The objective of this paper is to provide a review of distributed control and management strategies for the next generation power system in the context of microgrids. This paper also identifies future research directions. The next generation power system, also referred to as the smart grid, is distinct from the existing power system due to its extensive use of integrated communication, advanced components such as power electronics, sensing, and measurement, and advanced control technologies. At the same time, the need for increased number of small distributed and renewable energy resources can exceed the capabilities of an available computational resource. Therefore, the recent literature has seen a significant research effort on dividing the control task among different units, which gives rise to the development of several distributed techniques. This paper discusses features and characteristics of these techniques, and identifies challenges and opportunities ahead. The paper also discusses the relationship between distributed control and hierarchical control.

Distributed Control Techniques in Microgrids

The deployment of energy storage systems (ESSs) is a significant avenue for maximising the energy efficiency of a distribution network, and overall network performance can be enhanced by their optimal placement, sizing, and operation. An optimally sized and placed ESS can facilitate peak energy demand fulfilment, enhance the benefits from the integration of renewables and distributed energy sources, aid power quality management, and reduce distribution network expansion costs. This paper provides an overview of optimal ESS placement, sizing, and operation. It considers a range of grid scenarios, targeted performance objectives, applied strategies, ESS types, and advantages and limitations of the proposed systems and approaches. While batteries are widely used as ESSs in various applications, the detailed comparative analysis of ESS technical characteristics suggests that flywheel energy storage (FES) also warrants consideration in some distribution network scenarios. This research provides recommendations for related requirements or procedures, appropriate ESS selection, smart ESS charging and discharging, ESS sizing, placement and operation, and power quality issues. Furthermore, this study identifies future research opportunities in relation to challenges for optimal ESS placement planning, development and implementation issues, optimisation techniques, social impacts, and energy security.

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Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality

The microgrid concept allows small distributed energy resources (DERs) to act in a coordinated manner to provide a necessary amount of active power and ancillary service when required. This paper proposes an approach of coordinated and integrated control of solar PV generators with the maximum power point tracking (MPPT) control and battery storage control to provide voltage and frequency (V-f) support to an islanded microgrid. Also, active and nonactive/reactive power (P-Q) control with solar PV, MPPT and battery storage is proposed for the grid connected mode. The control strategies show effective coordination between inverter V-f (or P-Q) control, MPPT control, and energy storage charging and discharging control. The paper also shows an effective coordination among participating microresources while considering the case of changing irradiance and battery state of charge (SOC) constraint. The simulation studies are carried out with the IEEE 13-bus feeder test system in grid connected and islanded microgrid modes. The results clearly verify the effectiveness of proposed control methods. The simulations are carried out in Matlab and Simpowersystems.

Coordinated V-f and P-Q Control of Solar Photovoltaic Generators With MPPT and Battery Storage in Microgrids

This paper proposes a transformative architecture for the normal operation and self-healing of networked microgrids (MGs). MGs can support and interchange electricity with each other in the proposed infrastructure. The networked MGs are connected by a physical common bus and a designed two-layer cyber communication network. The lower layer is within each MG where the energy management system (EMS) schedules the MG operation; the upper layer links a number of EMSs for global optimization and communication. In the normal operation mode, the objective is to schedule dispatchable distributed generators (DGs), energy storage systems (ESs), and controllable loads to minimize the operation costs and maximize the supply adequacy of each MG. When a generation deficiency or fault happens in an MG, the model switches to the self-healing mode and the local generation capacities of other MGs can be used to support the on-emergency portion of the system. A consensus algorithm is used to distribute portions of the desired power support to each individual MG in a decentralized way. The allocated portion corresponds to each MG’s local power exchange target, which is used by its EMS to perform the optimal schedule. The resultant aggregated power output of networked MGs will be used to provide the requested power support. Test cases demonstrate the effectiveness of the proposed methodology.

Networked Microgrids for Self-Healing Power Systems

Existing electric power distribution networks are operating near full capacity and facing rapid changes to address environmental concerns and improve their reliability and sustainability. These concerns are satisfied through the effective integration and coordination of distributed generators (DGs), which facilitate the exploitation of renewable energy resources, including wind power, photovoltaics, and fuel cells [1]. Although DGs can be of rotating machinery type, more recently, DGs have been designed to support renewable energy resources by electronic interfacing through voltage source inverters (VSI). Each DG corresponds to one energy source, and its control inputs are given to the interface VSI [1]-[5]. The successful coordination of DGs can be realized through microgrids, which are small-scale power systems consisting of local generation, local loads, and energy storage systems. Microgrids are autonomous subsystems with dedicated control systems that provide guaranteed power quality for local loads such as hospitals, economic centers, apartments, and universities. The microgrid concept, with its local control and power quality support, allows for the scalable integration of local power resources and loads into the existing power grid and enables a high penetration of distributed generation [5]-[10].

Distributed Control Systems for Small-Scale Power Networks: Using Multiagent Cooperative Control Theory

Distributed energy resources (DE) or distributed generators (DG) with power electronics interfaces and logic control using local measurements are capable of providing reactive power related ancillary system services. In particular, local voltage regulation has drawn much attention in regards to power system reliability and voltage stability, especially from past major cascading outages. This paper addresses the challenges of controlling DEs to regulate local voltage in distribution systems. An adaptive voltage control method has been proposed to dynamically modify control parameters to respond to system changes. Theoretical analysis shows that there exists a corresponding formulation of the dynamic control parameters; hence the adaptive control method is theoretically solid. Both simulation and field experiment test results at the Distributed Energy Communications and Controls (DECC) Laboratory confirm that this method is capable of satisfying the fast response requirement for operational use without causing oscillation, inefficiency, or system equipment interference. Since this method has a high tolerance to real-time data shortage and is widely adaptive to variable power system operational situations, it is quite suitable for broad utility application.

Adaptive voltage control with distributed energy resources: Algorithm, theoretical analysis, simulation, and field test verification

Adaptive Voltage Control With Distributed Energy Resources: Algorithm, Theoretical Analysis, Simulation, and Field Test Verification

Grid-connected photovoltaic (PV) systems with power electronic interfaces can provide both real and reactive power to meet power system needs with appropriate control algorithms. This paper presents the control algorithm design for a three-phase single-stage grid-connected PV inverter to achieve either maximum power point tracking (MPPT) or a certain amount of real power injection, as well as the voltage/var control. The switching between MPPT control mode and a certain amount of real power control mode is automatic and seamless. Without the DC-to-DC booster stage, PV DC voltage stability is an important issue in the control design especially when the PV inverter is operating at maximum power point (MPP) with voltage/var control. The PV DC voltage collapse phenomenon and its reason are discussed. The method based on dynamic correction of the PV inverter output is proposed to ensure PV DC voltage stability. Simulation results of the single-stage PV system during system disturbances and fast solar irradiation changes confirm that the proposed control algorithm for single-stage PV inverters can provide appropriate real and reactive power services and ensure PV DC voltage stability during dynamic system operation and atmospheric conditions.

Real and reactive power control of a three-phase single-stage PV system and PV voltage stability

This paper proposes a plug-and-play control method to coordinate multiple distributed energy resources (DER or DE) to regulate voltages in future distribution systems with a high DE penetration. Theoretical analysis shows that there exists a corresponding formulation of the dynamic control parameters with multiple DEs to give the desired responses. Therefore, the proposed control method has a solid theoretical basis. The method is based on dynamically and adaptively adjusting DE control parameters to ensure that actual voltage responses follow the desired outputs. Also, it is based on local and the other DEs' voltages without the need of the full system data and extensive studies to tune the control parameters. Hence, the method is autonomous and adaptive for variable operational situations, and has the plug-and-play feature with a high tolerance to unavailable or inaccurate system data. Thus, it is suitable for broad utility application. Simulation results from various conditions, such as asynchronous start of multiple DEs, disappearance of the original disturbance in the middle of the control process, and operation in looped distribution systems, confirm the performance, validity, and flexibility of the proposed control method. The possible impact of communication latency on the performance of the proposed method is also discussed.

Autonomous and adaptive voltage control using multiple distributed energy resources

In this paper, simultaneous control of active power and volt/var is explored with photovoltaic (PV) generators in distribution systems. The PV active power output can be controlled in the load-following mode when sufficient solar power is available to supply a local load, or the maximum power point tracking (MPPT) mode when a local load is large or injection to the system is allowed. Two selected control approaches, P-Q control in the load-following mode and P-V control in the MPPT mode, are investigated in this paper. The P-Q control is implemented with a relatively simple approach, while the P-V control demands an extra MPPT logic, which is solved based on a power balance between the dc and ac sides in a two-stage PV configuration. The control algorithms are tested with the IEEE 13-bus distribution feeder with various system conditions like the presence of multiple PV generators, imbalance, harmonics, and faults. The MATLAB and SimPowerSystems simulation results clearly demonstrate the capability of the proposed control in maintaining the P/V bus as either a P-Q or P-V bus depending on different applications.

Huijuan Li

Papers

Adaptive voltage control with distributed energy resources: Algorithm, theoretical analysis, simulation, and field test verification

Adaptive Voltage Control With Distributed Energy Resources: Algorithm, Theoretical Analysis, Simulation, and Field Test Verification

Real and reactive power control of a three-phase single-stage PV system and PV voltage stability

Autonomous and adaptive voltage control using multiple distributed energy resources

P-Q and P-V Control of Photovoltaic Generators in Distribution Systems