Hybrid Petri Nets for Modeling and Analysis of Microgrid Systems

Hybrid Petri nets(HPNs) are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently,many researchers attempt to utilize them to characterize power and energy systems. This work proposes to adopt an HPN to model and analyze a microgrid that consists of green energy sources. A reachability graph for such a model is generated and used to analyze the system properties.

Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

Microgrids are a type of restricted power distribution systems in which electricity is generated,transmitted,and distributed within a small geographic region.They are used to ensure that renewable energy sources are used to their full potential.Microgrids provide further benefits,such as lowering transmission losses and the expenses associated with them.This research compares and contrasts the aims of economic dispatch,emission dispatch,fractional programing based combined economic emission dispatch,and environmental restricted economic dispatch(ECED).A low-voltage microgrid system is investigated for three different scenarios.As a study optimization tool,an innovative,resilient,and strong hybrid swarm-intelligence optimization algorithm is utilised,which is based on combining the properties of the traditional grey-wolf optimiser,sine-cosine algorithm,and crow search algorithm.The employment of a time-of-use energy mar-ket pricing approach instead of a fixed pricing plan resulted in a 15%decrease in gen-eration costs throughout the course of the research.When ECED was assessed with a 15%-20%demand side management based restructured load demand model for the microgrid system,the generation costs were reduced even further.

MAS Based Distributed Automatic Generation Control for Cyber-Physical Microgrid System

The microgrid is a typical cyber-physical microgrid system (CPMS). The physical unconventional distributed generators (DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components, such as the embedded computer and communication network, are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid, the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information (such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system (MAS). Based on the global information from cyber components of CPMS, automatic generation control (AGC) and automatic voltage control (AVC) are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods. © 2014 Chinese Association of Automation.

A Summary of Optimal Methods for the Planning of Stand-alone Microgrid System

This paper describes the characteristics and optimal methods for the planning of stand-alone microgrid system, in order to improve the power supply reliability, increase the coefficient of utilization of renewable energy and reduce the cost of investment and operation. Next, the problems in the optimal planning for a stand-alone microgrid system are summarized, including the unique operational control targets, the flexible combination approaches and the operation strategies of distributed generation energy supply system, and the special requirements of the reliability of power supply quality factor from the different users. And then, centering on the operational control and the advanced energy management strategy, the optimal mathematical models and the solving methods, the reliability assessment approaches and the improvement measures of a stand-alone microgrid system, an overview of the general situation of the recent research at home and abroad and the limitations of the study are summarized. Finally, several problems, existing in the optimal planning of stand-alone microgrid system, to be urgently solved, are put forward.

Modeling and Simulation of a Hybrid Energy Storage System for Residential Grid-Tied Solar Microgrid Systems

Present-day power conversion and conditioning systems focus on transferring energy from a single type of power source into a single type of load or energy storage system (ESS). While these systems can be optimized within their specific topology (e.g. MPPT for solar applications and BMS for batteries), the topologies are not easily adapted to accept a wide range of power flow operating conditions. With a hybrid approach to energy storage and power flow, a system can be designed to operate at its most advantageous point, given the operating conditions. Based on the load demand, the system can select the optimal power source and ESS. This paper will investigate the feasibility of combining two types of power sources (main utility grid and photovoltaics (PV)) along with two types of ESS (ultra-capacitors and batteries). The simulation results will show the impact of a hybrid ESS on a grid-tied residential microgrid system performance under various operating scenarios.

Simulating Annealing PLL for Autonomous Microgrid Systems

The Phase Locked Loop controller parameters are the key-point that affects the dynamic performance of the autonomous microgrid. They have to be optimally tuned to guarantee enhanced overall system stability. In this paper, two-microgrid plant with their associate PWM inverter connected to the ac main grid and the load is used as an example to demonstrate the capabilities of the proposed system. The Phase Locked Loop controller is designed and tuned using the Simulating Annealing algorithm. This algorithm is used to select the Phase Locked Loop PI controller gains with optimal percentage overshoot, rise time and settling time. The controller is tested during the transition between grid-connected and autonomous operation and in reverse order. The controller is compared with Ziegler and Nichols P and PI controllers. It shows the effectiveness and the extraordinary control response of the proposed control technique with respect to percentage overshoot, rise time and settling time control parameters compared to the conventional one.

Optimal Design of Grid-Connected Microgrid System for Cold Chain Logistics Centre in China

The growing interest in energy conservation has inspired companies to seek alternatives to highly polluting fuel electricity generation. This study designed an optimised solar wind power generation system to fulfil the energy requirement of a cold chain logistics centre. This study first conducted a thorough analysis of the clarity indicators and daily temperature positions of the cold chain logistics centre, determined the average daily electricity demand, and proposed an effective design scheme. The energy simulation software, RETScreen 8.0, was used to determine the scale of solar photovoltaic and wind power projects that meet the expected energy needs of the cold chain logistics centre. The results indicated that the estimated annual total energy demand was 833689.2 kWh. The annual power generation of 6 kW from solar photovoltaic projects and 150 kW from wind power projects was found to be enough to meet the expected electricity demand. Solar photovoltaic power generation and wind power generation account for 2.44% and 97.56%, respectively. The hybrid energy system achieved a 96.6% reduction in carbon emissions and provides a reasonable payback period of 6.1 years and an electricity generation of 904368.674 kWh per year. The feasibility of the project and the calculated period of investment return are very reasonable. Therefore, this hybrid renewable energy system provides reliable power by combining energy sources.

Optimal design of hybrid renewable-energy microgrid system:a techno-economic-environment-social-reliability perspective

The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass generator,a battery bank,a diesel generator and an electric vehicle.The optimal model selection is based on technical,economic,environmental,social and reliability parameters.A novel spoonbill swarm optimization algorithm is proposed to select the best hybrid MG system.The optimization results are compared with particle swarm optimization,the genetic algorithm and the grasshopper optimization algorithm.The number or size of components of the optimized MG system is 215 PV modules,92 kW of wind turbine generation,25 kW of biomass generation,267 batteries,22 kW of electric vehicles and 30 kW of diesel generation.The optimized system was selected based on technical factors such as renewable dispersion(93.5%),the duty factor(5.85)and excess energy(15975 kWh/year)as well as eco-nomic considerations including the net present cost(Rs.34686622)and the cost of energy(9.3 Rs./kWh).Furthermore,environ-mental factors such as carbon emissions(396348 kg/year)and atmospheric particulate matter(22.686 kg/year);social factors such as the human progress index(0.68411),the employment generation factor(0.0389)and local employment generation(15.64643);and reliability parameters including loss of power supply probability(0.01%)and availability index(99.99%)were considered during the selection process.The spoonbill swarm optimization algorithm has reduced the convergence time by 1.2 times and decreased the number of iterations by 0.83 times compared with other algorithms.The performance of the MG system is validated in the MATLAB®environment.The results show that the MG system is the optimal system considering technical,economic,environmental,social and reliability parameters.Additionally,the spoonbill swarm optimization algorithm is found to be more efficient than the other algo-rithms in terms of iteration time and convergence time.

Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission

To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day.To mitigate this challenge,an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system(HBESS)operating within a microgrid is proposed,with a focus on efficient state-of-charge(SoC)planning to minimize microgrid expenses.The SoC ranges of the battery energy storage(BES)are determined in the day-ahead stage.Concurrently,the power generated by fuel cells and consumed by electrolysis device are optimized.This is followed by the intraday stage,where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized.To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage,we proposed an outer-inner column-and-constraint generation algorithm(outer-inner-CCG).Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.

Research on Distributed Coordination Control Method for Microgrid System Based on Finite-time Event-triggered Consensus Algorithm

Microgrids are networked control systems with multiple distributed generators(DGs).Microgrids are associated with many problems,such as communication delays,high sampling rates,and frequent controller updates,which make it challenging to realize coordination control among the DGs.Therefore,finite-time consensus algorithms and event-triggered control methods are combined to propose a distributed coordination control method for microgrid systems.The DG in the microgrid system serves as an agent node in the control network,and a distributed secondary controller is designed using finite-time consensus algorithm,such that the frequency and voltage restoration control has a faster convergence time and better anti-interference performance.The event-triggered function was designed based on the state information of the agents.The controller exchanges the state information at the trigger instants.System stability is analyzed using the Lyapunov stability theory,and it is verified that the controller cannot exhibit the Zeno phenomenon in the event-triggered process.A simulation platform was developed in Matlab/Simulink to verify that the proposed control method can effectively reduce the frequency of controller updates during communication delays and the burden on the communication network.

Coordinated Chance-constrained Optimization of Multi-energy Microgrid System for Balancing Operation Efficiency and Quality-of-service

To enhance the flexible interactions among multiple energy carriers,i.e.,electricity,thermal power and gas,a coordinated programming method for multi-energy microgrid(MEMG)system is proposed.Various energy requirements for both residential and parking loads are managed simultaneously,i.e.,electric and thermal loads for residence,and charging power and gas filling requirements for parking vehicles.The proposed model is formulated as a two-stage joint chance-constrained programming,where the first stage is a day-ahead operation problem that provides the hourly generation,conversion,and storage towards the minimization of operation cost considering the forecasting error of photovoltaic output and load demand.Meanwhile,the second stage is an on-line scheduling which adjusts the energy scheme in hourly time-scale considering the uncertainty.Simulations have demonstrated the validity of the proposed method,i.e.,collecting the flexibilities of thermal system,gas system,and parking vehicles to facilitate the operation of electrical networks.Sensitivity analysis shows that the proposed scheme can achieve a compromise between the operation efficiency and service quality.

Distributed Virtual Inertia Based Control of Multiple Photovoltaic Systems in Autonomous Microgrid

The large inertia of a traditional power system slows down system's frequency response but also allows decent time for controlling the system.Since an autonomous renewable microgrid usually has much smaller inertia,the control system must be very fast and accurate to fight against the small inertia and uncertainties.To reduce the demanding requirements on control,this paper proposes to increase the inertia of photovoltaic(PV) system through inertia emulation.The inertia emulation is realized by controlling the charging/discharging of the direct current(DC)-link capacitor over a certain range and adjusting the PV generation when it is feasible and/or necessary.By well designing the inertia,the DC-link capacitor parameters and the control range,the negative impact of inertia emulation on energy efficiency can be reduced.The proposed algorithm can be integrated with distributed generation setting algorithms to improve dynamic performance and lower implementation requirements.Simulation studies demonstrate the effectiveness of the proposed solution.

Distributed Cooperative Control of Battery Energy Storage Systems in DC Microgrids

The control of battery energy storage systems(BESSs)plays an important role in the management of microgrids.In this paper,the problem of balancing the state-ofcharge(SoC)of the networked battery units in a BESS while meeting the total charging/discharging power requirement is formulated and solved as a distributed control problem.Conditions on the communication topology among the battery units are established under which a control law is designed for each battery unit to solve the control problem based on distributed average reference power estimators and distributed average unit state estimators.Two types of estimators are proposed.One achieves asymptotic estimation and the other achieves finite time estimation.We show that,under the proposed control laws,SoC balancing of all battery units is achieved and the total charging/discharging power of the BESS tracks the desired power.A simulation example is shown to verify the theoretical results.

Optimal configuration for photovoltaic storage system capacity in 5G base station microgrids

Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.

Reliability Assessment of a Cyber Physical Microgrid System in Island Mode

As cyber physical systems,microgrids(MGs),with distributed generations and energy management systems,can improve the reliability of power supply for customers in MGs.To quantify the reliability of isolated MGs,a cyber-physical assessment model is proposed.In this model,the circuit breakers and distributed energy resources are treated as the coupling elements between the cyber system and physical system,where the circuit breakers are uniquely modelled by using the Markov process theory based on the indirect interdependencies between cyber physical elements.For the cyber system,the reliability model of communication networks is formulated based on the link connectivity evaluation method.For the physical system,a system state generating method is presented to account for the optimal operation strategy,which considers the influence of the optimization strategy on the failure consequence analysis.With the proposed cyber and physical reliability models,the sequential Monte Carlo(SMC)simulation method is adopted to assess the reliability of islanded MGs.Simulations are carried out on a test system,and results verify the feasibility and effectiveness of proposed assessment method.Furthermore,one application of the proposed method is on the parameter setting of the cyber system,in terms of enhancing MGs reliability.

Three-phase Four-wire Interlinking Converter with Enhanced Power Quality Improvement in Microgrid Systems

This paper presents an advanced three-phase four-wire interlinking niicrogrid system with an improved harmonics reduction feature.Due to their robustness and simplicity features,time-domain second-order notch-filter equivalent techniques have drawn a great deal of research attention.However,the drawbacks of non-satisfactory harmonics rejection characteristics and dynamic response limits their applications.In this context,this paper proposes an advanced control system with an enhanced harmonics reduction feature for microgrid applications.The proposed control system exhibits a superior harmonics reduction feature and better dynamic response than the conventional notch-filter based techniques.In addition,a control scheme is developed for a three-phase power system application which presents higher accuracy in compensating both balanced and unbalanced harmonics.The performance of the proposed system is validated through simulations and tested on the hardware of a real microgrid system.From the results,it is evident that the proposed approach provides excellent performance in terms of harmonics reduction in microgrid systems.

Energy management for multi-microgrid system based on model predictive control

To reduce the computation complexity of the optimization algorithm used in energy management of a multi-microgrid system, an energy optimization management method based on model predictive control is presented. The idea of decomposition and coordination is adopted to achieve the balance between power supply and user demand, and the power supply cost is minimized by coordinating surplus energy in the multi-microgrid system. The energy management model and energy optimization problem are established according to the power flow characteristics of microgrids. A dual decomposition approach is imposed to decompose the optimization problem into two parts, and a distributed predictive control algorithm based on global optimization is introduced to achieve the optimal solution by iteration and coordination. The proposed method has been verified by simulation, and simulation results show that the proposed method provides the demanded energy to consumers in real time, and improves renewable energy efficiency. In addition, the proposed algorithm has been compared with the particle swarm optimization(PSO) algorithm. The results show that compared with PSO, the proposed method has better performance, faster convergence, and significantly higher efficiency.

Sizing battery storage for islanded microgrid systems to enhance robustness against attacks on energy sources

Power system security against attacks is drawing increasing attention in recent years.Battery energy storage systems(BESSs)are effective in providing emergency support.Although the benefits of BESSs have been extensively studied earlier to improve the system economics,their role in enhancing the system robustness in overcoming attacks has not been adequately investigated This paper addresses the gap by proposing a new battery storage sizing algorithm for microgrids to limit load shedding when the energy sources are attacked.Four participants are considered in a framework involving interactions between a robustness-oriented economic dispatch model and a bilevel attacker-defender model.The proposed method is tested with the data from a microgrid system in Kasabonika Lake of Canada.Comprehensive case studies are carried out to demonstrate the effectiveness and merits of the proposed approach.

Research and practice of designing hydro/ photovoltaic hybrid power system in microgrid

Small-hydro power station is often used in remote areas beside a river,but it doesn't match electricity demand so well,especially in dry seasons. A photovoltaic (PV) system with battery is a suitable option to complement the electricity gap. In this paper,a new structure of megawatt-class PV system integrating battery at DC-bus (DC: direct current) is proposed to be used in hydro/PV hybrid power system,and 4 main designing considerations and several key equipments are discussed. In 2011,a 2 MWp PV station with the proposed structure was built up in Yushu,China. From stability analysis,the station shows a strong stability under load cut-in/off and solar irradiance's fluctuation.

Distributed Intelligent Microgrid Control Using Multi-Agent Systems

In the future, the individual entities of microgrids such as distributed generators and smart loads may need to determine their power generation or consumption in more economic ways. Intelligent agents can help the decision-making procedure of the entities by intelligent algorithms and state-of-the-art communication with central controller and other local agents. This paper presents the development of atable-top microgrid control system using multi-agent systems and also the demonstration of demand response programs during power shortage. In our table-top system, agents are implemented using microcontrollers and Zigbee wireless communication technology is applied for efficient data communication in the multi-agent system. The power system models of distributed generators and loads are implemented in the real-time simulator using Opal-RT system. The whole test system that includes real-time system simulation and agent hardware is implemented in the hardware-in-the-loop simulation framework. The performance of the developed system is tested for emergency demand response cases.