The paper proposes an optimal management strategy for a system composed by a battery and a photovoltaic power plant. This integrated system is called to deliver the photovoltaic power and to simultaneously provide droop-based primary frequency regulation to the main grid. The battery state-of-energy is controlled by power offset signals, which are determined using photovoltaic energy generation forecasts and predictions of the energy required to operate frequency regulation. A two level control architecture is developed. A day-ahead planning algorithm schedules the energy profile which is traded at the day-ahead market and defines the primary control reserve that the integrated system is able to provide in the considered day. During the day operations, a second level algorithm corrects the dispatched plan using updated information, in order to guarantee a continuous and reliable service. Both control algorithms take into account the uncertainties of the photovoltaic generation and of the frequency dynamics using stochastic optimization.
Motivated by the need of assessing the optimal allocation of battery energy storage services across various markets and the corresponding impact on market operations, an optimization framework is proposed in this work to coordinate the operation of an independent utility-scale price-maker battery energy storage system (BESS) in the energy, spinning reserve and performance-based regulation markets. The entire problem is formulated as a bi-level optimization process, where the structure of all markets is modeled considering the joint operation limits. The strategic bidding behavior of a price-ma…
The progressive displacing of conventional generation in favour of renewable energy sources requires restoring an adequate capacity of regulating power to ensure reliable operation of power systems. Battery Energy Storage Systems (BESSs) are considered to be promising assets to restore suitable frequency regulation capacity levels. BESSs are typically connected to the grid with power-converters, able to operate in either grid-forming or grid-following modes. This paper quantitatively assesses the impact on the local distribution grid of BESSs providing frequency regulation to bulk power system…
Battery energy storage systems (BESS) are proving to be an effective solution in providing frequency regulation services to the bulk grid. However, there are several concerns for the transmission/distribution system operators (TSO/DSO) with the frequent dispatching of the distribution-connected fast-responding storage systems. Unfortunately, the existing decoupled models for transmission and distribution (T&D) simulations are unable to capture the complex interactions between the two systems especially concerning frequency regulation problems due to rapidly varying distribution-connected distr…
This paper proposes a bi-level optimization framework to investigate the optimal market operation strategies of price-maker battery energy storage systems (BESSs) in real-time energy, spinning reserve, and pay as performance regulation markets, with a special focus on understanding BESS's excessive regulation market participation observed by several system operators and the impact of battery degradation cost on BESS market activities. An accurate battery degradation cost function is integrated into the BESS's strategic bidding model. An automatic generation control (AGC) signal dispatch model …
This paper presents an optimal control strategy for operating a solar hybrid system consisting of solar photovoltaic (PV) and a high-power, low-storage battery energy storage system (BESS). A state-space model of the hybrid PV plant is first derived, based on which an adaptive model predictive controller is designed. The controller's objective is to control the PV and BESS to follow power setpoints sent to the the hybrid system while maintaining desired power reserves and meeting system operational constraints. Furthermore, an extended Kalman filter (EKF) is implemented for estimating the batt…
A hybrid hydropower power plant is a conventional HydroPower Plant (HPP) augmented with a Battery Energy Storage System (BESS) to decrease the wear and tear of sensitive mechanical components and improve the reliability and regulation performance of the overall plant. A central task of controlling hybrid power plants is determining how the total power set-point should be split between the BESS and the hybridized unit (power set-point splitting) as a function of the operational objectives. This paper describes a Model Predictive Control (MPC) framework for hybrid medium- and high-head plants to…
Driven by the global decarbonization effort, the rapid integration of renewable energy into the conventional electricity grid presents new challenges and opportunities for the battery energy storage system (BESS) participating in the energy market. Energy arbitrage can be a significant source of revenue for the BESS due to the increasing price volatility in the spot market caused by the mismatch between renewable generation and electricity demand. In addition, the Frequency Control Ancillary Services (FCAS) markets established to stabilize the grid can offer higher returns for the BESS due to …
Battery energy storage systems (BESSs) provide many benefits to the electricity grid, including stability, backup power, and flexibility in introducing more clean energy sources. As BESS penetration grows, knowledge of the uncertainty in the battery's state of charge (SOC) estimate is crucial for planning optimal BESS power injection trajectories. This paper proposes a framework for quantifying SOC estimation uncertainty based on battery rest periods. An uncertainty analysis is presented for a BESS participating in the frequency regulation market.
This work presents a suite of two optimisation models for the short-term scheduling and redispatch of a virtual power plant (VPP) composed of a wind farm and a Li-ion battery, that participates in the day-ahead energy and secondary regulation reserve markets of the Iberian electricity market. First, a two-stage stochastic mixed-integer linear programming model is used to obtain the VPP's generation and reserve schedule and the opportunity cost of the energy stored in the battery. The model has an hourly resolution and a look-ahead period beyond the markets' scheduling horizon and considers the…
This paper proposes a control method for battery energy storage systems (BESSs) to provide concurrent primary frequency and local voltage regulation services. The actual variable active and reactive power capability of the converter, along with the state-of-charge of the BESS, are jointly considered by the optimal operating point calculation process within the real-time operation. The controller optimizes the provision of grid services, considering the measured grid and battery statuses and predicting the battery DC voltage as a function of the current trajectory using a three-time-constant mo…
The recent decrease in battery manufacturing costs stimulates the market participation of utility-scale battery energy storage systems (BESSs). However, battery degradation remains a major concern for BESS owners while determining their BESS investment and operation strategies. This paper studies the impact of battery degradation on BESS's operation and revenue/cost in real-time energy, reserve, and pay as performance regulation markets. Comparative case studies are performed on two optimization frameworks which model the participation of a price-maker BESS in energy and ancillary services mar…
The power system needs more transmission capacity to deal with the increasing integration of renewable energy resources. The battery energy storage systems (BESSs) are effective to enhance the grid capacity and relieve the transmission congestion. A comprehensive revenue analysis of BESSs is critical for market participants to install such systems in a market-based power system. Taking PJM as an example, this paper carries out a thorough revenue analysis for the entire system. Highly profitable nodes in the system are revealed and characterized for BESS participants. A comparison study of stat…
This paper presents a dynamic Frequency Regulation (FR) model of a large interconnected power system including Energy Storage Systems (ESSs) such as Battery Energy Storage Systems (BESSs) and Flywheel Energy Storage Systems (FESSs), considering all relevant stages in the frequency control process. Communication delays are considered in the transmission of the signals in the FR control loop and ESSs, and their State of Charge (SoC) management model is considered. The system, ESSs and SoC components are modelled in detail from a FR perspective. The model is validated using real system and ESSs d…
Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-II: Intra-day and Experimental Validation
This paper proposes and experimentally validates a joint control and scheduling framework for a grid-forming converter-interfaced BESS providing multiple services to the electrical grid. The framework is designed to dispatch the operation of a distribution feeder hosting heterogeneous prosumers according to a dispatch plan and provide frequency containment reserve and voltage control as additional services. The framework consists of three phases. In the day-ahead scheduling phase, a robust optimization problem is solved to compute the optimal dispatch plan and frequency droop coefficient, acco…
Heating, ventilation, and air-conditioning (HVAC) systems are ideal demand-side flexible resources to provide regulation services. However, finding the best hourly regulation capacity offers for HVAC systems in a power market ahead of time is challenging because they are affected by non-Gaussian uncertainties from regulation signals. Moreover, since HVAC systems need to frequently regulate their power according to regulation signals, numerous thermodynamic constraints are introduced, leading to a huge computational burden. This paper proposes a tractable chance-constrained model to address the…
Achieving the Dispatchability of Distribution Feeders through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage
École Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）
In this paper, we propose a two-stage electricity market framework to explore the participation of distributed energy resources (DERs) in a day-ahead (DA) market and a real-time (RT) market. The objective is to determine the optimal bidding strategies of the aggregated DERs in the DA market and generate online incentive signals for DER-owners to optimize the social welfare taking into account network operational constraints. Distributionally robust optimization is used to explicitly incorporate data-based statistical information of renewable forecasts into the supply/demand decisions in the DA…
Risk analysis is currently not quantified in microgrid resource scheduling optimization. This paper conducts a conditional value at risk (cVaR) analysis on a grid-disconnected residential microgrid with distributed energy resources (DER). We assume the infrastructure to set up an ad-hoc microgrid is already in place for a residential neighborhood with power sources such as photovoltaic (PV), diesel, and battery energy storage system (BESS). With this scenario in mind, we solve day-ahead scheduling to optimally allocate various resources to match demand in scenarios where neighborhoods, especia…
Battery energy storage system (BESS) can effectively mitigate the uncertainty of variable renewable generation and provide flexible ancillary services. However, degradation is a key concern for rechargeable batteries such as the most widely used Lithium-ion battery. A neural network based battery degradation (NNBD) model can accurately quantify the battery degradation. When incorporating the NNBD model into security-constrained unit commitment (SCUC), we can establish a battery degradation based SCUC (BD-SCUC) model that can consider the equivalent battery degradation cost precisely. However, …
This paper proposes an incentive-based aggregator for electric vehicles (EVs) in workplace parking lots to participate in the energy and regulation markets. With the implementation of seasonal Autoregressive Integrated Moving Average (ARIMA) model to predict the market information, a Day-Ahead (DA) planning model coordinated with the EV's responses to the incentive is formulated to determine the days to activate the aggregation program and the optimal incentives that are broadcasted to the EV owners in the first stage. Given the determined incentives and EV's responses, an real-time (RT) optim…
The increasing diffusion of distributed energy generation systems requires the development of new control paradigms for the coordination of micro-generators, storage systems, and loads aimed at maintaining the efficiency and the safe operability of the electricity network. MicroGrids (MGs) are an interesting way to locally manage groups of generation devices, but they cannot singularly provide a significant contribution to sustain the main electricity grid in terms of ancillary services, such as the availability of a minimum amount of power reserve for the frequency regulation. For these reaso…
Vanderbilt University（范德堡大学）；University of Arizona（亚利桑那大学）
This work addresses whether a human-in-the-loop cyber-physical system (HCPS) can be effective in improving the longitudinal control of an individual vehicle in a traffic flow. We introduce the CAN Coach, which is a system that gives feedback to the human-in-the-loop using radar data (relative speed and position information to objects ahead) that is available on the controller area network (CAN). Using a cohort of six human subjects driving an instrumented vehicle, we compare the ability of the human-in-the-loop driver to achieve a constant time-gap control policy using only human-based visual …
To accommodate the advent of microgrids (MG) managing distributed energy resources (DER) in distribution systems, an interactive two-stage joint retail electricity market mechanism is proposed to provide an effective platform for these prosumers to proactively join in retail transactions. Day-ahead stochastic energy trading between the distribution system operator (DSO) and MGs is conducted in the first stage of a centralized retail market, where a chance-constrained uncertainty distribution locational marginal price (CC-UDLMP) containing the cost of uncertainty precautions is used to settle t…
