Energy storage is a unique grid asset in that it is capable of providing a number of grid services. In market areas, these grid services are only as valuable as the market prices for the services provided. This paper formulates the optimization problem for maximizing energy storage revenue from arbitrage (day-ahead and real-time markets) in the California Independent System Operator (CAISO) market. The optimization algorithm was then applied to three years of historical market data (2014-2016) at 2200 nodes to quantify the locational and time-varying nature of potential revenue. The optimization assumed perfect foresight, so it provides an upper bound on the maximum expected revenue. Since California is starting to experience negative locational marginal prices (LMPs) because of increased renewable generation, the optimization includes a duty cycle constraint to handle negative LMPs. Two additional trading algorithms were tested that do not require perfect foresight. The first sets a buy price threshold and a sell price threshold (e.g., limit orders) for participation in the real time market, subject to the constraints of the energy storage system. The second uses the day-ahead prices as an estimate for the real time prices and performs an optimization on a rolling time horizon. The simple threshold algorithm performed the best, but both fell well short of the potential revenue identified by the optimization with perfect foresight.
FERC Order 755 requires RTO/ISOs to compensate the frequency regulation resources based on the actual regulation service provided. Based on this rule, a resource is compensated by a performance-based payment including a capacity payment which accounts for its provided regulation capacity and a performance payment which reflects the quantity and accuracy of its regulation service. The RTO/ISOs have been implementing different market rules to comply with FERC Order 755. This paper focuses on the MISO's implementation and presents the calculations to maximize the potential revenue of electrical energy storage (EES) from participation in arbitrage and frequency regulation in the day-ahead market using linear programming. A case study was conducted for the Indianapolis Power & Light's 20MW/20MWh EES at Harding Street Generation Station based on MISO historical data from 2014 and 2015. The results showed the maximum revenue was primarily produced by frequency regulation.
Distributed control compensation based on local and remote sensor feedback can improve small-signal stability in large distributed systems, such as electric power systems. Long distance remote measurements, however, are potentially subject to relatively long and uncertain network latencies. In this work, the issue of asymmetrical network latencies is considered for an active damping application in a two-area electric power system. The combined effects of latency and gain are evaluated in time domain simulation and in analysis using root-locus and the maximum singular value of the input sensitivity function. The results aid in quantifying the effects of network latencies and gain on system stability and disturbance rejection.
This letter presents a new frequency control strategy that takes advantage of communications and fast responding resources such as photovoltaic generation, energy storage, wind generation, and demand response, termed collectively as converter interfaced generators (CIGs). The proposed approach uses an active monitoring of power imbalances to rapidly redispatch CIGs. This approach differs from previously proposed frequency control schemes in that it employs feed-forward control based on a measured power imbalance rather than relying on a frequency measurement. Time-domain simulations of the full Western Electricity Coordinating Council system are conducted to demonstrate the effectiveness of the proposed method, showing improved performance.
This paper proposes a method to modulate the power output of converter interfaced generators (CIGs) according to frequency variations. With the proposed approach, CIGs can successfully engage in the primary frequency regulation of a power system. The approach is a variation on the traditional droop-like proportional controller where the feedback signal is a global frequency measurement instead of a local one. Obtaining the global measurement requires transferring data using communications. This paper analyzes the performance of the proposed approach with respect to communications issues such as latencies and data dropouts. The approach implemented and tested in a simulation environment is compared against a method entirely based on local information. The results show that using global information in droop control provides benefits to the system as it improves its frequency regulation. The results also indicate that the proposed approach is robust to latencies and communication failures.
This paper proposes a method of enabling photovoltaic (PV) power plants to participate in primary frequency response by providing synthetic inertia (SI). This variation, referred to as communication enabled synthetic inertia (CE-SI), utilizes communication capabilities to provide global system frequency information to PV plants to emulate the inertial response of synchronous generators. The performance of CE-SI is analyzed with respect to the challenges associated with communication, such as latency and availability. Results indicate improvements in frequency response over SI using local frequency measurements when communication latency is sufficiently small.
The goal of this effort was to assess the effect of high penetration solar deployment on the small signal stability of the western North American power system (wNAPS). Small signal stability is concerned with the system response to small disturbances, where the system is operating in a linear region. The study area consisted of the region governed by the Western Electricity Coordinating Council (WECC). General Electric's Positive Sequence Load Flow software (PSLF®) was employed to simulate the power system. A resistive brake insertion was employed to stimulate the system. The data was then analyzed in MATLAB® using subspace methods (Eigensystem Realization Algorithm). Two different WECC base cases were analyzed: 2022 light spring and 2016 heavy summer. Each base case was also modified to increase the percentage of wind and solar. In order to keep power flows the same, the modified cases replaced conventional generation with renewable generation. The replacements were performed on a regional basis so that solar and wind were placed in suitable locations. The main finding was that increased renewable penetration increases the frequency of inter-area modes, with minimal impact on damping. The slight increase in mode frequency was consistent with the loss of inertia as conventional generation is replaced with wind and solar. Then, distributed control of renewable generation was assessed as a potential mitigation, along with an analysis of the impact of communications latency on the distributed control algorithms.
FERC order 755 and FERC order 784 provide pay-for-performance requirements and direct utilities and independent system operators to consider speed and accuracy when purchasing frequency regulation. Independent System Operators (ISOs) have differing implementations of pay-for-performance. This paper focuses on the PJM implementation. PJM is a regional transmission organization in the northeastern United States that serves 13 states and the District of Columbia. PJM's implementation employs a two part payment based on the Regulation Market Capability Clearing price (RMCCP) and the Regulation Market Performance Clearing Price (RMPCP). The performance credit includes a mileage ratio. Both the RMCCP and RMPCP employ an actual performance score. Using the PJM remuneration model, this paper outlines the calculations required to estimate the maximum potential revenue from participation in arbitrage and regulation in day-ahead markets using linear programming. Historical PJM data from 2014 and 2015 was then used to evaluate the maximum potential revenue from a 5 MWh, 20 MW system based on the Beacon Power Hazle Township flywheel plant. Finally, a heuristic trading algorithm that does not require perfect foresight was evaluated against the results of the optimization algorithm.
The uncontrolled intermittent availability of renewable energy sources makes integration of such devices into today's grid a challenge. Thus, it is imperative that dynamic simulation tools used to analyze power system performance are able to support systems with high amounts of photovoltaic (PV) generation. Additionally, simulation durations expanding beyond minutes into hours must be supported. This paper aims to identify the path forward for dynamic simulation tools to accommodate these needs by characterizing the properties of power systems (with high PV penetration), analyzing how these properties affect dynamic simulation software, and offering solutions for potential problems. In particular, the system eigenvalue configuration of representative power system models is examined and how this configuration influences numerical integration scheme selection is discussed.
The uncontrolled intermittent availability of renewable energy sources makes integration of such devices into today's grid a challenge. Thus, it is imperative that dynamic simulation tools used to analyze power system performance are able to support systems with high amounts of photovoltaic (PV) generation. Additionally, simulation durations expanding beyond minutes into hours must be supported. This report aims to identify the path forward for dynamic simulation tools to accom- modate these needs by characterizing the properties of power systems (with high PV penetration), analyzing how these properties affect dynamic simulation software, and offering solutions for po- tential problems. We present a study of fixed time step, explicit numerical integration schemes that may be more suitable for these goals, based on identified requirements for simulating high PV penetration systems. We also present the alternative of variable time step integration. To help determine the characteristics of systems with high PV generation, we performed small signal sta- bility studies and time domain simulations of two representative systems. Along with feedback from stakeholders and vendors, we identify the current gaps in power system modeling including fast and slow dynamics and propose a new simulation framework to improve our ability to model and simulate longer-term dynamics.
This project aimed to identify the path forward for dynamic simulation tools to accommodate these needs by characterizing the properties of power systems (with high PV penetration), analyzing how these properties affect dynamic simulation software, and offering solutions for potential problems.