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This paper presents a 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 data, based on a practical transient stability model of the North American Eastern Interconnection (NAEI), and the results show that the proposed model accurately represents the FR process of a large interconnected power network including ESS, and can be used for long-term FR studies. The impact of communication delays and SoC management of ESS facilities in the Area Control Error (ACE) is also studied and discussed, as well as the computational efficiency of the proposed FR model. [ABSTRACT FROM AUTHOR]

This paper presents a novel $\mathcal {H}_{2}$ filter design procedure to optimally split the Frequency Regulation (FR) signal between conventional and fast regulating Energy Storage System (ESS) assets, considering typical Communication Delays (CDs). The filter is then integrated into a previously validated FR model of the Ontario Power System (OPS) including Battery and Flywheel ESSs, which is used to analyze the impact of these ESSs, CDs, and limited regulation capacity in the FR process in a real system. The proposed methodology to split the FR signal is also compared with the existing FR process, with the results showing that the proposed $\mathcal {H}_{2}$ filter design and signal splitting strategy can improve the FR process performance significantly, in terms of reducing the Area Control Error (ACE) signal, and thus reduce the need for regulation capacity. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESSs) can improve energy management in distribution grids, especially with the increasing penetration of home energy management systems (HEMSs) that schedule household appliances and render them as smart loads. A large number of uncoordinated HEMSs can result in significant changes to the aggregated load profile of the distribution system. This paper proposes a framework and mathematical model for integrating ESS in the distribution grid to minimize the operation cost of the local distribution company (LDC) and alleviate the impact of uncoordinated HEMS operation on the distribution grid. A novel neural network (NN) based state of health (SoH) estimator for a lithium-ion (Li-ion) battery based ESS is proposed, which is incorporated within the LDC's planning problem. The results show that the proposed estimation model is an accurate estimation of the SoH of the ESS. The LDC's planning decisions are also compared, considering SoH of the ESS vis-á-vis linear degradation and no-degradation models. [ABSTRACT FROM AUTHOR]

This paper examines the non-strategic and strategic participation of a pumped hydro energy storage (PHES) facility in day-ahead energy and performance-based regulation (PBR), which includes regulation capacity and mileage markets. The PHES is modeled with the capability of operating in hydraulic short-circuit (HSC) mode with detailed representation of its operational constraints, and integrated with an energy-cum-PBR market clearing model. For its strategic participation, a bi-level market framework is proposed to determine the optimal offers and bids of the PHES that maximize its profit. The operation of PHES is modeled at the upper level, while the market clearing is modeled in the lower level problem. The bi-level problem is formulated as a mathematical program with equilibrium constraints (MPEC) model, which is linearized and solved as a mixed integer linear programming problem. Several case studies are carried out to demonstrate the impact of PHES’ non-strategic and strategic operations on market outcomes. Furthermore, stochastic case studies are conducted to determine the PHES strategies considering the uncertainty of the net demand and rivals’ price and quantity offers. [ABSTRACT FROM AUTHOR]

This paper discusses the implementation of a transient stability model of Compressed Air Energy Storage (CAES) systems in a power system analysis package. A block-diagram based model of a two-machine CAES system is proposed, including specific controls for active power, reactive power, and State of Charge (SoC), which consider limits associated with the cavern pressure. As an application, the model is implemented in Powertech's TSAT software connected to the 9-bus WSCC benchmark power system, which is then used to study the impact of a CAES facility in the transient and frequency stability of the system. Several contingencies are simulated comparing the CAES performance to a gas turbine and a base-case without storage, demonstrating that the CAES system improves the system transient stability due to its charging stage, controls, and additional inertia. Finally, the CAES model is used to study the effects of cavern sizes in the frequency of the system. It is shown that CAES systems have certain special characteristics that make them attractive as a storage technology to provide stability and regulation services, besides their energy arbitrage capabilities. [ABSTRACT FROM AUTHOR]

Recent Federal Energy Regulatory Commission (FERC) Order 841 requires that Independent System Operators (ISOs) facilitate the participation of energy storage systems (ESSs) in energy, ancillary services, and capacity markets, by including ESS bidding parameters that represent the physical and operational characteristics. However, in the existing market frameworks that allow Battery Energy Storage Systems (BESSs) to participate, the bids and offers do not explicitly represent the physical and operational characteristics such as the state of charge (SOC), discharge rate, degradation, etc. This paper proposes a novel BESS operational cost model considering degradation cost, based on depth of discharge and discharge rate. The model is developed considering Lithium-ion batteries, and the approach can be applied to other conventional electrochemical batteries, but not flow batteries. A detailed bid/offer structure based on the proposed BESS operational cost functions is formulated. Thereafter, a new framework and mathematical model for BESS participation in an LMP based, co-optimized, energy and spinning reserve market, are developed. Three case studies are presented to investigate the impact of BESS participation on system operation and market settlement. The proposed model is validated on the IEEE Reliability Test System (RTS) to demonstrate its functionalities. [ABSTRACT FROM AUTHOR]

In this paper, a detailed mathematical model of the diabatic compressed air energy storage (CAES) system and a simplified version are proposed, considering independent generators/motors as interfaces with the grid. The models can be used for power system steady-state and dynamic analyses. The models include those of the compressor, synchronous motor, cavern, turbine, synchronous generator, and associated controls. The configuration and parameters of the proposed models are based on the existing bulk CAES facilities of Huntorf, Germany. The models and performance of the CAES system are first evaluated with step responses, and then examined when providing frequency regulation in a test power system with high penetration of wind generation, comparing them with existing models of CAES systems. The simulation results confirm that the dynamic responses of the detailed and simplified CAES models are similar, and demonstrate that the simultaneous charging and discharging can significantly contribute to reduce the frequency deviation of the system from the variability of the wind farm power. [ABSTRACT FROM AUTHOR]

A novel stochastic planning framework is proposed to determine the optimal battery energy storage system (BESS) capacity and the year of installation in an isolated microgrid using a new representation of the BESS energy diagram. The BESS enhances microgrid operation via load leveling and reserve provisions in conjunction with the spinning reserve from dispatchable distributed generation (DG) units. A decomposition-based approach is proposed to solve the problem of stochastic planning of BESS under uncertainty. The optimal decisions minimize the net present value (NPV) of total expected costs over a multiyear horizon taking into consideration the optimal BESS operation considering a novel matrix representing BESS energy capacity degradation. The proposed approach is solved in two stages as mixed-integer linear programming problems to ensure the convergence of the stochastic optimization problem. The optimal ratings of the BESS are determined in the first stage, while the optimal installation year is determined in the second stage. The approach ensures utilizing the allocated budget effectively by performing several iterations. Extensive studies considering four types of BESS technologies for deterministic, Monte Carlo Simulations, and stochastic cases are presented to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

Driven by global environmental emission issues, energy access in remote communities, and tighter requirements for system resilience and reliability, electricity production is shifting from a centralized paradigm to a decentralized one. In this context, renewable energy sources (RESs) have proliferated over the past decade, exhibiting a steadily increasing trend. Thus, today, a large number of wind turbines and photovoltaic (PV) panels are connected to medium- (1-69 kV) and low-voltage (=1 kV) grids, with traditional integrated bulk power systems becoming decentralized in the presence of active distribution networks, where the flow of power is bidirectional between generators and "prosumers." In particular, with decreasing RES s costs, these technologies are becoming attractive solutions to bring energy to remote communities and/or replace expensive fossil-fuel-based generators. However, RES s such as wind and solar are intermittent sources of energy, difficult to predict, and prone to large output fluctuations-therefore, significantly affecting system voltage and frequency. [ABSTRACT FROM PUBLISHER]

• Small scale Compressed air energy storage system applications. • Behind-the-meter energy storage for peak demand charge management. • Economic and sensitivity analysis of customer-sited energy storage. • Energy Storage for Global adjustment management in Ontario, Canada. • Energy storage for commercial and Industrial customer peak load management. In this paper, the operations model of a behind-the-meter Small Scale Compressed Air Energy Storage (SS-CAES) facility is developed for an industrial customer with existing wells/caverns that can be re-purposed for air storage. The operations model seeks to minimize the electricity costs of the industrial customer, while determining the energy output and the corresponding charging and discharging decisions of the SS-CAES system. In order to examine the financial viability of a practical behind-the-meter SS-CAES facility, an economic analysis is carried out using real data of an industrial customer based in Ontario, Canada. Key parameters such as life cycle, CAES capacity and capital cost, and electricity price are considered for carrying out a sensitivity analysis, with the results showing that SS-CAES is economically viable for the current Ontario electricity tariff rate structure. The low capital cost of a SS-CAES project with a re-purposed storage cavern, and the high Global Adjustment charges levied in Ontario are shown to be a key determining factors for the economic feasibility of deployment of SS-CAES in Ontario. [ABSTRACT FROM AUTHOR]

This paper presents a detailed methodology to develop Marginal Rate of Technical Substitution (MRTS) curves, which can be used to optimally determine the appropriate substitution of traditional regulation signals with fast regulation signals, considering different Energy Storage System (ESS) technologies and discharging times, scenarios, and seasons. The presented work is based on the Ontario Power System (OPS) managed by the Independent Electricity System Operator (IESO) of Ontario, Canada. Different comparisons of the MRTS curves are carried out and the criteria used to obtain 16 average optimized MRTS curves, four per season, are presented. Finally, the 16 MRTS curves obtained for the IESO and their parameters are presented, and the use of these curves is explained through an example. • A methodology is proposed to compute Marginal Rate of Technical Substitution (MRTS) curves. • MRTS curves allow determining the substitution of traditional regulation with fast regulation signals. • MRTS curves are presented, explained, and compared, including the criteria to obtain them. • Results are based on data from the Independent Electricity System Operator (IESO) of Ontario, Canada. [ABSTRACT FROM AUTHOR]