The paper raises the issue of controlling rural low voltage microgrids in an optimal manner. The impact of different criterion functions, related to the amount of energy exchanged with the distribution system operator network, the level of active power losses, the amount of energy generated by different energy sources and the value of financial performance measures regarding the microgrid operation, on the choice of operating points for devices suggested by the optimization algorithm has been analyzed. Both island and synchronous microgrid operation modes are being considered. We propose two variants of the optimization procedure: the first one is based on the particle swarm optimization algorithm and centralized control logic, and the second one takes advantage of the decentralized approach and Monte Carlo methods. A comparison of the simulation results for two sample rural microgrids, obtained for different objective functions, microgrid operation modes and optimization procedure variants, with the use of prepared algorithm implementations, has been provided. The results show that the proper choice of an objective function can have a crucial impact on the optimization algorithm’s behavior, the choice of operating points and, as a consequence, on microgrid behavior as well. The choice of the proper form of the objective function is the responsibility of the person in charge of both the microgrid itself and its operation. This paper can contribute towards making correct decisions in this area. Generally, slightly better results have been achieved for the centralized control mode of operation. Nevertheless, the results also suggest that in many cases the approach based on distributed logic can return results that are better or sufficiently close to the ones provided by the centralized and more sophisticated approach.

Low voltage microgrids are autonomous subsystems, in which generation, storage and power and electrical energy consumption appear. In the paper the main attention has been paid to the voltage stability issue in low voltage microgrid for different variants of its operation. In the introduction a notion of microgrid has been presented, and also the issue of influence of active and reactive power balance on node voltage level has been described. Then description of voltage stability issue has been presented. The conditions of voltage stability and indicators used to determine voltage stability margin in the microgrid have been described. Description of the low voltage test microgrid, as well as research methodology along with definition of considered variants of its operation have been presented further. The results of exemplary calculations carried out for the daily changes in node load of the active and reactive power, i.e. the voltage and the voltage stability margin indexes in nodes have been presented. Furthermore, the changes of voltage stability margin indexes depending on the variant of the microgrid operation have been presented. Summary and formulation of conclusions related to the issue of voltage stability in microgrids have been included at the end of the paper.

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.

Solar energy is widely available in nature and electricity can be easily extracted using solar PV cells. A fuel cell being reliable and environment friendly becomes a good choice for the backup so as to compensate for continuously varying solar irradiation. This paper presents simple control schemes for power management of the DC microgrid consisting of PV modules and fuel cell as energy sources and a hydrogen electrolyzer system for storing the excess power generated. The supercapacitor bank is used as a short term energy storage device for providing the energy buffer whenever sudden fluctuations occur in the input power and the load demand. A new power control strategy is developed for a hydrogen storage system. The performance of the system is assessed with and without the supercapacitor bank and the results are compared. A comparative study of the voltage regulation of the microgrid is presented with the controller of the supercapacitor bank, realized using a traditional PI controller and an intelligent fuzzy logic controller.

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.

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.