Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

A digital twin model-based approach to cost optimization of residential community microgrids

This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.

Attack-resilient control for converter-based DC microgrids

In light of the growing integration of renewable energy sources in power systems,the adoption of DC microgrids has become increasingly popular,due to its simple structure,having no frequency,power factor concerns.However,the dependence of DC microgrids on cyber-networks also makes them susceptible to cyber-attacks.Potential cyberattacks can disrupt power system facilities and result in significant economic and loss of life.To address this concern,this paper presents an attack-resilient control strategy for microgrids to ensure voltage regulation and power sharing with stable operation under cyber-attack on the actuators.This paper first formulates the cyber-security problem considering a distributed generation based microgrid using the converter model,after which an attack-resilient control is proposed to eliminate the actuator attack impact on the system.Steady state analysis and root locus validation illustrate the feasibility of the proposed method.The effectiveness of the proposed control scheme is demonstrated through simulation results.

Smart Python Agents for Microgrids

Microgrids are revolutionary power systems that interconnect a mix of renewable power generation, load, storage systems, and inverters in a small-scale grid network. Operating microgrids while maintaining a consistent grid voltage and frequency during the islanding and disruption of renewables has been a challenging research problem. In this paper, a preliminary microgrid agent implementation is presented using SPADE (Smart Python Agent Development Environment) as a powerful development framework that has been used extensively in many application domains. Agents autonomously managed and operated microgrid individual components. A multiagent microgrid system was modeled to seamlessly operate and optimize energy balance by coordinating the actions of agents. Agents were built to forecast energy demand and solar power and coordinate to balance generation with load while maintaining optimal power flow and adequate network voltage and frequency.

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.

Distributed Secondary Control of AC Microgrids With External Disturbances and Directed Communication Topologies:A Full-Order Sliding-Mode Approach

This paper addresses the problem of distributed secondary control for islanded AC microgrids with external disturbances.By using a full-order sliding-mode(FOSM)approach,voltage regulation and frequency restoration are achieved in finite time.For voltage regulation,a distributed observer is proposed for each distributed generator(DG)to estimate a reference voltage level.Different from some conventional observers,the reference voltage level in this paper is accurately estimated under directed communication topologies.Based on the observer,a new nonlinear controller is designed in a backstepping manner such that an FOSM surface is reached in finite time.On the surface,the voltages of DGs are regulated to the reference level in finite time.For frequency restoration,a distributed controller is further proposed such that a constructed FOSM surface is reached in finite time,on which the frequencies of DGs are restored to a reference level in finite time under directed communication topologies.Finally,case studies on a modified IEEE 37-bus test system are conducted to demonstrate the effectiveness,the robustness against load changes,and the plug-and-play capability of the proposed controllers.

Distributed Periodic Event-Triggered Optimal Control of DC Microgrids Based on Virtual Incremental Cost

This article presents a distributed periodic eventtriggered(PET)optimal control scheme to achieve generation cost minimization and average bus voltage regulation in DC microgrids.In order to accommodate the generation constraints of the distributed generators(DGs),a virtual incremental cost is firstly designed,based on which an optimality condition is derived to facilitate the control design.To meet the discrete-time(DT)nature of modern control systems,the optimal controller is directly developed in the DT domain.Afterward,to reduce the communication requirement among the controllers,a distributed event-triggered mechanism is introduced for the DT optimal controller.The event-triggered condition is detected periodically and therefore naturally avoids the Zeno phenomenon.The closed-loop system stability is proved by the Lyapunov synthesis for switched systems.The generation cost minimization and average bus voltage regulation are obtained at the equilibrium point.Finally,switch-level microgrid simulations validate the performance of the proposed optimal controller.

Adaptive Decentralized Output-Constrained Control of Single-Bus DC Microgrids

A single-bus DC microgrid can represent a wide range of applications. Control objectives of such systems include high-performance bus voltage regulation and proper load sharing among multiple distributed generators(DGs) under various operating conditions. This paper presents a novel decentralized control algorithm that can guarantee both the transient voltage control performance and realize the predefined load sharing percentages. First, the output-constrained control problem is transformed into an equivalent unconstrained one. Second, a two-step backstepping control algorithm is designed based on the transformed model for bus-voltage regulation. Since the overall control effort can be split proportionally and calculated with locally-measurable signals, decentralized load sharing can be realized. The control design requires neither accurate parameters of the output filters nor load measurement. The stability of the transformed systems under the proposed control algorithm can indirectly guarantee the transient bus voltage performance of the original system. Additionally, the high-performance control design is robust, flexible, and reliable. Switch-level simulations under both normal and fault operating conditions demonstrate the effectiveness of the proposed algorithm.

Programmable Adaptive Security Scanning for Networked Microgrids

Communication-dependent and software-based distributed energy resources(DERs)are extensively integrated into modern microgrids,providing extensive benefits such as increased distributed controllability,scalability,and observability.However,malicious cyber-attackers can exploit various potential vulnerabilities.In this study,a programmable adaptive security scanning(PASS)approach is presented to protect DER inverters against various power-bot attacks.Specifically,three different types of attacks,namely controller manipulation,replay,and injection attacks,are considered.This approach employs both software-defined networking technique and a novel coordinated detection method capable of enabling programmable and scalable networked microgrids(NMs)in an ultra-resilient,time-saving,and autonomous manner.The coordinated detection method efficiently identifies the location and type of power-bot attacks without disrupting normal NM operations.Extensive simulation results validate the efficacy and practicality of the PASS for securing NMs.

Structured Microgrids (SμGs) and Flexible Electronic Large Power Transformers (FeLPTs)

Structured microgrids(SμGs)and Flexible electronic large power transformers(FeLPTs)are emerging as two essential technologies for renewable energy integration,flexible power transmission,and active control.SμGs provide the integration of renewable energy and storage to balance the energy demand and supply as needed for a given system design.FeLPT’s flexibility for processing,control,and re-configurability offers the capability for flexible transmission for effective flow control and enable SμGs connectivity while still keeping multiscale system level control.Early adaptors for combined heat and power have demonstrated significant economic benefits while reducing environmental foot prints.They bring tremendous benefits to utility companies also.With storage and active control capabilities,a 300-percent increase in bulk transmission and distribution lines are possible without having to increase capacity.SμGs and FeLPTs will also enable the utility industry to be better prepared for the emerging large increase in base load demand from electric transportation and data centers.This is a win-win-win situation for the consumer,the utilities(grid operators),and the environment.SμGs and FeLPTs provide value in power substation,energy surety,reliability,resiliency,and security.It is also shown that the initial cost associated with SμG and FeLPTs deployment can be easily offset with reduced operating cost,which in turn reduces the total life-cycle cost by 33%to 67%.

Dual Layered Architecture for Multi Agent Based Islanding and Load Management for Microgrids

This paper proposes a novel dual layered multi agent system (MAS) based control system for the use in microgrid operations. In developing a smarter grid capable of withstanding disturbances and/or outages and providing quality service to the consumers, reliable microgrid control architecture is vital. The innovative microgrid control system proposed, makes the microgrid capable of isolating the local grid from effects of any upstream disturbances in the main utility grid by operating disconnected from the main utility via islanding, and it allows the most critical local loads to be supplied by any, available, local power source during such islanded operation. The proposed MAS control architecture is developed using the JADE platform and it is used to control a test network simulated in MATLAB. The results of these simulations show the capability of developing MAS based reliable control mechanism for islanding and load management of microgrids based on the proposed concept.

Optimal Scheduling of PEV Charging/Discharging in Microgrids with Combined Objectives

While renewable power generation and vehicle electrification are promising solutions to reduce greenhouse gas emissions, it faces great challenges to effectively integrate them in a power grid. The weather-dependent power generation of renewable energy sources, such as Photovoltaic (PV) arrays, could introduce significant intermittency to a power grid. Meanwhile, uncontrolled PEV charging may cause load surge in a power grid. This paper studies the optimization of PEV charging/discharging scheduling to reduce customer cost and improve grid performance. Optimization algorithms are developed for three cases: 1) minimize cost, 2) minimize power deviation from a pre-defined power profile, and 3) combine objective functions in 1) and 2). A Microgrid with PV arrays, bi-directional PEV charging stations, and a commercial building is used in this study. The bi-directional power from/to PEVs provides the opportunity of using PEVs to reduce the intermittency of PV power generation and the peak load of the Microgrid. Simulation has been performed for all three cases and the simulation results show that the presented optimization algorithms can meet defined objectives.

Distributed Secondary Control and Optimal Power Sharing in Microgrids

We address the control problem of microgrids and present a fully distributed control system which consists of primary controller,secondary controller,and optimal active power sharing controller.Different from the existing control structure in microgrids,all these controllers are implemented as local controllers at each distributed generator.Thus,the requirement for a central controller is obviated.The performance analysis of the proposed control systems is provided,and the finite-time convergence properties for distributed secondary frequency and voltage controllers are achieved.Moreover,the distributed control system possesses the optimal active power sharing property.In the end,a microgrid test system is investigated to validate the effectiveness of the proposed control strategies.

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.

Cyber Attack Protection and Control of Microgrids

Recently, the smart grid has been considered as a next-generation power system to modernize the traditional grid to improve its security, connectivity, efficiency and sustainability.Unfortunately, the smart grid is susceptible to malicious cyber attacks, which can create serious technical, economical, social and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional(RSC) code and Kalman filter(KF) based method in the context of smart grids.Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a-posterior is used to recover the state information, which is affected by random noises and cyber attacks. Once the estimated states are obtained by KF algorithm, a semidefinite programming based optimal feedback controller is proposed to regulate the system states, so that the power system can operate properly. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states.

Real-time scheduling strategy for microgrids considering operation interval division of DGs and batteries

Real-time scheduling as an on-line optimization process must output dispatch results in real time. However, the calculation time required and the economy have a trade-off relationship. In response to a real-time scheduling problem, this paper proposes a real-time scheduling strategy considering the operation interval division of distributed generators(DGs) and batteries in the microgrid. Rolling scheduling models, including day-ahead scheduling and hours-ahead scheduling, are established, where the latter considers the future state-of-charge deviations. For the real-time scheduling, the output powers of the DGs are divided into two intervals based on the ability to track the day-ahead and hours-ahead schedules. The day-ahead and hours-ahead scheduling ensure the economy, whereas the real-time scheduling overcomes the timeconsumption problem. Finally, a grid-connected microgrid example is studied, and the simulation results demonstrate the effectiveness of the proposed strategy in terms of economic and real-time requirements.

A Grid Interface Current Control Strategy for DC Microgrids

In this paper,a grid interface current control strategy is presented for a DC microgrid,which aims to reduce the disturbance from PV generation and the load variation to the main grid without a grid interface converter.The grid interface current is directly controlled by a battery DC-DC converter within the DC microgrid.Based on a comprehensive analysis of the battery DC-DC converter and interface current control,the control system has been mathematically modelled.This enabled two transfer functions to be derived that reflect the dynamic response of the inductor current to the duty cycle variation(inner loop),and the dynamic response of the grid interface current to the inductor current variation(outer loop).Experimental study has been done to assess the effectiveness of the proposed control strategy.The experimental results indicate that the proposed control strategy has a good performance to control the grid interface current without an interface converter,regardless the variations of both PV and the load conditions.

Resilience enhancement strategy using microgrids in distribution network

We propose a restoration strategy using microgrids for restoring power supply to critical loads after an extreme event and thereby enhancing the resilience of the distribution power grid. The limited capacities of distributed generators(DGs) within the microgrids and those of intermittent energy sources such as wind and photovoltaic power are considered. An enhanced strategy model of the distribution network is established for maximizing the power supply to critical loads. Firstly, the importance of the load is quantified by using the analytic hierarchy process(AHP) and the model of the microgrid output is further improved. In the demand response mechanism, an interruptible load is used to suppress the fluctuation in the distributed power output. Secondly, piecewise linearization method is applied to address the power flow constraints. Then, the resilience enhancement model of the distribution network is transformed into a mixed integer quadratic programming problem. The CPLEX solver is adopted to solve the above problem on the MATLAB platform. Finally, the proposed method is verified by applying it to practical scenarios.

Robust Controller Synthesis and Analysis in Inverter-Dominant Droop-Controlled Islanded Microgrids

This work investigates the problem of controller design for the inverters in an islanded microgrid.Robust-synthesis controllers and local droop controllers are designed to regulate the output voltages of inverters and share power among them,respectively.The designed controllers alleviate the need for additional sensors to measure the states of the system by relying only on output feedback.It is shown that the designed-synthesis controller properly damps resonant oscillations,and its performance is robust to the control-loop time delay and parameter uncertainties.The stability of a droop-controlled islanded microgrid including multiple distributed generation(DG)units is analyzed by linearizing the nonlinear power flow model around the nominal operating point and applying theorems from linear algebra.It is indicated that the droop controller stabilizes the microgrid system with dominantly inductive tie-line impedances for all values of resistive-inductive loads,while for the case of resistive-capacitive loads the stability is conditioned on an upper bound on the load susceptances.The robust performance of the designed-synthesis controller is studied analytically,compared with the similar analysis in an control(benchmark)framework,and verified by simulations for a four DG benchmark microgrid.Furthermore,the robustness of the droop controllers is analyzed by Monte Carlo simulations in the presence of local voltage fluctuations and phase differences among neighboring DGs.

Microgrids-as-a-Service for Rural Electrification in Sub-Saharan Africa

The majority of the population on the African continent is unable to access basic electricity services,this despite the abundance of renewable energy sources(RESs).The inability to adequately tap into these RESs has led to the continued dependence on non-renewable energy sources such as coal for electricity generation,and kerosene for cooking and lighting,the resulting use of which is poor health conditions.The use of Microgrids(MGs)is being extensively researched as a feasible means of tackling the challenge of electrification,especially in rural and remote areas.Recent times have seen an increasing number of research works focusing on Sub-Saharan Africa(SSA),which is one of the regions with the lowest electrification rates in the world.MGs provide the most suitable means to integrate RESs into the electricity generation process,paving the way towards clean energy for the African continent.This paper presents a review of recent literature on the usage of MG technology for rural electrification,with a specific focus on the applicability of MGs in the SSA context.The paper additionally presents the challenges and opportunities to date.Research findings indicate that SSA has already begun the transition towards clean energy via implementation of RES-based MGs.However,two resonating challenges in the literature are adequate support via policy,and proper planning of project implementation.These two major barriers are needed to be overcome in order to fully utilize MGs for rural electrification in SSA.The key methodology derived from this study is that any effort towards rural electrification requires a sufficient amount of investigation,incorporating both the technological and socio-economic aspects into a suitable design for the target location.