Novel Control Strategy for Enhancing Microgrid Operation Connected to Photovoltaic Generation and Energy Storage Systems

Optimizing energy management strategies for microgrids through chaotic local search and particle swarm optimization techniques

The advent of multi-Microgrid (MG) energy systems necessitates the optimization of management strategies to curtail operational costs. This paper introduces an innovative MG energy management strategy that integrates Chaotic Local Search (CLS) with Particle Swarm Optimization (PSO) to fulfill this requirement. Our approach leverages PSO for extensive global exploration and subsequently employs CLS to refine local searches, thereby ensuring the attainment of optimal global outcomes. To further enhance performance, we have crafted a PSO algorithmic framework underpinned by chaotic local search principles, aimed at circumventing regions of local optima. The study presents a comprehensive MG energy system model that encompasses a photovoltaic generation unit, battery energy storage, and a micro gas turbine. The experimental data corroborates that our proposed algorithm secures optimal solutions within a range of 48.2-51.7, outperforming others in achieving these optimal resolutions. When juxtaposed with Scenario 1, there is a significant reduction in both operational and primary energy conversion costs by 24.22 % and 31.39 %, respectively. In comparison to Scenario 2, these figures are reduced by an additional 3.08 % and 6.05 %, respectively. The research findings underscore the strategy's exceptional performance in optimization tasks, as illustrated by the simulation outcomes. The methodology's application to a micro-energy network substantiates its practical relevance. Collectively, this research offers a holistic solution for the optimization of MG energy systems, effectively merging theoretical progress with tangible practical applications.

MTDC Grids: A Metaheuristic Solution for Nonlinear Control

This scientific paper aims to increase the voltage source converter (VSC) control efficiency in a multi-terminal high voltage direct current (MTDC) network during dynamic operations. In the proposed study, the Mayfly algorithm (MA) is used to modify the control parameters of VSC stations. Traditional strategies that modify VSC control settings using approximate linear models fail to produce optimal results because VSCs are nonlinear characteristics of the MTDC system. Particle swarm optimization (PSO) may produce optimal outcomes, but it is prone to becoming stuck in a local optimum. To modify the proportional-integral (P.I.) control parameters of the VSC station, the Mayfly algorithm, a modified form of PSO, is used. The suggested algorithm’s objective function simultaneously optimizes both the outer and inner control layers. A four-terminal MTDC test system is developed in PSCAD/EMTDC to assess the benefits of the proposed algorithm. For VSCs, a comparison of classical, PSO, and proposed MA-based tuned parameters is carried out. The integral of time multiplied by absolute error (ITAE) criterion is used to compare the performance of classical, PSO, and a proposed algorithm for VSC controller parameters/gains. With an ITAE value of 6.8521 × 10−6, the MA-based proposed algorithm computes the optimal values and outperforms its predecessor to adjust the VSCs controller gains. For (i) wind farm power variation, (ii) AC grid load demand variation, and (iii) ultimate permanent VSC disconnection, steady-state and dynamic performances are evaluated. According to the results, the proposed algorithm based MTDC system performs well during transients.

Design and Analysis of Sliding-Mode Artificial Neural Network Control Strategy for Hybrid PV-Battery-Supercapacitor System

Nowadays, the growing integration of renewable energy sources poses several challenges to electrical energy systems. The latter need be controlled by grid rules to ensure their stability and maintain the efficiency of renewable energy consumption. In this context, a novel HESS (hybrid energy storage system) control strategy, combining the PV (photovoltaic) generator with FLC (fuzzy logic control), SC (super-capacitor), and lithium-ion battery modules, is advanced. The proposed energy control rests on monitoring of the low-frequency and high-frequency electrical power components of the mismatch between power demand and generation, while applying the error component of the lithium-ion battery current. On accounting for the climatic condition and load variation considerations, the SC undertakes to momentarily absorb the high-frequency power component, while the low-frequency component is diverted to the lithium-ion battery. To improve the storage system’s performance, lifetime, and avoid load total disconnection during sudden variations, we consider equipping the envisioned energy control design with controllers of SM and ANN types. The MATLAB/Simulink based simulation results turn out to testify well the investigated HESS control scheme’s outstanding performance and efficiency in terms of DC bus voltage rapid regulation, thereby enhancing the battery’s lifetime and ensuring the PV system’s continuous flow.

Constant Power Load Stabilization in DC Microgrids Using Continuous-Time Model Predictive Control

Despite its advantages over its AC counterparts, DC microgrids present a lot of challenges. One of these challenges is the instability issues caused by constant power loads (CPLs). CPLs deteriorate the system’s performance due to their incremental negative impedance characteristics. In this paper, a DC microgrid composed of a PV/battery system feeding a pure CPL was considered. A continuous-time model predictive control combined with a disturbance observer was applied to the DC–DC bidirectional converter. The purpose of the composite controller is to address the nonlinearity of the CPL and to maintain the stability of the system in a large operating region under load and PV generation variations. To show the performance of the system, several tests were performed under PV power and CPL power variations. Simulation results show good performance in terms of transient response, optimal tracking, and stability in a large operating region.

Mitigating Generation Schedule Deviation of Wind Farm Using Battery Energy Storage System

Meeting the generation schedule in a wind farm is a major issue. This work utilized battery energy storage systems (BESS) integrated wind farms (WF) to supply energy to the power grid at a pre-determined generation schedule, which was set previously based on the meteorological forecast and BESS characteristics. This study proposed the integration of two independently controlled BESS into the WF to balance stochastic power deviations between actual wind power and scheduled power. By utilizing linear optimization and solving in MATLAB, simulation models of the operations of BESS-integrated WF have been developed. The technical performance of the BESS-integrated wind farm on meeting the generation schedule, along with the cost benefits and profit attributed to the BESS, is therefore measured by a series of indices. The simulation on a practical wind farm, i.e., Adama-I WF, Ethiopia shows that even though it depends on the type of state exchanging strategy adopted, the developed methodology of integrating BESS into the WF is effective and BESS profits can totally cover the cost. Technical and economic indices that resulted from the integration of two separate BESSs with independent control were compared with indices that resulted from integrating a single BESS. Simulation results show that operating the wind farm with two independently controlled batteries has better performance as compared to operating with a single battery. It also shows that the discharging and charging state exchanging approaches of the BESS (in the case of two battery integration), as well as the number of batteries integrated into the wind farm, have significant impacts on the performance of the WF integrated with BESS.

Wind-Photovoltaic-Energy Storage System Collaborative Planning Strategy Considering the Morphological Evolution of the Transmission and Distribution Network

The collaborative planning of a wind-photovoltaic (PV)-energy storage system (ESS) is an effective means to reduce the carbon emission of system operation and improve the efficiency of resource collaborative utilization. In this paper, a wind-PV-ESS collaborative planning strategy considering the morphological evolution of the transmission and distribution network is proposed. Firstly, aiming at the optimal economy of transmission and distribution network and considering the constraints of safe and stable operation of the system, the planning model of the transmission network based on DC power flow and the planning model of the distribution network based on AC power flow are constructed. Further, considering the coupling interaction between the transmission and distribution networks, a collaborative planning model of transmission and distribution networks based on second-order cone relaxation (SOCR) is constructed. Secondly, in order to reduce the computational complexity of the model and ensure the global optimality of the model solution, a fast model solution method based on heterogeneous decomposition architecture is proposed. Thirdly, the multiple driving factors of the morphological evolution of transmission and distribution network are analyzed, the morphological evolution path and typical characteristics of transmission and distribution network are determined, and a wind-PV-ESS collaborative planning strategy considering the morphological evolution of a transmission and distribution network is proposed. Finally, the results show that, compared with the sprouting period, the overall economy of the development period and maturity period is improved by 3342 k$ and 5751 k$ respectively, and the effectiveness and necessity of the collaborative planning strategy proposed in this paper is verified.

Stochastic Approach to Hosting Limit of Transmission System and Improving Method Utilizing HVDC

According to the global de-carbonization trends, renewable energy integration has become an increasingly important issue in power systems. To achieve 100% renewable energy integration and operate a system with these resources, it is necessary to appropriately evaluate the system hosting capability and prepare appropriate planning and operation strategies using the evaluation result. So far, these interests have focused particularly on distribution-level systems. However, although the hosting limit in transmission-level systems requires further consideration, previous study is limited. This study introduces the constraints on the transmission-level hosting limit. In addition, a stochastic estimation of the hosting limit methodology in the transmission system and the use of a high voltage direct current system to improve hosting capacity are proposed and evaluated. Moreover, these methodology-based simulations are conducted using possible scenarios on the IEEE 39 bus system with some constraints, and the simulation results are presented herein. The results showed that the HVDC location selection and operation using the proposed method and optimization technique is appropriate. The strategy can be used to integrate more renewable energy. Furthermore, the proposed methodology can be applied to renewable energy integration scenario establishing a plan.

The Influence of Temperature on the Capacity of Lithium Ion Batteries with Different Anodes

Temperature is considered to be an important indicator that affects the capacity of a lithium ion batteries. Therefore, it is of great significance to study the relationship between the capacity and temperature of lithium ion batteries with different anodes. In this study, the single battery is used as the research object to simulate the temperature environment during the actual use of the power battery, and conduct a charge and discharge comparison test for lithium iron phosphate battery, lithium manganate battery and lithium cobalt oxide battery. In the test of capacity characteristics of lithium ion batteries of three different cathode materials at different temperatures, the optimal operating temperature range of the lithium ion battery is extracted from the discharge efficiencies obtained. According to the research results, the discharge capacity of a lithium ion battery can be approximated by a cubic polynomial of temperature. The optimal operating temperature of lithium ion battery is 20–50 °C within 1 s, as time increases, the direct current (DC) internal resistance of the battery increases and the slope becomes smaller. Between 1 s and 10 s, the DC internal resistance of the battery basically shows a linear relationship with time. In the charge and discharge process, when state of charge (SOC) 0% and SOC 100%, the internal resistance of the battery is the largest. The SOC has the greatest impact on the polarization internal resistance, and the smallest impact on the ohmic internal resistance.

Modified Permanent Magnet Synchronous Generators for Using in Energy Supply System for Autonomous Consumer

In this paper, the possibility of using synchronous generators with magnetoelectric excitation for the autonomous consumers’ supply with the use of renewable energy sources is considered. To eliminate a number of the disadvantages associated with the difficulty of energy-efficient regulation of the generated parameters, such as the generated current and voltage, the use of modified multi-winding synchronous generators with permanent magnets is proposed. It allows solving the problem of controlling this type of generator. In addition, the use of this type of generator helps to increase the amount of energy generated. The authors have proposed several synchronous generators with permanent magnets of various supply network architectures: single-phase, two-phase and traditional three-phase types. This will simplify the design of architecture for several cases of consumer power supply systems. It will also help to eliminate the need to organize a balanced distribution of loads in phases to prevent accidents, damage and/or disabling of consumers themselves. Here, we considered mathematical descriptions of several types of generators that differ in their assembling, in particular, the number of phases (one-, two- and three-phase generators), the number of pairs of permanent magnet poles on the rotor, and the method of switching the generator windings among themselves. Using the developed mathematical descriptions that describe the operation of every single winding of the generator, their mathematical models were developed in the SimInTech mathematical modeling environment. The results of the mathematical modeling of these generators were presented; their interpretation for use with renewable energy sources was made; and the methods of using these generators were described. The developed mathematical descriptions of synchronous generators with permanent magnets can be used for further study of their operation. It can also help for the development of control systems and power systems for micro-grid energy complexes that use renewable energy sources to increase the energy efficiency of micro-grid systems.

Study on Performance of Rooftop Solar Power Generation Combined with Battery Storage at Office Building in Northeast Region, Vietnam

At present, renewable energy sources are considered to ensure energy security and combat climate change. Vietnam has a high potential for solar power development, especially in the central region and the southern region. However, the northeast region has the lowest solar radiation value, so it can cause difficulty for rooftop solar power investment. In this paper, the study results analyze the financial efficiency of the grid-tied rooftop solar power system with battery storage and compared it to the grid-tied rooftop solar power system without battery storage. The experimental data of a grid-tied solar power system with battery storage at an office building in the northeast region of Vietnam is collected to evaluate the system’s operation performance in real conditions. The study results present that the financial efficiency of rooftop grid-tied power project with and without storage is viable since the benefit-cost ratio (B–C) is larger than one, and internal rate of return (IRR) and net present value (NPV) are positive. However, the grid-tied rooftop solar power system with storage is not quite feasible in case of changing the electricity selling price and investment cost even though the grid-tied solar power system using the storage device can operate more flexibly. The payback period of the grid-tied solar power system with storage is 6.2 years longer and the total profit is nearly 1.9 times lower than the solar power system without battery storage due to the difference in the price of the inverters and the battery. In contrast, the grid-tied solar power system without battery storage shows better financial efficiency but strongly depends on the operation of the utility grid.

Grounding Fault Model of Low Voltage Direct Current Supply and Utilization System for Analyzing the System Grounding Fault Characteristics

Grounding fault analysis is of vital importance for low voltage direct current (LVDC) supply and utilization systems. However, the existing DC grounding fault model is inappropriate for LVDC supply and utilization system. In order to provide an appropriate assessment model for the DC grounding fault impact on the LVDC supply and utilization system, an LVDC supply and utilization system grounding fault model is proposed in this paper. Firstly, the model is derived by utilizing capacitor current and voltage as the system state variable, which considers the impact of the converter switch state on the topology of the fault circuit. The variation of system state parameters under various fault conditions can be easily obtained by inputting system state data in normal conditions as the initial value. Then, a model solution algorithm for the proposed model is utilized to calculated the maximum fault current, the system maximum fault current with different grounding resistance is simple to acquired based on the solution algorithm. The calculation results demonstrate that grounding resistance and structure of LVDC supply and utilization system have remarkable impacts on the transient current. The effectiveness of the proposed model is verified in PSCAD/EMTDC. The simulation results indicate that the proposed method is appropriate for the system fault analysis under various fault conditions with different grounding resistance and the proposed model can offer theoretical guidance for system fault protection.

Optimization of a Multi-Energy Complementary Distributed Energy System Based on Comparisons of Two Genetic Optimization Algorithms

The development and utilization of low-carbon energy systems has become a hot topic of energy research in the international community. The construction of a multi-energy complementary distributed energy system (MCDES) is researched in this paper. Based on the multi-objective optimization theory, the planning optimization of an MCDES is studied, and a three-dimensional objective-optimization model is constructed by considering the constraints of the objective function and decision variables. Aiming at the optimization problem of building terminals for the MCDES studied in the paper, two genetic optimization algorithms—Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Sorting Genetic Algorithm III (NSGA-III)—are used for calculation based on an example analysis. The constraint conditions of practical problems were added to the existing algorithms. Combined with the comparison of the solution quality and the optimal compromise solution of the two algorithms, a multi-decision method is proposed to obtain the optimal solution based on the Pareto optimal frontier of the two algorithms. Finally, the optimal decision scheme of the example is determined and the effectiveness and reliability of the optimization model are verified. Under the application of the MCDES optimization model studied in this paper, the iteration speed and hypervolume index of NSGA-III are found to be better than those of NSGA-II. The values of the life cycle cost and life cycle carbon emission objectives after the optimization of NSGA-III are indicated as 2% and 14% lower, respectively, than those of NSGA-II. The primary energy efficiency of NSGA-III is shown to be 20% higher than that of NSGA-II. According to the optimal decision, the energy operation strategies of the example MCDES with each typical day in the four seasons indicate that good integrated energy application and low-carbon operation performance are shown during the four-seasons operation process. The consumption of renewable energy is significant, which effectively reduces the application of high-grade energy. Thus, the theoretical guidance and engineering application reference are provided for MCDES design planning and operation optimization.

Design of a Laboratory Scale Solar Microgrid Cyber-Physical System for Education

Renewable energy sources such as solar and wind provide an effective solution for reducing dependency on conventional power generation and increasing the reliability and quality of power systems. Presented in this paper are design and implementation of a laboratory scale solar microgrid cyber-physical system (CPS) with wireless data monitoring as a teaching tool in the engineering technology curriculum. In the system, the solar panel, battery, charge controller, and loads form the physical layer, while the sensors, communication networks, supervisory control and data acquisition systems (SCADA) and control systems form the cyber layer. The physical layer was seamlessly integrated with the cyber layer consisting of control and communication. The objective was to create a robust CPS platform and to use the system to promote interest in and knowledge of renewable energy among university students. Experimental results showed that the maximum power point tracking (MPPT) charge controller provided the loads with power from the solar panel and used additional power to charge the rechargeable battery. Through the system, students learned and mastered key concepts and knowledge of multi-disciplinary areas including data sampling and acquisition, analog to digital conversion, solar power, battery charging, control, embedded systems and software programing. It is a valuable teaching resource for students to study renewable energy in CPS.