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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]

Oil refining is an energy-intensive industry, that is often equipped with different types of distributed generation (DG) resources. Optimal energy management of the refinery's load and its DG resources, under dynamic electricity pricing, improves electricity consumption behavior of the facility and hence reduces its energy costs. An energy management system (EMS) model is proposed in this paper for minimizing electricity consumption costs of an oil refinery facility considering on-site cogeneration capability. The energy management is based on power demand modeling of the oil refinery process. A joint electrical–thermal model is used for the cogeneration units to account for the electricity and steam production. The developed EMS model is also used as part of a demand response strategy to illustrate the impact of EMS decisions on distribution system operations. [ABSTRACT FROM AUTHOR]

In this paper the optimal design of an Electric Vehicle Charging Station (EVCS) with the goal of minimizing the lifecycle cost, while taking into account environmental emissions, is presented. Different energy sources such as renewable energy technology based and diesel generation are considered, with realistic inputs on their physical, operating and economic characteristics. In order to address the “range anxiety”, concern of EV owners regarding the distance the vehicle can travel, the design of an EVCS along highways, as an isolated microgrid, is studied. In another study, the EVCS is assumed to be connected to the grid as a smart energy hub. The charging demand of the EVCS is estimated considering real drive data. Analysis is also carried out to compare the economics of a grid-connected EVCS with an isolated EVCS and the optimal break-even distance for the grid connected EVCS to be a viable option, is determined. [ABSTRACT FROM AUTHOR]

With deregulation of the power industry, environmental policy changes, advancements in technology, and the transformation to smart grid, the distribution planning paradigm has gone through significant changes in recent years. Concurrently, with increase in gas prices, driven by a foreseeable fossil fuel depletion in the future, developments in the automotive sector, and environmental concerns, penetration of plug-in electric vehicles (PEVs) has been increasing. These changes will continue to drive the distribution planning problem to evolve in the coming years. This paper presents a comprehensive long-term distribution planning framework from the perspective of local distribution companies (LDCs) considering distributed generation (DG), substations, capacitors, and feeders. Apart from considering the usual demand profile, the proposed framework considers uncontrolled and controlled (smart) PEV charging demand, as well as demand response (DR) options. Based on a back-propagation algorithm combined with cost-benefit analysis, a novel approach is proposed to determine the optimal upgrade plan, allocation, and sizing of the selected components in distribution systems, to minimize the total capital and operating cost. A new iterative method is proposed which involves post-processing the plan decisions to guarantee acceptable adequacy levels for each year of the planning horizon. The performance of the proposed framework is examined considering several case studies on the 33-bus and 69-bus test systems. It is noted from the studies that the presence of uncontrolled PEV charging loads results in much higher plan costs as compared to the case without PEVs, impacts the distribution plan significantly, and hence these loads indeed need be considered in the planning process. On the other hand, smart charging of PEVs have a much reduced impact on the plan cost, and helps alleviate some investments which were needed with uncontrolled charging PEVs. Therefore, the LDCs and policy makers need to encourage customers to adapt these options in the long-run. [ABSTRACT FROM AUTHOR]

Electric power systems are facing major challenges because of the increase in penetration of energy resources (ERs). This paper focuses on composite system reliability based planning for ERs, and presents novel clustering techniques based approaches to determine the optimal location, size and year of installation of ERs in the system. The K-means clustering and Fuzzy C-means clustering techniques are applied to the set of reliability indices, Load Not Served per Interruption (LNSI), which are determined using nodal minimal cut sets. The nodal minimal cut sets are obtained using an optimal power flow (OPF) based approach in this paper. Once the optimal sizes and locations of ERs are obtained, the earliest year of penetration is determined using an adequacy check algorithm. Detailed studies presented considering the IEEE RTS demonstrate the applicability of the proposed technique. [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 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 two mathematical formulations to represent uncertainties in self-scheduling models of a price-taker Compressed Air Energy Storage (CAES) facility. The proposed model is from the point of view of the plant owner participating in the energy, spinning, and idle reserve markets. The first described formulation is based on Robust Optimization (RO) and the second one is based on Affine Arithmetic (AA) techniques, which are both range arithmetic methodologies, and consider the thermodynamic characteristics of the CAES facility for a more realistic representation. The implementation of both methods are tested, validated and compared with each other and with Monte Carlo Simulations (MCS) using prices from the Ontario market. From the simulation results, it can be observed that both methods have some similarities, presenting lower computational burden compared with MCS, and demonstrate the advantage of applying the proposed models for CAES plant owners to hedge against price uncertainties. [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 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]

In this paper, a past-aware state estimation (PASE) method (for static state estimation) is proposed for power distribution systems, which takes previous estimates into account to improve the accuracy of the current one, using an Ensemble Kalman Filter (EnKF). Fewer phasor measurements units are needed to achieve the same estimation error target than snapshot-based methods. Furthermore, contrary to existing methods, the proposed approach does not embed power flow equations into the state estimator, thus making it a versatile technique. The theoretical formulation of the EnKF-based PASE presented in the paper has been validated considering a 33-bus distribution system and using power consumption traces from real households. [ABSTRACT FROM AUTHOR]

Demand Response (DR) is an important tool for Independent System Operators (ISO) for reliable operation of electricity markets, and there has been considerable interest from load-side market participants to offer their services for DR provisions. In this environment, the ISO needs to develop effective mathematical models for procurement of DR so as to maximize its benefits, such as reducing the peak demand, regulating electricity price shocks, and mitigating market power. In this paper, a new mathematical model for a Locational Marginal Price based, loss included, day-ahead, cooptimized, energy and spinning reserve market including DR provisions, is proposed. The proposed model includes a new proposition for load-side participants to submit price responsive demand (PRD) and load curtailment based DR bids simultaneously, in a unified market framework. Case studies considering DR providers participating in energy market only, in both energy and spinning reserve markets, and in spinning reserve market only, are presented, which examine the impact on system operation, market prices, and DR provider's benefits. The proposed model is tested on the IEEE Reliability Test System to demonstrate its functionalities and the results clearly justify the merits of simultaneous consideration of PRD bids and load curtailment based DR offers in a cooptimized energy and spinning reserve market. [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]

An affine arithmetic (AA) method is proposed in this paper to solve the optimal power flow (OPF) problem with uncertain generation sources. In the AA-based OPF problem, all the state and control variables are treated in affine form, comprising a center value and the corresponding noise magnitudes, to represent forecast, model error, and other sources of uncertainty without the need to assume a probability density function (pdf). The proposed AA-based OPF problem is used to determine the operating margins of the thermal generators in systems with uncertain wind and solar generation dispatch. The AA-based approach is benchmarked against Monte Carlo simulation (MCS) intervals in order to determine its effectiveness. The proposed technique is tested and demonstrated on the IEEE 30-bus system and also a real 1211-bus European system. [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]

This paper describes the development of a freeware smart residential load simulator to facilitate the study of residential energy management systems in smart grids. The proposed tool is based on MATLAB-Simulink-GUIDE toolboxes and provides a complete set of user-friendly graphical interfaces to properly model and study smart thermostats, air conditioners, furnaces, water heaters, stoves, dishwashers, cloth washers, dryers, lights, pool pumps, and refrigerators, whose models are validated with actual measurements. Wind and solar power generation as well as battery sources are also modeled, and the impact of different variables, such as ambient temperature and household activity levels, which considerably contribute to energy consumption, are considered. The proposed simulator allows modeling of appliances to obtain their power demand profiles, thus helping to determine their contribution to peak demand, and allowing the calculation of their individual and total energy consumption and costs. In addition, the value and impact of generated power by residential sources can be determined for a 24-h horizon. This freeware platform is a useful tool for researchers and educators to validate and demonstrate models for energy management and optimization, and can also be used by residential customers to model and understand energy consumption profiles in households. Some simulation results are presented to demonstrate the performance and application of the proposed simulator. [ABSTRACT FROM AUTHOR]

With the increasing importance of battery energy storage systems (BESS) in microgrids, accurate modeling plays a key role in understanding their behavior. This paper investigates and compares the performance of BESS models with different depths of detail. Specifically, several models are examined: an average model represented by voltage sources; an ideal dc source behind a voltage source converter; a back-to-back buck/boost and bidirectional three-phase converter, with all models sharing the same control system and parameters; and two additional proposed models where the switches are replaced by dependent sources to help analyze the differences observed in the performance of the models. All these models are developed in PSCAD and their performances are simulated and compared considering various issues such as voltage and frequency stability and total harmonic distortion in a benchmark test microgrid. It is shown through simulation results and eigenvalue studies that the proposed models can exhibit a different performance, especially when the system is heavily loaded, highlighting the need for more accurate modeling under certain microgrid conditions. [ABSTRACT FROM AUTHOR]

Although electric power networks and district heating networks are physically coupled, they are not operated in a coordinated manner. With increasing penetration of renewable energy sources, a coordinated market-based operation of the two networks can yield significant advantages, as reduced need for grid reinforcements, by optimizing the power flows in the coupled systems. Transactive control has been developed as a promising approach based on market and control mechanisms to coordinate supply and demand in energy systems, which when applied to power systems is being referred to as transactive energy. However, this approach has not been fully investigated in the context of market-based operation of coupled electric power and district heating networks. Therefore, this paper proposes a transactive control approach to coordinate flexible producers and consumers while taking into account the operational aspects of both networks, for the benefit of all participants and considering their privacy. A nonlinear model predictive control approach is applied in this work to maximize the social welfare of both networks, taking into account system operational limits, while reducing losses and considering system dynamics and forecasted power supply and demand of inflexible producers and consumers. A subtle approximation of the operational optimization problem is used to enable the practical application of the proposed approach in real time. The presented technique is implemented, tested, and demonstrated in a realistic test system, illustrating its benefits. • Transactive control design for coupled electric power and district heating networks. • Development and application of an accurate and computationally efficient system model. • Technical and economic optimal system operation considering participant privacy. [ABSTRACT FROM AUTHOR]