Navigating the Physics of Virtual Power Plants: The Role of Devices, Controller Design, and the Grid

An increasing number of state and national interconnection standards are requiring Distributed Energy Resources (DER) to include grid-support functionality. These capabilities along with the growing number of communications-enabled DER make it possible for 3rd party aggregators to provide a range of high-level grid services such as voltage regulation, frequency regulation, and contingency reserves. For the last three years, Sandia National Laboratories has been designing and testing a real-time Virtual Power Plant (VPP) optimization and control platform to provide ancillary services with interoperable DER. In this paper we address the design of feedback controllers for VPPs to meet energy market and tertiary reserve targets. The VPP controller is designed to issue set points to the fleet of DERs to maintain the VPP output within the error margin. This is accomplished by compensating for individual DER losses and output fluctuations with the remainder of the aggregation. The impact of the communication network on the controller design is discussed and simulation results are presented to validate the proposed controller design.

To achieve the national carbon-peak and carbon-neutral strategic development goals, it is necessary to build power systems dominated by renewable and sustainable energy. The future power system with a high proportion of renewable and sustainable energy is required to have large-scale, low-cost, flexible, and adjustable resources. To this end, this article aggregates user-side distributed energy storage and electric vehicles into a virtual power plant, considering the uncertainty of wind power fluctuations and the uncertainty of electric vehicle charging and discharging to establish a day-ahead and intra-day peak regulation model for combined peak regulation of virtual and thermal power plants. The bounding algorithm seeks the optimal strategy for the two-stage model of joint peak regulation and obtains the day-ahead and intra-day two-stage optimal peak regulation strategy. The simulation example shows that the virtual power plant and its day-ahead and intra-day optimal peak regulation strategy can reduce the peak regulation cost of the power system, as compared with the deep peak regulation of thermal power plants with a special supporting energy storage power station. This work provides a global perspective for virtual power plants to participate in the formulation of power system peak regulation rules.

This paper describes modeling solar power generation as a renewable energy generator by simulating the analytical approach mean absolute error and root mean square error (MAE and RMSE). This research estimates the error referring to long short-term memory (LSTM) network learning. Related to this, the Indonesian government is currently actively developing solar power plants without ignoring the surrounding environment. The integration of solar power sources without accurate power prediction can hinder the work of the grid and the use of new and renewable generation sources. To overcome this, virtual power plant modeling can be a solution to minimize prediction errors. This study proposes a method for on-site virtual solar power plant efficiency with a research approach using two models, namely RMSE and MAE to account for prediction uncertainty from additional information on power plants using virtual solar power plants. A prediction strategy verified against the output power of photovoltaic (PV) modules and a set based on data from meteorological stations used to simulate the virtual power plants (VPP) model. This forecast prediction refers to the LSTM network and provides forecast errors with other learning methods, where the approach simulated with 12.36% and 11.85% accuracy for MAE and RMSE, respectively.

This article describes problems related to the operation of a virtual micro power plant at the Faculty of Electrical Engineering (FEE), Czestochowa University of Technology (CUT). In the era of dynamic development of renewable energy sources, it is necessary to create alternative electricity management systems for existing power systems, including power transmission and distribution systems. Virtual power plants (VPPs) are such an alternative. So far, there has been no unified standard for a VPP operation. The article presents components that make up the VPP at the FEE and describes their physical and logical structure. The presented solution is a combination of several units operating in the internal power grid of the FEE, i.e., wind turbines, energy storage (ES), photovoltaic panels (PV) and car charging stations. Their operation is coordinated by a common control system. One of the research goals described in the article is to optimize the operation of these components to minimize consumption of the electric energy from the external supply network. An analysis of data from the VPP management system was carried out to create mathematical models for prediction of the consumed power and the power produced by the PVs. These models allowed us to achieve the assumed objective. The article also presents the VPP data processing results in terms of detecting outliers and missing values. In addition to the issues discussed above, the authors also proposed to apply the Prophet model for short-term forecasting of the PV farm electricity production. It is a statistical model that has so far been used for social and business research. The authors implemented it effectively for technical analysis purposes. It was shown that the results of the PV energy production forecasting using the Prophet model are acceptable despite occurrences of missing data in the investigated time series.

The electricity supply chain is changing, due to increasing awareness for sustainability and an improved energy efficiency. The traditional infrastructure where demand is supplied by centralized generation is subject to a transition towards a Smart Grid. In this Smart Grid, sustainable generation from renewable sources is accompanied by controllable distributed generation, distributed storage and demand side load management for intelligent electricity consumption. The transmission and distribution grid have to deal with increasing fluctuations in demand and supply. Since realtime balance between demand and supply is crucial in the electricity network, this increasing variability is undesirable. Monitoring and controlling/managing this infrastructure increasingly depends on the ability to control distributed appliances for generation, consumption and storage. In the development of control methodologies, mathematical support, which consists of predicting demand, solving planning problems and controlling the Smart Grid in realtime, is of importance. In this thesis we study planning problems which are related to the Unit Commitment Problem: for a set of generators it has to be decided when and how much electricity to produce to match a certain demand over a time horizon. The planning problems that we formulate are part of a control methodology for Smart Grids, called TRIANA, that is developed at the University of Twente.

Currently, the most promising areas of development of motor transport are an increase of the horsepower characteristic of their power plants as well as increase of fuel efficiency, and reduction of the toxicity level of exhaust fumes. An internal combustion engine as a power unit of the car in a number of operation modes (supplemental motion, small work load, idling, etc.) works extremely inefficiently and contains the high concentration of harmful components in the exhaust fumes. Additionally, in a context of growing shortage of carbohydrate fuels and increase in their value, the problem of the fuel-burn improvement is especially acute. To improve the environmental compatibility and efficiency of power plants of the vehicles, combined cycle power plants are used. One of the most important problems that the machine construction faces is the creation of environmentally friendly and economical power plants. A hybrid power plant, which contains several power units operating on different physical principles, is proposed by the authors. The main power unit uses the energy of liquid or gaseous fuel in the mode of an internal combustion engine; the auxiliary power unit which is made as a reverse volumetrical driving machine with swinging motion of the work tools (forcers or blades), uses air power which comes from a pneumocylinder through a cooler and / or pneumatic air tank. The auxiliary power unit is equipped with a reversible invertor of the driving direction, made on the basis of a spherical slider-crank mechanism. This insures the operation of the auxiliary power unit in the mode of a pneumatic motor or compressor in accordance with the algorithm generated by the electronic control unit of the combined power plant of the vehicle. To utilize the heat energy of the exhaust fumes of the main power unit, the combined power plant is additionally equipped with a Stirling engine or steam generation module and a steam engine; in order to break energy recuperation of the vehicle it is additionally equipped with a hydraulic or electrodrive. Naturally, when choosing the specific forms of application of combined cycle power plants, any combinations of auxiliary power units are possible. They can be supplemented and / or specified based on the knowledge of specialists. Combined cycle power plants are technically complete solution. Their industrial applicability is obvious and is substantiated by experiments. Nowadays, the creation of a combined cycle power plants of a vehicle, which are a combination of several engines operating on different physical principles is the task of great economic importance. Combined power plants this allows to reduce fuel consumption per 100 km significantly, increase energy potential, horsepower characteristic and improve the environmental performance of the vehicle. The work is planned to be continued in the direction of optimization synthesis of auxiliary power units that work on different physical principles.

The aim of the work is the integration of combined heat and power (CHP) micro-units into the low voltage network under technical and economical point of view. The whole power and gas consumption of a new residential district are measured and recorded in fifteen minutes intervals during one year. Based on these power and gas load curves the basis of a virtual power plant with CHP micro-units is analysed. With a simulation tool the operation of a CHP micro-unit is simulated. The results show the behaviour of single units in different types of houses and of all units in a virtual power plant. Furthermore they show how the operation of a CHP micro-unit must be optimized for the operation in a virtual power plant. On the basis of this technical parameters a business model for an virtual control power plant is presented and calculated.

Power controller design for electrolysis systems with DC/DC interface supporting fast dynamic operation: A model-based and experimental study

Benefits and cost implications from integrating small flexible nuclear reactors with off-shore wind farms in a virtual power plant

This paper proposes a novel application for the optimal Linear Quadratic Gaussian (LQG) servo controller to enable a proper coordination of the AC/HVDC interconnected system with Virtual Synchronous Power (VSP) based inertia emulation. Particularly, the proposed control design takes the process disturbances and measurement noise of the studied VSP-HVDC system into account, while few studies have focused on this perspective. The proposed LQG controller with modifications is designed by means of a combination of Kalman Filter (state estimator) and an added Linear Quadratic Integrator (LQI) to observe the system model’s states and track the reference commands while rejecting the effects of system noise. Besides, we utilize a swarm-based optimization algorithm to operate as the search process for the tuning of the elements in the weighting matrices involved in the controller design. The role of the proposed optimal LQG controller is to stabilize such AC/DC interconnected system with VSP-based inertia emulator while minimizing the associated performance index. According to the obtained simulation results, in addition to the advancement from the VSP-based approach for damping frequency oscillations excited by faults, application of the proposed LQG servo controller can achieve the targets on both estimating the state variables and tracking the reference signals with satisfactory performance, comparing with the conventional LQG regulator.

This paper describes the design and implementation of the Power Plant Voltage Controller (PPVC) with an adaptive control which equips at the power plant level with the local high side voltage control. The Power Plant Voltage Controller is part of the hierarchical voltage control system which consists of Tertiary Voltage Control (TVC) at the higher control level and then followed by Secondary Voltage Control (SVC) as a regional controller and Primary Voltage Control (PVC) at the lowest control level to perform the control command. In this control approach, PPVC participates in the lowest control level in the Coordinated Voltage Control (CVC) system. The Power Plant Voltage Control regulators are autonomous controllers that regulate the high-side bus of the power plant while maintaining balanced VAR generation of the individual units and avoiding the dynamic interaction among multiple controlled generators. This paper presents a method of controlling the terminal voltage of the generators at the power plant by utilizing a quasi-steady-state sensitivity to get a control parameter for the PPVC. Using a simple control strategy, an adaptive control can be achieved by periodically calculating the quasi-steady-state sensitivity to update the control parameter, in such a way the PPVC control parameter not only can adapt to the variation of the interconnected network but also with the fluctuation of the load demands.

Summary form only given. This paper presents modeling, controller design, and simulation study of a proton exchange membrane fuel cell (PEMFC) distributed generation (DG) system. The overall configuration of the PEMFC DG system is given, dynamic models for the PEMFC power plant and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units to control the power flow from the fuel cell power plant to the utility grid are presented. A MATLAB/Simulink simulation model is developed for the PEMFC DG system by combining the individual component models and the controllers designed for the power conditioning units. Simulation results are given to show the overall system performance including load-following and fault handling capability of the system.

This paper presents modeling, controller design, and simulation study of a grid connected Photovoltaic (GCPV) distributed generation (DG) system. The overall configuration of the grid connected photovoltaic DG system are present. The dynamic models for the GCPV power plant and its power electronic interfacing are described. Controller design methodologies for the control of power flow from the photovoltaic cell power plant to the utility grid are also presented. A Matlab/Simulink based simulation model is developed for the GCPV DG system by combining the individual component models and the controllers design. Simulation results are presented to show the overall system performance.

This paper presents modeling, controller design, and simulation study of a proton exchange membrane fuel cell (PEMFC) distributed generation (DG) system. The overall configuration of the PEMFC DG system is given, dynamic models for the PEMFC power plant and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units to control the power flow from the fuel cell power plant to the utility grid are presented. A MATLAB/Simulink simulation model is developed for the PEMFC DG system by combining the individual component models and the controllers designed for the power conditioning units. Simulation results are given to show the overall system performance including load-following and fault-handling capability of the system.

In this study the controller forthree tank multi loop system is designed using coefficient Diagram method. Coefficient Diagram Method is one of the polynomial methods in control design. The controller designed by using CDM technique is based on the coefficients of the characteristics polynomial of the closed loop system according to the convenient performance such as equivalent time constant, stability indices and stability limit. Contro ller is designed for the threetank process by using CDM Techniques;the simulation results show that the proposed control strategies have good set point tracking and better responsecapability. Most of the processes industry in power plants, refinery process, aircrafts and chemical industries are multivariable or multi-input multi-output (MIMO) and control of these MIMO processes are more complicated than SISO processes. The strategies are used to design a controller for the S ingle input and single output (SISO) process cannot be applied for Multi input and multi output (MI MO) process because of the more interaction between the two loops. The different methods have been presented in the literature for control (1) of MIMO process. Proportional -integral-derivative (PID) or Proportional-Integral (PI) based controllers are used very commonly to control three tank systems. Generalized synthesis method used to tuning the controller parameters. Generally the two types of control schemes are available to control the MIMO processes. The first control scheme or multiloop control scheme, where single loop controller are used to in the form of diagonal matrix is one.. The second scheme is a (3) multivariable controller known as the centralized controller. Matrix is not a diagonal one. In this paper, the Coefficient Diagram Method (CDM) can be used to design a controller for MIMO process. Now the CDM is well established approach to design a controller, which provides an outstanding time domain characteristics of closed loop systems. Basically the CDM is based on pole assignment, which can locate of the closed-loop system are used to obtained the predetermined values. Although it has been used to demonstrate the design based on CDM. It has some robustness and is possible to see that of the smooth response without oscillation in change in the model of the process exists.