic model. © 2022 The Author

Optimal load frequency control of island microgrids via a pid controller in the presence of wind turbine and pv

This article studied the load frequency control (LFC) of a multi-source microgrid with the presence of renewable energy sources. To maintain a sustainable power supply, the frequency of the system must be kept constant. A Proportional–Integral–Derivative (PID) controller is presented as a secondary controller to control the frequency of the microgrid in island mode, and the integral of squared time multiplied by error squared (ISTES) is used as a performance index. The use of the Craziness-Based Particle Swarm Optimization (CRPSO), which is an improved version of Particle Swarm Optimization (PSO), improves the convergence speed in optimizing the nonlinear problem of load and frequency controller design. The test microgrid is composed of the load and distributed generation units such as diesel generators, photovoltaics and wind turbines. The proposed controller provided the desired response to adjusting the microgrid frequency, achieving the final response after a short time and making it more stable and less oscillatory compared with the conventional system.https://www.mdpi.com/journal/sustainabilityMechanical and Aeronautical Engineerin

Modified Topology and Modulation Technique for Z-Source Neutral-Point Clamped Inverter

The impedance network makes it possible to increase and decrease the voltage, which is not available in normal inverters (voltage and current sources).This paper presents a modified topology and modulation technique for a three-phase Modified Z-Source Neutral-Point Clamped (MZS-NPC) inverter. A modulation scheme for the proposed topology is designed based on maximum gain control method to achieve the maximum voltage gain by simple implementation and balancing the neutral point voltage of the dc link. In order to supply the desired voltage to the critical load in an islanded micro-grid, a closed-loop ac voltage controller is realized in fuel cell or photovoltaic applications based on the proposed inverter. The ability to reinforce and validity of topology operations and modulation techniques has been demonstrated by simulation. It should be noted that the simulations are implemented in MATLAB / Simulink software

A Sustainable Energy Distribution Configuration for Microgrids Integrated to the National Grid Using Back-to-Back Converters in a Renewable Power System

A desire to produce power in microgrids has grown as the demand for electricity has expanded and the cost of installing modern transmission lines over long distances has become infeasible. As such, microgrids pose DC/AC harmonic distortion losses to the voltage supply that eventually fluctuate the output voltage. The key takeaways that this study presents are: (a) a configuration for microgrids integrated to the national grid using back-to-back converters in a renewable power system is achieved; (b) different scenarios of various schemes of sustainability of the power management in microgrids are analyzed; and (c) the reliable and stable network output power distribution is achieved. In this, the proposed control configuration provides space for construction and stability of the power system with sustainability of the power management. The results show that this current configuration works and stabilizes the network in the shortest time possible, and that the DC connection voltage is regulated and maintains reliable network output despite declining slope controllers, DC power and voltage, and power electronic back-to-back converters. Overall, the simulation results show that the proposed system shows acceptable performance under different scenarios. The accuracy of the results is validated with mathematical formulation simulation using MATLAB software. This system can be utilized in distant regions where there is no power grid or in areas where, despite having a power infrastructure, renewable energies are used to supply the output load for the majority of the day and night

Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks

This paper presents a new optimal power flow (OPF) formulation for monopolar DC networks using a recursive convex representation. The hyperbolic relation between the voltages and power at each constant power terminal (generator or demand) is represented as a linear constraint for the demand nodes and generators. To reach the solution for the OPF problem a recursive evaluation of the model that determines the voltage variables at the iteration t+1 (vt+1) by using the information of the voltages at the iteration t (vt) is proposed. To finish the recursive solution process of the OPF problem via the convex relaxation, the difference between the voltage magnitudes in two consecutive iterations less than the predefined tolerance is considered as a stopping criterion. The numerical results in the 85-bus grid demonstrate that the proposed recursive convex model can solve the classical power flow problem in monopolar DC networks, and it also solves the OPF problem efficiently with a reduced convergence error when compared with semidefinite programming and combinatorial optimization methods. In addition, the proposed approach can deal with radial and meshed monopolar DC networks without modifications in its formulation. All the numerical implementations were in the MATLAB programming environment and the convex models were solved with the CVX and the Gurobi solver

Maximum Power Point Tracking for Photovoltaic Systems Operating under Partially Shaded Conditions Using SALP Swarm Algorithm

This article presents a new method based on meta-heuristic algorithm for maximum power point tracking (MPPT) in photovoltaic systems. In this new method, the SALP Swarm Algorithm (SSA) is used instead of classic methods such as the Perturb and Observe (P&O) method. In this method, the value of the duty cycle is optimally determined in an optimization problem by SSA in order to track the maximum power. The objective function in this problem is maximizing the output power of the photovoltaic system. The proposed method has been applied on a photovoltaic system connected to the load, taking into account the effect of partial shade and different atmospheric conditions. The SSA method is compared with the Particle Swarm Optimization (PSO) algorithm and P&O methods. Additionally, we evaluated the effect of changes in temperature and radiation on solving the problem. The results of the simulation in the MATLAB/Simulink environment show the optimal performance of the proposed method in tracking the maximum power in different atmospheric conditions compared to other methods. To validate the proposed algorithm, it is compared with four important indexes: ISE, ITSE, IAE, and ITAE

A Sustainable Energy Distribution Configuration for Microgrids Integrated to the National Grid Using Back-to-Back Converters in a Renewable Power System

A desire to produce power in microgrids has grown as the demand for electricity has expanded and the cost of installing modern transmission lines over long distances has become infeasible. As such, microgrids pose DC/AC harmonic distortion losses to the voltage supply that eventually fluctuate the output voltage. The key takeaways that this study presents are: (a) a configuration for microgrids integrated to the national grid using back-to-back converters in a renewable power system is achieved; (b) different scenarios of various schemes of sustainability of the power management in microgrids are analyzed; and (c) the reliable and stable network output power distribution is achieved. In this, the proposed control configuration provides space for construction and stability of the power system with sustainability of the power management. The results show that this current configuration works and stabilizes the network in the shortest time possible, and that the DC connection voltage is regulated and maintains reliable network output despite declining slope controllers, DC power and voltage, and power electronic back-to-back converters. Overall, the simulation results show that the proposed system shows acceptable performance under different scenarios. The accuracy of the results is validated with mathematical formulation simulation using MATLAB software. This system can be utilized in distant regions where there is no power grid or in areas where, despite having a power infrastructure, renewable energies are used to supply the output load for the majority of the day and night

Allocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm

Given the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new algorithm based on the behavior of salp is used. The objective functions include reducing losses, improving voltage profiles, and reducing the costs of renewable energy sources. In this method, the allocation of renewable resources is considered for different load models in distribution systems and different load levels using smart meters. Due to the fact that these objective functions are multi-objective, the fuzzy decision-making method is used to select the optimal solution from the set of Pareto solutions. The considered objective functions lead to loss reduction, voltage profile improvement, and RES cost reduction (A allocating RES resources optimally without resource limitations; B: allocating RES resources optimally with resource limitations). In addition, daily wind, solar radiation, and temperature data are taken into account. The proposed method is applied to the IEEE standard 33-bus system. The simulation results show the better performance of the multi-objective salp swarm algorithm (MSSA) at improving voltage profiles and reducing losses in distribution systems. Lastly, the optimal results of the MSSA algorithm are compared with the PSO and GA algorithms