Hybrid Energy Microgrid Research Articles

Cost-effective energy management of an islanded microgrid

The interest in the integration of distributed energy resources in microgrids increased significantly in the last decade. The stochastic nature of some energy sources and the dynamic power demand has brought difficulties regarding the optimal control of microgrids. This current study addresses the energy management challenge in an islanded hybrid energy microgrid that includes three types of renewable energy resources (photovoltaic, geothermal and biomass) and a battery storage system, using intelligent management methods that optimize energy production costs. The proposed intelligent management methods are based on cost function minimization. These ensure optimal energy management operation under uncertain weather conditions, keeping to the minimum the price of the energy produced by the microgrid. Due to the erratic nature of solar irradiance and considering that solar energy is cheaper than its counterparts (geothermal and biomass in this case), forecasting the photovoltaic power production is an essential task for guaranteeing optimal microgrid operation. Day-ahead photovoltaic power forecasts are issued based on solar irradiance forecasts provided by the Global Forecasting System and further integrated into the day-ahead scheduling of the microgrid. This algorithm, together with the cost-optimization algorithms, gives intelligence to the management protocol generating the input parameters (power and operating time for each generating unit) for the microgrid Energy Management Controller. Different cost optimization methods are studied and compared, including mathematical models, such as Mixed Integer Linear Programming, or nature-inspired optimization algorithms, such as Genetic Algorithm, Harmony Search Algorithm, and Particle Swarm Optimization. It is shown that these algorithms provided suitable solutions for the energy balance and scheduling ensuring minimal operation costs for the microgrid. The study also highlights the differences and limitations of these algorithms and shows a method on how these energy management methods can be integrated into a real-world microgrid providing a step forward in the development of intelligent microgrids.

A multi-objective optimization model for sizing an off-grid hybrid energy microgrid with optimal dispatching of a diesel generator

The paper presents a multi-objective optimization model for sizing and operating a hybrid energy system consisting of solar photovoltaic, wind energy, diesel generator, and battery storage. A new concept of optimizing the diesel generator loading percentage has been introduced. Also, the introduced battery management criteria will enable an adaptive operation hours of the diesel generator while regulating the battery state of charge. The proposed optimization model aims to minimize the total investment cost, operation & maintenance cost, and system’s carbon emissions. The number of PV panels, number of wind turbines, rated diesel generator capacity, rated battery capacity, and optimal loading percentage of the diesel generator will be optimized. The multi-objective optimization will be done using the Genetic Algorithm using MATLAB software. Obtained results are presented in a Pareto optimal chart for better analysis. The fuel cost per day, the levelized cost of electricity, the diesel generator on hours, and the emission factor of the hybrid system have been determined for each optimal output. A comparison was carried out with a previously proposed study and found that the proposed method increases the lifetime of the diesel generator by 42.9%. The optimal loading percentage of the diesel generator is found to be 75%. The proposed optimization model reduced the total cost and carbon emissions of the hybrid energy system by 3.5% and 0.7%, respectively. The levelized cost of energy and the payback period of the proposed hybrid microgrid system are 0.16 USD/kWh and 8 years, respectively, which verify that the proposed system is economically feasible.

An algorithm for power flow analysis in isolated hybrid energy microgrid considering DG droop model and virtual impedance control loop

Power flow analysis (PF) is an essential tool for secure and efficient operation in power systems. For isolated microgrid (IMG) with only local distributed generators (DGs), there is no slack bus that enables the microgrid to have a constant frequency. So, the bus admittance matrix (Ybus) is not fixed. Also, IMG usually has droop-controlled DGs (DCDG) whose voltage and power are frequency-dependent. These factors make PF a challenging task for IMG that cannot be accomplished through the classic PF techniques. This paper proposes a substantial modification to the well-established Newton–Raphson PF algorithm, called (ENR), to fit the IMG. A new formulation of the Jacobian matrix is developed to accommodate the different control characteristics of DGs as well as the frequency variation. Droop control, maximum power point tracking, and constant power control are considered as DG control types with complete models. Moreover, the virtual impedance concept and its control loop are integrated into the DCDG control scheme to guarantee the stable operation regardless the microgrid X/R ratio. Further, the ENR convergence speed is improved by introducing acceleration factors for voltage angle, magnitude, and frequency. The optimal acceleration factors are determined using a modified PSO method. The ENR is applied to a 45-bus IMG with 12 renewable and dispatchable DGs based on a modified version of the IEEE 33-bus test system. Results are compared to time-domain simulations and also to recent literature. The accuracy and high speed of the ENR are verified.

Energy management system for optimal cost and storage utilization of renewable hybrid energy microgrid

This paper proposes an improved energy management system to reduce the energy cost and the storage utilization of a hybrid solar and wind energy microgrid with battery storage and grid-connected option. The performance improvement relies on a parameter, called the contribution factor, that provides an adequate amount of the required power from the battery based on the electricity price of the main grid. Different profiles, for that factor, are investigated to enhance the system performance. Load shifting mechanism has been integrated into the energy management to enhance the energy cost. The system uses the efficiencies of the components to accurately compute the energy cost. Simulations have been performed for different rates of the load demand and results have shown the superiority of the proposed energy management system compared to the conventional one with respect to reducing the energy cost, the battery degradation cost and increasing the battery lifespan. From the results, it has been found that using a linear profile for the contribution factor and the load shifting will result in daily costs of $68.27 and $0.81 for the energy and the degradation, respectively. These costs represent a 25.66 % decrease in energy cost and a 91.72 % decrease in battery degradation cost compared to the conventional energy management system where the grid electricity and the load shifting are not considered in the usage of the battery storage.

Design and control of hybrid energy microgrid system using renewable energy sources

Decentralized distributed generation technologies based on renewable energy resources like Photo Voltaic (PV) or/and Wind Turbine Generators (WTG) address the above barriers to large extent and are therefore considered as emerging alternate power solutions to telecommunication base stations. Three stand-alone SPV power systems using different storage technologies i.e. PV-Battery system, PV-Fuel Cell (FC) system and SPV-FC-Battery system are optimized, analysed, compared in paper. PV configurations with tracker also included. According simulation results observed that PV-Battery hybrid system with maximum power point tracker most economical solution. Cost and energy sensitivity with solar radiation data also analysed in this paper. Hybrid system modelling, designing of each component of Hybrid system is done in MATLAB sim power. In this paper, the hybrid system modelled is used for the different insulation, noticed the power output change with the insulation input change. Simulation is done for a step change of 1 kW for the PV-FC system. Different Maximum power point tracking algorithms are discussed, from these algorithms P&O method is implemented in MATLAB. Simulation done for one module and compared the result with actual result. This MPPT tracker used in the PV-FC, PV-Battery-FC hybrid systems for extracting the maximum power available from the PV system.

Economic dispatch of household PV-BS-EV microgrid under TOU tariffs

Economic dispatch is a hotspot issue of household hybrid energy microgrid. This paper gives modellings of a typical household microgrid integrated with solar PV, battery energy storage system (BS) and electric vehicle (EV). The charging/discharging strategy of EV and its coordinated dispatch strategy with supply side units are presented to solve the minimum system operation objective under time of use (TOU) tariffs. The simulation results show that the proposed method is effective and feasible.

Optimal Sizing of an Island Hybrid Microgrid Based on Improved Multi-Objective Grey Wolf Optimizer

The hybrid renewable energy system is a promising and significant technology for clean and sustainable island power supply. Among the abundant ocean energy sources, tidal current energy appears to be very valuable due to its excellent predictability and stability, particularly compared with the intermittent wind and solar energy. In this paper, an island hybrid energy microgrid composed of photovoltaic, wind, tidal current, battery and diesel is constructed according to the actual energy sources. A sizing optimization method based on improved multi-objective grey wolf optimizer (IMOGWO) is presented to optimize the hybrid energy system. The proposed method is applied to determine the optimal system size, which is a multi-objective problem including the minimization of annualized cost of system (CACS) and deficiency of power supply probability (DPSP). MATLAB software is utilized to program and simulate the hybrid energy system. Optimization results confirm that IMOGWO is feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. Furthermore, comparison of hybrid systems with and without tidal current turbines is undertaken to confirm that the utilization of tidal current turbines can contribute to enhancing system reliability and reducing system investment, especially in areas with abundant tidal energy sources.

Optimal configuration of hybrid‐energy microgrid considering the correlation and randomness of the wind power and photovoltaic power

In this study, an improved method of optimal sizing method for a hybrid-energy microgrid (HEM) is proposed, simultaneously considering the impact of correlation and randomness of the wind power and photovoltaic (PV) power on HEM's sizing. The proposed optimal sizing method is based on the following steps: firstly, in order to obtain a large amount of data for the wind power and PV power in the planned area, a combined method which includes Kendall rank correlation coefficient, non-parametric estimation, Copula theory and Monte Carlo is proposed to generate the joint probability density function of the wind power and PV power and to generate an amount of data. Then, while guaranteeing reliable system operation of energy supply, the optimal sizing objective function with a minimum of operation cost, investment cost and pollution gas treatment cost is established based on the scenario-based approach. Finally, a case study of HEM is presented to verify the advantages of the proposed optimal sizing method.

Frequency and voltage control of microgrid with high WECS penetration during wind gusts using superconducting magnetic energy storage

The intermittent behavior of wind power generation results in a fast variation of both frequency and voltage magnitudes of isolated microgrids with high wind power penetration. In this paper, a hybrid energy microgrid with wind energy conversion system (WECS) and diesel synchronous generators are analyzed during wind gust conditions. Superconducting magnetic energy storage (SMES) is connected at the same node of the WECS to mitigate the intermittent wind power generation. A developed fuzzy logic controller has been applied to achieve active power sharing. The damping of voltage fluctuation depends on SMES reactive power, which is controlled by a voltage source converter. The studied microgrid comprises 33 nodes, two diesel SGs, and two WECSs of squirrel cage induction generator type at 30% penetration level. The results demonstrate the effectiveness of the proposed control strategy to mitigate the frequency fluctuations during the wind speed gusts by smoothing power output from WECSs/SMES system. Moreover, voltage control is achieved by injecting reactive power from the SMES system. All simulations are performed by MATLAB/Simulink package.

Hybrid microgrid for microfinance institutions in rural areas – A field demonstration in West Africa

We present a hybrid energy microgrid optimization model for a microbank in a remote rural residential area. The model is based on the use of renewable (wind turbines & solar photovoltaic (PV)) and conventional (gasoline generators) energy sources and battery storage systems. We conducted a detailed assessment of a typical microbank’s load, residential loads and energy resources in a village called Ajasse-Ipo in Kwara State, Nigeria. We performed the modeling of a hybrid microgrid system, followed by an economic analysis and sensitivity analysis to optimize the hybrid system design. We performed simulations based on the energy resources available (solar PV, wind, gasoline generator & battery energy storage system) to satisfy the energy demands of the microbank, while the excess energy was supplied to meet the demand of the community loads, i.e. water pumping machine and rural home lighting. The results obtained showed that the hybrid system comprising the solar PV/battery/diesel was most techno-economically viable with a Net Present Cost (NPC) and Cost of Energy (COE) of $468,914 and 0.667$/kWh, respectively. Comparing these results with those obtained using analytical methods, the solar PV, battery and converter sizes obtained were slightly higher than the optimal system configurations as produced by HOMER. The proposed hybrid energy system also allowed to achieve almost 50% reductions in CO2, CO, unburned hydrocarbons, particulate matter, SO2 & NO2. The system can be applicable for other rural regions in the developing countries with similar environmental conditions.

Fuzzy expert system for management of smart hybrid energy microgrid

This paper proposes a fuzzy expert system for demand-side management, management of renewable energy sources, and electrical energy storage for smart households and microgrids. The proposed fuzzy expert system is used for automatic decision making regarding energy management in smart microgrids containing renewable sources, storage systems, and controllable loads. The fuzzy expert system optimizes energy consumption and storage in order to utilize renewable energy and maximize the financial gain of a microgrid. In order to enable energy management, the fuzzy expert system uses insolation, price of electrical energy, temperature, wind speed, and power of the controllable and uncontrollable loads as input variables. These input data can be directly measured, imported from grid measurements, or predicted using any data prediction method. This paper presents fuzzification of input variables, defines a set of rules of the expert system, and presents defuzzification of outputs. The outputs of the expert system are decisions, i.e., answers to the question of how to manage energy production and consumption in a microgrid. Three outputs are defined to decide about produced energy, controllable loads, and own consumption. The first output is used to store, sell, or consume produced energy. The second output is used to manage the controllable load. The third output shows how to supply own consumption of the prosumer. The expert system is tested on hourly values of input variables in a single day in Serbia. The proposed approach is compared with other available approaches in order to validate the results.

Optimal operation of a hybrid-energy microgrid with energy storage system

In this paper, a day-ahead profit-maximizing energy management scheme for a grid-tied microgrid operation is proposed. The microgrid contains various types of distributed energy resources (DERs) and an inverter-interfaced battery-bank storage system. The average of day-ahead hourly forecasted data for loads, wind speed, and solar radiation are inputted into the framework of energy management (EMF). To optimize the microgrid performance, EMF determines the hourly dispatch of reactive and active power for each DER. Also, it specifies the discharging and charging times of the energy storage system and the onload tap changer position setting of the transformer connected to the main grid. The main aim is to maximize the revenue of microgrid meeting all technical limitations. The main grid can sell/buy reactive and active powers to/from the microgrid with a variable daily energy price of the market. A collective rule base-BAT algorithm is implemented as a solver of the energy management optimization problem for a grid-tided microgrid. Furthermore, the ability of the suggested EMF is proved in comparison with recent approaches.

Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration

The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.

Triple-objective optimal sizing based on dynamic strategy for an islanded hybrid energy microgrid

ABSTRACTA triple-objective optimal sizing method based on a dynamic strategy is presented for an islanded hybrid energy microgrid, consisting of wind turbine, solar photovoltaic, battery energy storage system and diesel generator. The dynamic strategy is given based on a dynamic complementary coordination between two different master-slave control modes for maximum renewable energy utilization. Combined with the proposed strategy, NSGA-II-based optimization program is applied to the sizing optimization problem with triple different objectives including the minimization of annualized system cost, the minimization of loss of power supply probability and the maximization of utilization ratio of renewable energy generation. The sizing results and the proposed strategy are both compared and analyzed to validate the proposed method in a real case of an islanded hybrid energy microgrid on Dong’ao Island, China.

Dynamic economic dispatch of a hybrid energy microgrid considering building based virtual energy storage system

The increasing complexities of hybrid energy Microgrid (H-Microgrid) integrated with renewable generations, dispatchable distribution generators (DGs) and low-carbon buildings require more intelligent dispatch method. The building sector occupies the main body of the energy consumption, which represents a major potential contributor for reducing the daily operating cost of the H-Microgrid. In this paper, a building based virtual energy storage system (VESS) model was developed by utilizing the heat storage capability of the building. Then, a dynamic economic dispatch (DED) model of the H-Microgrid considering the VESS was developed. Finally, the VESS was integrated into the DED model of the H-Microgrid for daily operating cost reduction. The indoor temperature of the building was adjusted within the customer temperature comfort range to manage the charging/discharging power of the VESS. Numerical studies demonstrate that the proposed DED method can make full use of the available capacity of VESS to reduce the daily operating cost, and guarantee the customer temperature comfort level at the same time.

An Optimal Scheduling Model for a Hybrid Energy Microgrid Considering Building Based Virtual Energy Storage System

An optimal scheduling model for a hybrid energy microgrid considering the building based virtual energy storage system (VSS) is developed in this paper. The VSS model is developed by utilizing the building thermal equilibrium equation taking the heat storage characteristics of building into consideration. Firstly, mathematical models of various energy systems and VSS in the hybrid energy microgrid are developed. Then, an optimal scheduling model is developed to minimize the operation costs of the microgrid. Numerical studies demonstrate that the proposed optimal scheduling model can provide the microgrid with an effective and economical scheduling scheme and reduce the operation costs.

Modeling and Testing of Hybrid Energy Microgrid with Wind Turbine and Photovoltaic Power

Modeling of the wind and PV hybrid microgrid is carried out by PSCAD/EMTDC. The model includes direct-drive wind power generator, Single-stage photovoltaic power generation system and storage battery. Simulate and analyze the operating characteristics of the microgrid running in grid-connected and islanding mode, which take into account the actual wind speed and light intensity. The simulation results show that the battery is able to regulate the voltage of the point of common coupling and smooth the power fluctuation of wind generator and PV generation system in the grid-connected mode. The microgrid can isolate itself from the grid in a rapid and seamless fashion when the battery adopting P/V and Q/f control strategy based on the droop characteristics.