A microgrid with parallel structure operating under islanded mode is considered in this paper. Under microgrid islanded operation mode, lines bring adverse effect for power distribution between microsources (MSs). Because traditional droop control ignores this effect, MSs adopting this method can not achieve satisfactory power distribution. A kind of droop control including line compensation applied to this microgrid is proposed. It can eliminate this effect to obtain satisfactory power distribution. The relationship of two kinds of droop control with power distribution is analyzed. The reference voltage generated by droop control is applied to control output voltage of MSs. Comparison of two kinds of droop control through MATLAB/Simulink simulation is made to verify the superiority of droop control including line compensation for power distribution. The relationship between PCC voltage and output power of MSs is also presented.

In this paper, a novel Power-Frequency Droop Control (PFDC) is introduced to perfectly bring back the system frequency and share the reactive power in isolated microgrid with virtual power plant (VPP). The frequency-based power delivery must be essentially implemented in VPP which can operate as a conventional synchronous generator. It has been attained by enhancing the power processing unit of each VPP to operate as an active generator. The inverter coupling impedance which has been assigned by the virtual impedance technique has reduced the affected power coupling resulting from line resistance. The reference has been subsequently adjusted to compensate the frequency deviation caused by load variation and retrieve the VPP frequency to its nominal value. In addition, the line voltage drop has compensated the voltage drop and load sharing error to obliterate the reactive power sharing imprecision resulting from the voltage deviation. The voltage feedback confirms the correct voltage after compensating the voltage drop. As an illustration, conventional PFDC after a load change cannot restore the system frequency which is deviated from 50 Hz and rested in 49.9 Hz while, proposed PFDC strategy fades away the frequency deviation via compensating the variation of the frequency reference. Likewise, the frequency restoration factor ( γ) has an effective role in retrieving the system frequency, i.e., the restoration rate of the system frequency is in proportion with γ. As a whole, the simulation results have pointed to the high performance of proposed strategy in an isolated microgrid.

The paper raises the issue of optimizing the control of the rural low voltage microgrids. Microgrids can operate in a synchronous mode with grids of distribution system operators and in an island mode. We can distinguish two control strategies in microgrids: one approach based on centralized control logic, which is usually used, and another on decentralized control logic. In this paper we decided to present the approach based on the distributed control, combining the efforts of the distributed cooperative control and modified Monte Carlo optimization method. Special attention has been paid to the impact of the order of processing particular devices’ groups on results of optimization calculations. Moreover, different scenarios of behavior of the microgrid control system with respect to the communication loss have been also presented. The influence of the issue of continuity of communication between particular devices’ groups on the possibility of carrying out the optimization process has been investigated. Additionally, characteristics of power loads and generation of electricity from small renewable energy sources appearing in rural areas have been described and the sensitivity of the optimization algorithm to the changes of demanded power values and changes of values of power generated by renewable energy sources has been studied. We analyzed different objective functions which can be used as an optimization goal both in synchronous and island operation modes of microgrid. We decided to intensively test our approach on a sample rural LV microgrid, which is typical in the countryside. The observed results of the tests have been presented and analyzed in detail. Generally, results achieved with the use of proposed distributed control are the same as with the use of centralized control. We think that the approach based on distributed control is promising for practical applications, because of its advantages.

In this paper, a control strategy for real-time operation of a master-slave controlled microgrid is developed. The basic idea of this control strategy is to schedule all dispatchable energy sources available into a microgrid to minimize its operational costs. Control actions are centrally evaluated by solving a two-stage optimization problem formulated to take place on two different time-scales: in the day-ahead and in the real-time. The first one provides a 24-hour plan in advance. It mainly draws up the active power levels that Distributed Energy Resources (DERs) should provide for each quarter hour of the next day by taking into account energy prices of the day-ahead energy market, the forecasted energy production of non-dispatchable renewables and loads. The real-time optimization problem updates the active power set-points of DERs in order to minimize as much as possible the real-time deviations between the actual power exchanged with the utility grid and its scheduled value. The effectiveness of the proposed methodology has been experimentally tested on an actual microgrid.

Currently, the distribution system has been adapted to include a variety of Distributed Energy Resources (DERs). Maximum benefits can be extracted from the distribution system with high penetration of DERs by transforming it into a sustainable, isolated microgrid. The key aspects to be addressed for this transformation are the determination of the slack bus and assurance of reliable supply to the prioritized loads even during contingency. This paper explores the possibilities of transforming the existing distribution system into a sustainable isolated network by determining the slack bus and the optimal locations and capacity of Distributed Generators (DGs) in the isolated network, taking into account the contingencies due to faults in the network. A combined sensitivity index is formulated to determine the most sensitive buses for DG placement. Further, the reliability based on the loss of load in the isolated system when a fault occurs is evaluated, and the modifications required in for reliability improvement are discussed. The supremacy of the transformed isolated network with distributed generators is comprehended by comparing the results from conventional IEEE 33-bus grid connected test system and modified IEEE 33-bus isolated test system having no interconnection with the main grid.

The abundant use of solar energy in Indonesia has the potential to become electrical energy in a microgrid system. Currently the use of renewable energy sources (RESs) in Indonesia is increasing in line with the reduction of fossil fuels. This paper proposes a new microgrid DC configuration and designs a centralized control strategy to manage the power flow from renewable energy sources and the load side. The proposed design uses three PV arrays (300 Wp PV module) with a multi-battery storage system (MBSS), storage (200 Ah battery). Centralized control in the study used an outseal programmable logic controller (PLC). In this study, the load on the microgrid is twenty housing, so that the use of electrical energy for one day is 146.360 Wh. It is estimated that in one month it takes 4.390.800 Wh of electrical energy. The new DC microgrid configuration uses a hybrid configuration, namely the DC coupling and AC coupling configurations.The results of the study show that the DC microgrid hybrid configuration with centralized control is able to alternately regulate the energy flow from the PV array and MBSS. The proposed system has an efficiency of 98% higher than the previous DC microgrid control strategy and configuration models.

In this study, the inverter in a microgrid was adjusted by the particle swarm optimization (PSO) based coordinated control strategy to ensure the stability of the isolated island operation. The simulation results showed that the voltage at the inverter port reduced instantaneously, and the voltage unbalance degree of its port and the port of point of common coupling (PCC) exceeded the normal standard when the microgrid entered the isolated island mode. After using the coordinated control strategy, the voltage rapidly recovered, and the voltage unbalance degree rapidly reduced to the normal level. The coordinated control strategy is better than the normal control strategy.

Water scarcity is a phenomenon that is occurring more and more frequently in larger areas of Europe. As a result of drought, there are significant drops in yields. As demand for food continues to rise, it is becoming necessary to bring about a substantial increase in crop production. The best solution to water scarcity appears to be irrigation for crops that are particularly sensitive to drought. Today, many technical solutions are used to supply and distribute water to crops. The optimal solution is drip irrigation, which makes it possible to deliver water directly to the plant root system to save melting freshwater resources. In the article special attention was paid to methods of supplying electricity to power irrigation pumps. The analysis was made for areas with a significant distance between the agricultural land and the urbanised area (which has water and electricity). The authors have selected the parameters of an off-grid photovoltaic mini-hydropower plant with energy storage (with a power of 1.36 kW). An analysis was made of the profitability of such an investment and a comparison with other types of power supply. Based on the performed calculations, a prototype power supply system equipped with photovoltaic panels was made to show the real performance of the proposed system. The tests carried out showed that the irrigation pump will be powered most of the time with a voltage whose parameters will be very close to the nominal ones.

In microgrid distribution generation (DG) sources are integrated parallelly for the economic and efficient operation of a power system. This integration of DG sources may cause many challenges in a microgrid. The islanding condition is termed a condition in which the DG sources in the microgrid continue to power the load even when the grid is cut off. This islanding situation must be identified as soon as possible to avoid the collapse of the microgrid. This work presents the hybrid islanding detection technique. This technique consists of both active and parametric estimation methods such as slip mode shift frequency (SMS) and exact signal parametric rotational invariance technique (ESPRIT), respectively. This technique will easily distinguish between islanding and non-islanding events even under very low power perturbations. The proposed method also has no power quality impact. The proposed method is tested with UL741 standard test conditions.

Nowadays, the development of smart grids has been the focus of attention due to its advantages for power systems. One of the aspects of smart grids defined by using distributed generation (DG) in a low voltage network is a microgrid (MG). Based on its operational states, MG can operate in different configurations such as grid-connected mode or off-grid mode. The switching between these states is one of the challenging issues in this technical area. The fault currents in different buses have higher value compared to islanded mode of MG when the MG is connected to the main grid, which influences the protection equipment. In this situation, some electrical devices may be damaged due to the fault currents. Application of a fault current limiter (FCL) is considered as an effective way to overcome this challenge. The optimal size of these FCLs can optimize the performance of an MG. In this paper, an index for FCL size optimization has been used. In addition, two optimization algorithms (Bat Algorithm and Cuckoo Search Algorithm) have been applied to the problem. The application of an FCL has been studied in grid-connected and islanded-mode. In addition, the application of the capacitor bank in both modes has been investigated. The results of simulations carried out by MATLAB have been presented and compared.

In a PV-dominant DC microgrid, the traditional energy distribution method based on the droop control method has problems such as output voltage drop, insufficient power distribution accuracy, etc. Meanwhile, different battery energy storage units usually have different parameters when the system is running. Therefore, this paper proposes an improved control method that introduces a reference current correction factor, and a weighted calculation method for load power distribution based on the parameters of battery energy storage units is proposed to achieve weighted allocation of load power. In addition, considering the variation of bus voltage at the time of load mutation, voltage secondary control is added to realize dynamic adjustment of DC bus voltage fluctuation. The proposed method can achieve balance and stable operation of energy storage units. The simulation results verified the effectiveness and stability of the proposed control strategy.

This study suggests a new algorithm based on a combination of fuzzy logic and genetic algorithm (GA) to improve voltage profile in a microgrid. The considered microgrid includes control variables such as onload tap changer (OLTC), active power output from distributed generators (DG) and reactive power output from feeder switched capacitors that are controlled in a microgrid controller (MGC) by communication links. The proposed method was used to obtain the optimum value of control variables to establish voltage stabilization in varying load condition as online. For establishing voltage stabilization at the microgrid, an objective function is defined and is tried to minimize it by control variables. The control variables were changed based on fuzzy logic and the GA was employed for finding the optimum shape of membership functions. In order to verify the proposed method, a 34 buses microgrid in varying load condition was analyzed and was compared with previous works.

The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.

In this paper, an energy coordination control method based on intelligent multi-agent systems (MAS) is proposed for energy management and voltage control of a DC microgrid. The structure of the DC microgrid is designed to realize the mathematical modeling of photovoltaic cells, fuel cells and batteries. A two-layer intelligent MAS is designed for energy coordination control: grid-connection and islanding of a DC microgrid is combined with energy management of PV cells, fuel cells, loads and batteries. In the hidden layer and the output layer of the proposed neural network there are 17 and 8 neurons, respectively, and the “logsig” activation function is used for the neurons in the network. Eight kinds of feature quantities and 13 different actions are taken as the input and output parameters of the neural network from the micro-source and the load, and the as the control center agent’s decision-makers. The feasibility of the proposed intelligent multi-agent energy coordination control strategy is verified by MATLAB/Simulink simulation, and three types of examples are analyzed after increasing the load. The simulation results show that the proposed scheme exhibits better performance than the traditional approaches.

The paper presents a honey badger algorithm (HB) based on a modified backwardforward sweep power flow method to determine the optimal placement of droop-controlled dispatchable distributed generations (DDG) corresponding to their sizes in an autonomous microgrid (AMG). The objectives are to minimise active power loss while considering the reduction of reactive power loss and total bus voltage deviation, and the maximisation of the voltage stability index. The proposed HB algorithm has been tested on a modified IEEE 33-bus AMG under four scenarios of the load profile at 40%, 60%, 80%, and 100% of the rated load. The analysis of the results indicates that Scenario 4, where the HB algorithm is used to optimise droop gains, the positioning of DDGs, and their reference voltage magnitudes within a permissible range, is more effective in mitigating transmission line losses than the other scenarios. Specifically, the active and reactive power losses in Scenario 4 with the HB algorithm are only 0.184% and 0.271% of the total investigated load demands, respectively. Compared to the base scenario (rated load), Scenario 4 using the HB algorithm also reduces active and reactive power losses by 41.86% and 31.54%, respectively. Furthermore, the proposed HB algorithm outperforms the differential evolution algorithm when comparing power losses for scenarios at the total investigated load and the rated load. The results obtained demonstrate that the proposed algorithm is effective in reducing power losses for the problem of optimal placement and size of DDGs in the AMG.

The smart grid concept is predicated upon the pervasive use of advanced digital communication, information techniques, and artificial intelligence for the current power system, to be more characteristics of the real-time monitoring and controlling of the supply/demand. Microgrids are modern types of power systems used for distributed energy resource (DER) integration. However, the microgrid energy management, the control, and protection of microgrid components (energy sources, loads, and local storage units) is an important challenge. In this paper, the distributed energy management algorithm and control strategy of a smart microgrid is proposed using an intelligent multi-agent system (MAS) approach to achieve multiple objectives in real-time. The MAS proposed is developed with co-simulation tools, which the microgrid model, simulated using MATLAB/Simulink, and the MAS algorithm implemented in JADE through a middleware MACSimJX. The main study is to develop a new approach, able to communicate a multi-task environment such as MAS inside the S-function block of Simulink, to achieve the optimal energy management objectives.

In recent years, due to the increasing number of renewable energy sources, which are characterised by the stochastic nature of the generated power, interest in energy storage has increased. Commercial installations use simple deterministic methods with low economic efficiency. Hence, there is a need for intelligent algorithms that combine technical and economic aspects. Methods based on computational intelligence (CI) could be a solution. The paper presents an algorithm for optimising power flow in microgrids by using computational intelligence methods. This approach ensures technical and economic efficiency by combining multiple aspects in a single objective function with minimal numerical complexity. It is scalable to any industrial or residential microgrid system. The method uses load and generation forecasts at any time horizon and resolution and the actual specifications of the energy storage systems, ensuring that technological constraints are maintained. The paper presents selected calculation results for a typical residential microgrid supplied with a photovoltaic system. The results of the proposed algorithm are compared with the outcomes provided by a deterministic management system. The computational intelligence method allows the objective function to be adjusted to find the optimal balance of economic and technical effects. Initially, the authors tested the invented algorithm for technical effects, minimising the power exchanged with the distribution system. The application of the algorithm resulted in financial losses, €12.78 for the deterministic algorithm and €8.68 for the algorithm using computational intelligence. Thus, in the next step, a control favouring economic goals was checked using the CI algorithm. The case where charging the storage system from the grid was disabled resulted in a financial benefit of €10.02, whereas when the storage system was allowed to charge from the grid, €437.69. Despite the financial benefits, the application of the algorithm resulted in up to 1560 discharge cycles. Thus, a new unconventional case was considered in which technical and economic objectives were combined, leading to an optimum benefit of €255.17 with 560 discharge cycles per year. Further research of the algorithm will focus on the development of a fitness function coupled to the power system model.

Three synchronous machine models representing three precision levels (complete, reduced and static), implemented in a virtual synchronous generator (VSG)-based industrial inverter, are compared and discussed to propose a set of tests for a possible standardization of VSG-based inverters and to ensure their “grid-friendly” operation in the context of isolated microgrids. The models and their implementation in the microcontroller of an industrial inverter (with the local control) are discussed, including the usability of the implementation with large-scale developments constraints in mind. The comparison is conducted based on existing standards (for synchronous machines and diesel generators) in order to determine their needed evolution, to define the requirements for future grid-friendly inverter-based generators, notably implementing a VSG solution.

This paper highlights the storage charging and discharging issue. The study objective is to manage the energy inputs and outputs of the principal grid at the same time in order to maximize profit while decreasing costs, as well as to ensure the availability of energy according to demand and the decisions to either save or search for energy. A fuzzy logic control model is applied in MATLAB Simulink to deal with the system’s uncertainties in scheduling the storage battery technology and the charging- discharging. The results proved that the fuzzy logic model has the potential to efficiently lower fluctuations and prolong the lifecycle.