Industrial Microgrid Research Articles

Nonlinear modeling of a Free Piston Stirling Engine combined with a Permanent Magnet Linear Synchronous Machine

Converting thermal energy to electricity (from renewable or nonrenewable sources) is one of the most required energy conversions around the world. The waste heat of industrial plants and microgrids should also be recovered in the most efficient way. Stirling engines are one of those systems with the highest possible theoretical efficiency and capability of working with different thermal energy sources that have been industrialized. In the following study, a combined model of a β-type Free Piston Stirling Engine (FPSE) and a Permanent Magnet Linear Synchronous Machine (PMLSM) has been proposed. First, both linear and nonlinear equations of the FPSE were extracted and implemented in MATLAB Simulink®. The results were compared and validated with the experimental results. In the second step, an independent model of a standard PMLSM was also implemented in MATLAB Simulink®. At the final step, state equations of the combined system of an FPSE with a PMLSM were developed. These equations were implemented in MATLAB Simulink® and the combined system was controlled. This combined model is a key tool in order to find the optimized control of the combined system (FPSE-PMLSM). This is the main interest of the following study. This system combination will be tested experimentally in future studies.

Impact of microgrid operation on performance of radial distribution system

Voltage profile and real power loss are the criteria in determining performance of Radial Distribution System (RDS). Presence of Distributed Generators in RDS is assessed by ‘Penetration Ratio’. The use of PR fails in the analysis of the implications of the presence of a Microgrid on RDS as it is zero in islanded mode and sometimes in grid-connected mode. An attempt has been made to introduce a new term ‘Relief Factor’ to overcome this lacuna. This Factor is evaluated by developing an algorithm based on power flow analysis using Backward Forward Sweep method. The developed algorithm is tested on a 34 bus RDS by integration of a two-shift industrial Microgrid. The power flow analysis is run for 24 snapshots of the day. Relief Factor is found to be suitable to analyze the impact of a Microgrid on the performance of RDS in both the modes of Microgrid operation viz. grid-connected mode and islanded mode.

Smoothing Tie-Line Power Fluctuations for Industrial Microgrids by Demand Side Control: An Output Regulation Approach

This paper investigates the problem of how to effectively smooth the short-term tie-line power fluctuations for grid-connected industrial microgrids (IMGs) from demand side. A wide-area closed-loop control architecture is proposed by directly and continuously modulating load power consumption, e.g., the aluminum electrolysis load. To optimally design the load smoothing controllers, an output regulation approach combined with LQ optimal control is developed. In particular, dominant frequencies of wind power fluctuations are analyzed and incorporated into the exogenous system that models time-varying disturbances. Simulations are conducted for a real industrial microgrid in the Inner Mongolia, China, to validate the practical feasibility and effectiveness of the proposed smoothing control strategy. It is demonstrated that the demand side control based on output regulation is able to achieve not only zero steady error in rejecting the time-varying wind power disturbance but also guarantee the satisfactory dynamic performance of modulated loads for the grid-connected IMG.

Communication system architecture of an industrial‐scale microgrid: A case study

The industrial‐scale microgrids are revolutionizing the way commercial and industrial organizations traditionally anticipated to feed their production facilities for meeting up the energy demands. Due to the large volume and a diverse range of heterogeneous electrical components combining together in these microgrids, setting up a proper communication system becomes challenging. Along many others, the authors have also found it challenging to properly set up a communication system during the deployment of industrial‐scale experimental microgrid at PrInCE Lab. This paper is aimed at providing the guidelines for the research and industrial communities outlining the set of communication challenges along the way and highlighting their possible remedies with the intention to make it possible even for the nontechnical industrial staff handling these issues with ease while setting up their own industrial microgrids.

Nonlinear optimal control for DC industrial microgrids

ABSTRACTDC industrial microgrids can assure uninterrupted and free-of-perturbations power supply to industrial units. Besides the solution of the related optimal control problem can result in minimisation of electric power consumption by such units. In this article, the problem of nonlinear optimal (H-infinity) control for industrial microgrids is treated. The dynamic model of an indicative microgrid that comprises photovoltaic units, batteries and supercapacitors is considered. This model undergoes approximate linearisation around a temporary operating point that is recomputed at each time-step of the control method. The linearisation relies on Taylor series expansion and on the computation of the associated Jacobian matrices. For the linearised state-space model of the system, a stabilising optimal (H-infinity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. Finally, to implement state estimation-based control without the need to measure the entire state vector of the DC microgrid the H-infinity Kalman Filter is used as a robust state estimator.

Multitimescale Coordinated Adaptive Robust Operation for Industrial Multienergy Microgrids With Load Allocation

Manufactory load allocation can be used as an effective industrial demand response scheme to reduce operating costs for industrial multienergy microgrids (iMEMGs). In addition, combined cooling, heat, and power (CCHP) plants with auxiliary devices can provide low-cost multiple energies for industrial plants. However, uncertain power generation from renewable energy sources impairs the iMEMG's operation, leading to challenges such as increased operating costs and energy supply deficiency. To conquer these challenges, this paper proposes a multitimescale coordinated adaptive robust operation approach where manufactory load allocation and iMEMG operation are optimally coordinated on different timescales. In the weekly scheduling stage, industrial loads and CCHP units are scheduled for the following week and the hourly iMEMG operation is optimized within the week. Besides, this paper applies an adaptive robust optimization method where the uncertain renewable power generation is fully addressed. The proposed approach is tested on an iMEMG with various industrial manufactories, and it is compared with conventional methods. The simulation results indicate that compared to the conventional ones, the proposed approach can guarantee a robustly optimal operation solution for the iMEMG against any uncertainty realization.

Long-Term Planning of Connected Industrial Microgrids: A Game Theoretical Approach Including Daily Peer-to-Microgrid Exchanges

In this paper, a tool for the long-term (LT) planning, i.e., up to 20 years, of industrial microgrids (IMGs) connected to the distribution network and made of industrial consumers, prosumers, and of the distribution system operator (DSO), is proposed. The DSO assumes here the new role of microgrid energy manager. In order to realize the proper choice of LT investments (e.g., in renewable energy system and energy storage system), a short-term (ST) energy management is performed each day of the planning period. For that purpose, a new system of daily operation including industrial load management and allowing peer-to-microgrid as well as external energy exchanges is implemented. The LT investments and ST operational decisions are coupled via two game theoretical frameworks, which also allow the modeling of the different, even conflicting, objectives of the stakeholders. Different LT and ST pricing schemes are also considered in order to provide general advices concerning the creation of new IMGs. The developed tool is tested on a virtual IMG and the technical and economical outputs are presented.

A New Time-Decoupled Framework for PEVs Charging and Scheduling in Industrial Microgrids

Solving the optimal power flow (OPF) in industrial microgrids (IMGs) in presence of plug-in electric vehicles (PEVs) changes the structure of problem to a complex dynamic OPF (DOPF). The complication is due to energy and time related constraints of PEVs that requires the complex non-linear time-coupled DOPF problem to be solved over a long period of few hours (e.g., 24-h). This paper presents a novel time-decoupled framework for solving the generation scheduling problem in IMGs by relaxing the time correlated constraints of the DOPF. The relaxation is mathematically achieved by replacing the time-coupled constraints with their corresponding long term time averages. This will resolve the time coupling property of DOPF and results in a simpler solution approach. The relaxed DOPF problem can be solved in independent time periods while considering other constraints such as PEVs and security constraints of OPF as well as factories constraints. To examine the effectiveness of the proposed method, different simulation scenarios have been applied to an 18-bus IMG consisting of PEVs and 12 factories with electrical and thermal loads as well as combined heat and power systems.

Optimal Energy Management and Control of an Industrial Microgrid With Plug-in Electric Vehicles

Optimal Energy Management and Control of an Industrial Microgrid With Plug-in Electric Vehicles

Economically viable emissions reductions through industrial microgrid optimisation

The optimisation of systems where engaging with a high volume of data is a critical task in engineering and information technology. This paper explores the use of optimisation tool in energy systems, that can be utilised in combination with the optimisation of communication systems. This paper examines the environmental impact of implementing economically competitive microgrids in industrial projects and offers a range of microgrid configurations that display notable environmental improvements when compared to the benchmark. This benchmark is a proposed AU$31.1m substation infrastructure upgrade to supply a hypothetical 60 MW industrial load through the centralised electricity network in Western Australia. With the assistance of HOMER (Hybrid Optimisation of Multiple Energy Resources) modelling software and industry data, a range of distributed energy resource configurations were modelled over a 25-year project life. Evaluations found that across economically viable topologies, an average reduction of 52% on CO2 gas emissions was observed. Mean initial capital expenses for featured microgrid systems were observed to be more than 6 times the benchmark, however mean emissions reductions were observed at 439.76 T/yr for every dollar invested. A set of featured architectures are presented utilizing combined heat and power equipped gas turbine, diesel generator, wind farm and vanadium redox flow battery bank.

Simulation planning of power supply capacity: an approach to optimal industrial microgrid operation with carbon emission permits

ABSTRACTMicrogrids integrated with distributed generation provide energy intensive enterprises (EIEs) with a solution to cut down their total system costs. However, unreasonable capacity allocation of power supply in industrial microgrid may result in capacity shortage or excess, thus leading to uneconomical solutions. Considering carbon emission permits and renewable energy access on demand side, this paper analyses and evaluates the long-term impacts of power supply capacity on economic benefits and carbon emission. The power suppliers consist of industrial self-generation, wind power generation and power grid. A HOMER software based industrial microgrid model is designed, and time series simulation of the model for a cycle of 10 years is performed to provide numerical analysis. The simulation results with sensitivity analysis show that optimal capacity planning of power supply can lead to considerable economical and ecological benefits under carbon emission permits; besides, it can also be conducive to peak load shedding for power grid.

Hardware-in-the-Loop Validation of Energy Management Systems for Microgrids: A Short Overview and a Case Study

The energy management system (EMS) of a microgrid often presents a complex structure and a large number of control functions, which must be validated to ensure a reliable and optimal operation of the microgrid. Control system validation is typically performed by using hardware-in-the-loop (HIL) architectures in which the microgrid is simulated in real time and interfaced with the actual system under test. The simulation must ensure both an accurate representation of the microgrid and a reliable replica of the field communication of the EMS with all the control devices. In this paper, an overview of the various HIL architectures proposed in the literature is firstly outlined. Then, an HIL validation facility is presented and used to validate the EMS of an industrial microgrid. Finally, some results of the validation tests are reported to give evidence of the effectiveness of the proposed facility. In the proposed architecture, the soft real-time digital simulator of the microgrid is interfaced with the actual EMS using the same communication system and protocol as on the field. The main advantages of the proposed testing facility are: (i) the use of commercial PCs and the absence of dedicated interface modules, resulting in inexpensive hardware components; (ii) the capability to validate both control and communication functions of the EMS; (iii) the applicability to microgrids of different types (industrial, commercial, residential), as well as of various dimensions, including large microgrids; (iv) the easiness in changing the microgrid and the EMS under validation by only software modifications of the simulator tasks and of the exchange interface. As drawbacks, the proposed testing facility presents the need to adapt the software interface between EMS and the field to the EMS under test and the possibility of testing only the EMS functions and not fast-acting local controllers of the microgrid such as the protection systems.

Data center holistic demand response algorithm to smooth microgrid tie-line power fluctuation

With the rapid development of cloud computing, artificial intelligence technologies and big data applications, data centers have become widely deployed. High density IT equipment in data centers consumes a lot of electrical power, and makes data center a hungry monster of energy consumption. To solve this problem, renewable energy is increasingly integrated into data center power provisioning systems. Compared to the traditional power supply methods, renewable energy has its unique characteristics, such as intermittency and randomness. When renewable energy supplies power to the data center industrial park, this kind of power supply not only has negative effects on the normal operation of precision equipment, such as CPU/GPU chips and hard disk, in data center, but it would also impact the stability of the utility power grids operation. To solve this problem, this paper presents a novel tie-line power fluctuation smoothing algorithm with consideration of data center’s holistic demand response. The contributions of this paper are: (1) overcoming the limitations of treating IT load as uncontrollable workload in the traditional demand response research, we design a data center resource scheduling model to realize IT load demand response controllability; (2) two novel mechanisms are proposed: (i) the server cluster workload scheduling method with time shift mechanism, and (ii) the data center UPS (Uninterruptible Power Supply) energy storage dynamic response mechanism. (3) Combining these two mechanisms as holistic demand response of data center, we present a tie-line power fluctuation smoothing algorithm to improve power supply reliability, which is beneficial to both the high density and precision IT equipment in the data center and the utility power grid. In the experiments, the results show that the new algorithm can effectively regulate the tie-line power fluctuations under different server cluster utilization ranges and scenarios of large-scale penetration of distributed renewable energy scenarios. The new algorithm is hence able to contribute beneficially to the reliability and stability of intelligent industrial park micro-grid and utility power grids.

Investigation of harmonic distortions in photovoltaic integrated industrial microgrid

Due to the abundance of power electronic appliances, harmonic distortion has become one of the growing power quality concerns in recent years. Harmonic distortion is also caused by the nonlinearity of other power equipment such as transformers and rotating machines. Power systems, rich in harmonics, offer poor power factor and hence low efficiency operation. Due to the large concentration of nonlinear loads such as motor drives, investigation of harmonic distortion in industrial systems is getting special attention. Widespread integration of solar Photovoltaic (PV) systems into distribution systems brings additional challenges to the existing power quality scenario. Inclusion of solar PV systems in an industrial microgrid equipped with a large share of motor drives results in a significant increase in existing Total Harmonic Distortion (THD). To better understand the above issues, a methodology is proposed in this paper to identify the most suitable PV placement topology between the two schemes (namely, centralized and distributed) in terms of THD performance. Also, a technique is developed to estimate the maximum PV penetration level by maintaining the THD within the given acceptable limit. The proposed methodologies are applied to an industrial distribution system under various operating conditions.

Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems

This paper presents a new framework for optimizing the operation of Industrial MicroGrids (IMG). The proposed framework consists of three levels. At the first level, a Profit Based Security Constrained Unit Commitment (PB-SCUC) is solved in order to minimize the total expected cost of IMG via maximizing the IMG revenue by transacting in the day-ahead power market and optimizing the scheduling of the units. In this paper, the tendency of IMG for participating in the day-ahead power market is modelled as a quadric function. At the second level, a Security Constrained Unit Commitment is solved at the upper grid for minimizing the upper grid operation and guaranteeing its security. At this level, the accepted IMG bids in the day-ahead power market would be determined. Finally, at the third level, the IMG operator must settle its units on the basis of its accepted bids. Therefore, a rescheduling problem is solved in the third level. Notably, Renewable Energy Sources (RESs), Combined Heat and Power (CHP) units, thermal and electrical storage systems are considered in the IMG. As the RESs and day-ahead market price have stochastic behaviours, their uncertainty is taken into account by implementing stochastic programming. Further, different cases for grid-connected and island modes of IMG are discussed, and the advantages of utilizing RES and storage systems are given. The simulation results are provided based on the IEEE 18-bus test system for IMG and IEEE 30-bus test system for the upper grid.

Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

This paper proposes an efficient energy management system (EMS) for industrial microgrids (MGs). Many industries deploy large pumps for their processes. Oftentimes, such pumps are operated during hours of peak electricity prices. A lot of industries use a mix of captive generation and imported utility electricity to meet their energy requirements. The MG considered in this paper includes diesel generators, battery energy storage systems, renewable energy sources, flexible loads, and interruptible loads. Pump loads found in shipyard dry docks are modelled as exemplar flexible industrial loads. The proposed EMS has a two-stage architecture. An optimal MG scheduling problem including pump scheduling and curtailment of interruptible loads (ILs) is formulated and solved in the first stage. An optimal power flow problem is solved in the second stage to verify the feasibility of the MG schedule with the network constraints. An iterative procedure is used to coordinate the two EMS stages. Multiple case studies are used to demonstrate the utility of the proposed EMS. The case studies highlight the efficacy of load management strategies such as pump scheduling and curtailment of ILs in reducing the total electricity cost of the MG.

Protection Systems and Earthing Schemes for Microgrids: Main Aspects and Fault Analysis

AbstractThe content of this paper aims to assist in the development and implementation of microgrids by addressing the challenges and possible solutions for their protection systems. Therefore, an overview of some protection methods available in the literature that can be implemented to ensure a safe and reliable microgrid operation is presented, including the most common protection devices and earthing schemes that can be adopted in low voltage distribution systems. In addition, this paper also presents a brief fault analysis of internal faults at three different locations in an industrial microgrid with centralized and decentralized deployment of energy sources, as well as a short-circuit analysis of symmetric and asymmetric faults at these faulty locations. An approximate method based on the calculation of the equivalent impedance seen from the fault location is used to determine the fault currents. This study is made to observe how microgrids with different configurations perform in the event of internal faults.It is demonstrated in this work that setting a specific protection strategy to allow the microgrid to operate effectively during both operation modes can be problematic and expensive in most situations. With this in mind, additional effort is necessary to engineer and implement new protection approaches that can overcome the limitations of protection systems in future microgrids.

Optimal sizing of an industrial microgrid considering socio‐organisational aspects

An industrial microgrid can be an effective way to introduce a high percentage of renewable power in the electrical energy supply of an industrial park. An optimal sizing process can be employed in the design phase of such a newly developed hybrid power system to assure the power system's technical and economic efficiency. While optimal sizing algorithms have been developed for different types of hybrid power systems, these often treat stand-alone systems and do not consider the socio-organisational drivers for inter-firm energy supply facilities. Here, a techno-economic optimisation is carried out using a genetic algorithm to determine the optimal system configuration of a grid-connected power system. The current development of the project Eiland Zwijnaarde in Ghent provides the basis for a concrete case study. The main results suggest that the optimal configuration consists of a significant share of renewable sources. A cogeneration unit can compensate the renewables' intermittent behaviour and lower the thermal energy cost. Large-scale electrical storage is found not to be profitable under the used control structure. A gradual ingress of firms in the park and the subsequent sloped annual energy demand have a negative effect on the power system's fraction of shared facilities.

Microgrid Architecture Evaluation for Small and Medium Size Industries

AbstractThe content of this paper addresses possible approaches that will eventually allow the development of microgrids for small and medium size industries on a massive scale. Therefore, it addresses in a comprehensive way, the most suitable communication technologies for microgrids in this type of enterprises. Several energy sources that can be implemented in industrial microgrids are also briefly addressed, including generation and storage units frequently adopted for power supply in small scale distribution grids. The overview of communication technologies and energy sources takes into account the financial limitations of small enterprises with the purpose of assisting the study of industrial microgrid architectures. In addition, a case study is presented in order to observe how a centralized and a decentralized deployment of energy sources affect the performance of a small or medium scale industrial microgrid. Since this sector is very important for the development of modern societies, it should make use of the most advanced infrastructures in order to be more sustainable, both environmentally and competitively. The practical limitations applied to industrial microgrids (e.g., lack of standards in the grid codes, some unfit technological performance and amiss system design) shows that the subject presented in this paper deserves much more research and developments. Thus, this work demonstrates the importance of the development of the microgrid for the small and medium-sized enterprises sector.

A Communication-Supported Comprehensive Protection Strategy for Converter-Interfaced Islanded Microgrids

The deployment of distributed generators (DGs) gives rise to several challenges for a microgrid or conventional distribution feeder, regarding control and protection issues. The major ones are: bi-directional flow of power, changes in fault current magnitude, and continuous changes in operational configuration due to both the plug-and-play of DGs and loads, and the intermittency of the renewable DGs. This issue is exacerbated when the microgrid contains several converter-interfaced DGs and operates in the islanded mode of operation. Hence, conventional protection strategies and relaying techniques will no longer be sufficient to protect islanded microgrids against network faults and disturbance conditions. This paper proposes a fast and reliable communication-supported protection strategy for ensuring the safe operation of converter-interfaced islanded microgrids. The strategy is implementable using commercially accessible microprocessor based digital relays, and is applicable for the protection of low voltage islanded microgrids. It provides backup protection to handle communication failures and malfunctions of protective devices. The paper also presents the detailed structural layout of the digital relay, which executes the proposed protection strategy. A number of improvements are proposed to find an alternative method for conventional overcurrent relays to reliably detect small-magnitude fault currents and high impedance faults, commonly encountered in converter-interfaced islanded microgrids. A simple and economical bus protection method is also proposed. Several simulations are conducted on a comprehensive model of a realistic operational industrial microgrid (Goldwind Smart Microgrid System) using PSCAD/EMTDC software environment—for different case studies and fault scenarios—to verify the effectiveness of the present strategy and its digital relay.