Flexible Ramping Products Research Articles

Distributed optimization for EVs integrated power system considering flexible ramping requirement

More flexible ramping service is required due to the increase of renewable power generation in power systems. Electric vehicles (EVs) could provide such flexible ramping products (FRPs) at low cost while participating in the electricity market through aggregation. However, EVs’ dispatching capability cannot be fully utilized without the right incentives. This paper addresses a distributed optimal model developed between EV aggregators (EVAs) and the independent system operator (ISO). To make such concept, a cloud-edge collaborated market structure is adopted. At the edge level, EVAs assess the dispatching capability and solve the market bidding subproblem. At the cloud level, ISO solves the market clearing subproblem considering system economy and security. The overall problem is solved by the analytical target cascading (ATC) method. Heuristic constraints are also introduced into the model to improve convergence performance. The model is tested on a modified IEEE 30-bus system. Results demonstrate that the proposed method can incentivize EVAs with different owners to shift load and provide FRPs accurately, meanwhile reducing the cost and increasing the consumption of renewable energy effectively.

A Joint Electricity Market-Clearing Mechanism for Flexible Ramping Products with a Convex Spot Market Model

A high proportion of renewable energy access makes the net load of the power system volatile and uncertain, increasing the demand for the ramping capacity of the power system. Traditional electricity spot markets compensate for the power imbalances caused by an insufficient ramping capacity through traditional flexibility services such as ancillary services and interconnection power. However, conventional flexibility services may lead to frequency deviations in the power system, increased response costs, spikes in electricity prices, and dramatic price volatility in the traditional spot market. To solve the above problems, this paper proposes an FRP and convex electricity spot market joint clearing (FCESMJC) market mechanism. The FCESMJC model can more accurately represent the relationship between electrical power output and the price of electricity and reduces the number of spikes in electricity prices. In addition, a novel FRP pricing method is proposed to compensate FRP market participants for their FRP costs more reasonably. Additionally, the difference in system performance is provided by comparing the energy prices, pricing method, clearing prices, and system costs in the FCESMJC method and the traditional electricity spot market. The FCESMJC system reduces the total system cost by 18.6% compared with the electricity spot market. Numerical experiments are simulated on the IEEE 14-bus test system to validate the superiority of the proposed model.

Network-constrained flexible ramping product provision of prosumer aggregator: a data-driven stochastic bi-level optimization

Prosumers are expected to provide the flexible ramping product (FRP) in the power system. However, voltage violations and line congestion may arise in the distribution network, when FRP delivered by prosumers. Hence, this paper proposes a data-driven stochastic bi-level optimization model to coordinate the prosumer aggregator to decide FRP-offering while ensuring distribution network security under FRP delivery. In the proposed bi-level model, the upper-level is a min-max problem, representing the minimum expected cost under the worst-case scenario probability distribution for the prosumer aggregator. The lower-level is the operation cost minimization within the distribution network security for distribution network operator. The proposed model is converted into a single-level model using the Karush-Kuhn-Tucker condition and strong duality theory, and applied to the modified IEEE 33-bus network with three prosumers. The results demonstrate the effectiveness of the proposed model.

Multi-Time-Scale Rolling Optimal Scheduling of Virtual Power Plants in Energy and Flexible Ramping Product Markets

Virtual power plants (VPPs) offer a feasible solution for integrating various types of distributed energy resources (DERs) into the power grid in the electricity market. This paper proposes a multi-time-scale rolling optimal scheduling for VPPs, enabling optimal self-scheduling plans across intra-week rolling scheduling, intra-day rolling dispatch, and real-time dispatch. The proposed method facilitates participation in energy and flexible ramping product (FRP) markets while considering the specific characteristics with complementary advantages for the aggregated renewable resources, gas turbines, energy storages, and flexible demands of each time scale. The flexible ramping products within the VPP framework are established, while the energy storage systems address fluctuations during dispatch periods. Case studies are conducted to verify the efficiency of the proposed method. The results show that the proposed method can obtain optimal self-scheduling plans within the multi-time framework and has better performance in economy and security operation in comparisons among cases.

Power-Gas Coordination: Making Flexible Ramping Products Feasible

The power industry has introduced flexible ramping products (FRPs) to improve the operational flexibility that high penetration of renewables requires. However, FRPs are mainly provided by natural-gas-fired power generators, whose capability to provide ramping service is determined by the operational conditions of the natural gas system. We develop a power-gas coordination model that takes into account FRP requirement. Specifically, the power market represents the required energy-FRP co-optimization, while the natural-gas market is settled considering FRP-deployment gas constraints. A Lagrangian coordination scheme is used to identify a market equilibrium involving the two markets that are settled separately. Computations results on two test systems examine the impact of gas-system operating constraints on the delivery of FRPs. Additionally, sensitivity analyses with respect to gas-network bottlenecks, FRP price caps, and renewable penetration levels are presented.

Coordinating flexible ramping products with dynamics of the natural gas network

In electricity networks with high penetration levels of renewable resources, Flexible Ramping Products (FRPs) are among the utilized measures for dealing with the potential fluctuations in the net demand. This paper investigates the coordinated operation of Integrated Electricity-Gas Systems (IEGSs) with considering FRPs. To accurately model and reflect the effects of variations in the natural gas fuel demand on the natural gas network, a dynamic Optimal Gas Flow (OGF) formulation is utilized. The non-convex dynamic model of the natural gas system is represented in a convex form via a tight relaxation scheme. An improved distributed optimization method is proposed to solve the coordinated operation problem in a privacy-preserving manner, where the two infrastructures only share limited information. We introduce the Inexact Varying Alternating Direction Method of Multipliers (IV-ADMM) and show that compared with the classic ADMM, it converges considerably faster and in fewer iterations. Through a comparison of day-ahead and real-time operation planning results, it is concluded that without accounting for natural gas network dynamics, the FRP model is not a trustworthy tool in day-ahead planning against uncertainties.

Distributionally robust comprehensive declaration strategy of virtual power plant participating in the power market considering flexible ramping product and uncertainties

The volatility and randomness of renewable energy output make the flexible ramping ability demand of power system more urgent, and flexible ramping product (FRP) can effectively improve the flexibility of the power system. Virtual power plant (VPP) can regulate distributed generation, which is conducive to the regulation potential of flexible resources. To solve the problems of FRP and electric energy markets synergy and the wind power output uncertainty faced by the VPP in the declaration process, this paper proposes a comprehensive declaration strategy for the VPP to participate in the power market considering FRP and uncertainties. Firstly, this paper designs a synergistic trading mode covering flexibility resource demand determination and the virtual bidding curve formation for electric energy and FRP markets, in which the virtual bidding curve can reasonably compensate for the unit opportunity cost. Secondly, a comprehensive declaration-dispatching strategy decision-making model for VPP is constructed, and a two-stage distributed robust optimization (DRO) technology is used to deal with the wind power output uncertainty in the model, and flexible resources such as energy storage are used to mitigate energy deviation in the VPP. Finally, simulations implemented on a typical VPP are delivered to show that: 1) Virtual bidding curve realizes the accurate compensation for the units providing FRP. 2) Compared with the single market, VPP can increase the expected profit by 20.44% and reduce wind curtailment cost by 59.68% in the joint declaration of multi-markets.3) VPP can effectively suppress output uncertainty through energy storage system. 4) DRO model has significant advantages in data-driven, less conservative results and stable running time.

Improving the flexibility of power systems using transportable battery, transmission switching, demand response, and flexible ramping product market in the presence of high wind power

AbstractWith the increasing demand for electricity and the significant growth of renewable energy sources (RES), especially wind power, the need for new services to increase system flexibility has increased more than ever. Flexibility services can enhance system security. This paper proposes a framework for enhancing system flexibility by integrating emerging services for running the day‐ahead energy, spinning, and flexible ramping product (FRP) markets, considering high wind power penetration. Due to the uncertainty of wind power production, this framework is presented as a stochastic network‐constraint unit commitment (NCUC) problem. The services that are implemented simultaneously in the problem include transmission switching (TS), demand response (DR) program, and transportable battery energy storage (TBES). Moreover, two new indices are introduced to evaluate the effects of flexibility services. Another contribution of this paper is performing comprehensive studies for comparing various case studies in normal and the worst contingency conditions of the network. The IEEE RTS‐79 test system is employed to approve the effectiveness of the proposed framework. The results of various case studies show that using emerging services together increases power grid flexibility and reduces system operating costs.

Provision of the Flexible Ramping Product in a microgrid considering the trading strategies in the energy markets

The Flexible Ramping Product (FRP) market has been created as a new ancillary service market for the power systems to manage the severe ramp rates in the net load of the system. Microgrids (MGs) can provide the required ramp service for this market. The MG manager (MGM) sends its bids to the FRP market. The mutual effects of these bids on the MGM trading strategies in the day-ahead (DA) and real-time (RT) energy markets have not been considered in the previous studies. For this purpose, a new formulation is developed in this paper to model the MGM decisions in the FRP market while participating in the DA and RT energy markets. Moreover, the uncertainty on the probability of bid acceptance in the FRP market is modeled in the MGM decision-making problem using the information gap decision theory approach. The results show that changing the MGM strategies in participating in the markets, the objective function of the MGM improves when it participates in the DA energy, FRP and RT energy market, in comparison with the cases in which the MGM does not participate in the FRP market or the RT energy market. Also, the results show how the risk-averse MGM changes its strategies to provide the ramp service for the FRP market to make its decisions robust against the uncertain parameter.

A transaction mechanism for flexible ramping products with the participation of hydropower

A transaction mechanism for flexible ramping products with the participation of hydropower

Day-ahead self-scheduling from risk-averse microgrid operators to provide reserves and flexible ramping ancillary services

In this paper, a new decision-making framework is proposed for the day-ahead self-scheduling problem of microgrids, in which the microgrid operator (MGO) can provide ancillary services for both the independent system operator (ISO) and the distribution system operator (DSO). The MGO provides the reserve and flexible ramping product (FRP) services for the ISO through participating in the corresponding markets. Also, the MGO reschedules its resources to provide the requested services for the DSO. To model the uncertain behavior of the renewable energy resource, demand, and real-time energy price, the MGO problem is modeled as a two-stage stochastic model. Then, the uncertainties of the reserve and the FRP deployment in real-time operation are modeled using the information gap decision theory approach. The results show the effects of the different strategies in scheduling the local resources adopted by the MGO to participate in the energy and ancillary service markets. In the risk-based model proposed for the MGO, increasing the risk parameter decreases the capacity of the provided reserve and ramp-up FRP while it increases the energy sold to the day-ahead energy market.

미국 내 다중 간격 실시간 시장 운영 및 가격 결정 방식 분석

With the increase of renewable energy in the power system, the volatility of net load and uncertainty in the power system continue to increase. This can increase the number of ramp events and supply and demand imbalances in the power system, which can lead to abnormal and inefficient operations such as price instability and price spikes in the power market. Accordingly, securing ramping capability to strengthen flexibility is becoming important. In this paper, we will look at the markets introduced by ISO, especially CAISO and NYISO in the United States to secure ramping up/down resources. MIRTM(multi-interval real time market) is a market based on real time unit commitment and look-ahead dispatch considering continuous time. MIRTM operation can reflect the volatility of the net load in economic dispatch, but there is a limit to reflecting shortterm uncertainty of net load, and there is an issue related to the uplift in determining electricity prices. It is analyzed that these limitations of MIRTM can be partially supplemented through the FRP(flexible ramping product) introduced by CAISO. The FRP is a product that ensures a 95% confidence interval for net load forecasting error in economic dispatch. Through FRP, pure energy prices and ramping related costs can be distinguished in MIRTM, and and it is analyzed that FRP can be a reasonable decision method to calculate the uplift in MIRTM.

Impact of implementing a price-based demand response program on the system reliability in security-constrained unit commitment problem coupled with wind farms in the presence of contingencies

Large scale penetration of highly intermittent wind energy sources has caused new challenges to the reliable operation of power systems. To address these challenges, demand response program is considered as an efficient solution to manage shift-able loads. In this paper, the impact of demand response on power system reliability has been evaluated by developing a two-stage stochastic security constraint unit commitment that considers both the wind volatility and line outages at the same time. The allocation of ramping products and spinning reserves to cover these uncertainties has also been modeled. wind curtailment and load shedding are considered as alternative strategies, and an optimal exchange between them and the use of spinning reserves and flexible ramping products has been modeled in the objective function. To assess the system reliability, the expected load not served (ELNS) index was evaluated in different cases. The proposed scheme as a mixed-integer linear programming problem was solved by a scenario-based two-stage stochastic programming method. The IEEE test systems 6-bus, modified 24-bus, and 118-bus were examined numerically. The results show that the simultaneous consideration of demand response and flexible ramping product coordinated with wind energy has adequate flexibility to reduce the reliability index and system operational cost.

Day-Ahead Operational Scheduling With Enhanced Flexible Ramping Product: Design and Analysis

New resource mix, e.g., renewable resources, are imposing operational complexities to modern power systems by intensifying uncertainty and variability in the system net load. This issue has motivated independent system operators (ISOs), e.g., California ISO (CAISO), to add flexible ramping products (FRPs) to their day-ahead (DA) market models. Such structural changes in the DA market formulation require further analyses and detailed design to ensure adequate operational flexibility, market efficiency, and reliability. This paper conducts a comprehensive study to: (a) augment existing DA market models with enhanced FRP design to schedule ramp capabilities that are more adaptive with respect to the real-time (RT) 15-min net load variability and uncertainty, and (b) design corresponding market payment policies that accurately reflect the value of the added flexibility through enhanced FRP design. The proposed FRP design can be implemented in present-day system operations with minimal disruption to existing DA market models. Performance of the proposed DA market model, which includes the enhanced FRP design, is compared against the DA market model with existing FRP design through a validation methodology based on RT unit commitment model. This validation methodology mimics fifteen-minute markets of CAISO. The proposed method is tested on an IEEE 118-bus test system.

Enhanced Flexible Ramping Product Formulation for Alleviating Capacity Shortage in Look-ahead Commitment

The roll-out of a flexible ramping product provides independent system operators (ISOs) with the ability to address the issues of ramping capacity shortage. ISOs procure flexible ramping capability by committing more generating units or reserving a certain amount of headrooms of committed units. In this paper, we raise the concern of the possibility that the procured flexible ramping capability cannot be deployed in real-time operations due to the unit shut-down in a look-ahead commitment (LAC) procedure. As a solution to the issues of ramping capacity shortage, we provide a modified ramping product formulation designed to improve the reliability and reduce the expected operating cost. The trajectories of start-up and shutdown processes are also considered in determining the ramping capability. A new optimization problem is formulated using mixed integer linear programming (MILP) to be readily applied to the practical power system operation. The performance of this proposed method is verified through simulations using a small-scale system and IEEE 118-bus system. The simulation results demonstrate that the proposed method can improve the generation scheduling by alleviating the ramping capacity shortages.

Application of flexible ramping products with allocation rates in microgrid utilizing electric vehicles

Microgrids account for a relatively high proportion of renewable energy utilization. Therefore, an operation method that ensures flexible resources to cope with the variability and uncertainty in renewable energy is indispensable for microgrid operators (MGOs). Here, we focus on the necessity of an optimal generation scheduling model for MGOs by considering flexible resources, namely flexible ramping products (FRPs). We propose a microgrid scheduling model including a method of utilizing electric vehicles (EVs) as a flexible resources and an operation method to secure FRPs in microgrids by applying allocation indices. The states and available capacities of EVs during each period are estimated using a Markov chain. The net load scenarios, which are considered as the target for the supply–demand balancing in the proposed method, are generated considering the uncertainty in forecasting load and renewable energy. The effectiveness and merits of the proposed model are validated through experiments on a microgrid test system that allows transactions between utilities through the tie-line. The results confirm that the proposed optimal generation scheduling model affords a reduction in microgrid operating costs and enables the stabilization of variability.

Portfolio management for a wind‐storage system based on distributionally robust optimisation considering a flexible ramping product

A wind-storage system (WSS) can use the synergy between wind farms and battery storages to mitigate the uncertainty of wind. With the flexible ramping capability of battery storages, a WSS can diversify its portfolio by selling energy, committing regulation services and offering flexible ramping products in a power market. The portfolio management problem of a WSS is studied here. The uncertainties of market prices and wind power are considered. In order to maximise the expected profit in the worst case, a distributionally robust optimisation model is proposed. The model is then reformulated as a solvable semidefinite optimisation problem. Real market data are used in the simulation, which validates the proposed method.

Enhancing electricity market flexibility by deploying ancillary services for flexible ramping product procurement

The escalated penetration of wind energy in the electric industry has by large contributed to an intensified uncertainty and variability of the net-load, i.e., the difference between stochastic demand and intermittent supply. In response, some Independent System Operators (ISOs) have recently introduced the Flexible Ramping Product (FRP) to heighten the grid flexibility via effective hosting of the uncertain renewables. This paper suggests a novel framework for optimal FRP provision in real-time markets (RTM) in which the shortage in the RTM ramp capacity is compensated by optimal deployment of day-ahead procured spinning reserve. In the envisioned mechanism, the ISO can deploy specific portions of the spinning reserve capacity as the FRP price increases. On this basis, a new optimization algorithm is formulated that can best capture the joint ability of ESSs and thermal generating units in providing FRP in the RTM. The proposed model is numerically investigated on the IEEE 118-bus test system, where it reveals its efficacy and applicability in load curtailment reduction.

Dual-timescale generation scheduling with nondeterministic flexiramp including demand response and energy storage

Increased grid-connected wind power generation results in net load with higher volatility as well as larger ramping requirements. It is becoming imperative to provide flexible ramping products (flexiramp) for better generation / load alignment and smoother wind power integration. This paper advocates a non-deterministic flexiramp modeling approach devised in a hybrid stochastic / deterministic dual-timescale framework. The latter uses a day-ahead chance-constrained scheduling formulation along with a deterministic real-time online rolling scheduling model, to facilitate the procurement of flexiramp products in the two timescales. Demand response and energy storage are implemented and quantified as additional flexiramp product. Flexiramp reserve is introduced, to ensure sufficient flexiramp capacity throughout the timescales. To reduce the wear and tear of generators and consider the operational and maintenance costs in the proposed framework, cycling ramping (cycliramp) cost is subsumed as a penalty in the day-ahead objective function. Simulations are carried out for the 24-bus and 118-bus systems. Numerical results highlight the efficacy of the proposed generation scheduling models, along with the impact of contemplating flexiramp and cycliramp cost components in the dual-timescale scheduling approach.

Advanced bidding strategy for participation of energy storage systems in joint energy and flexible ramping product market

Recently, power system operators have initiated procurement of a new service in electricity markets named flexible ramping product (FRP). With the main goal of enhancing the grid flexibility, this product can provide a remarkable opportunity for an enhanced short-term profitability. Energy storage systems (ESSs) with high ramping capability can leverage their profitability when properly participating in this market. This study introduces a stochastic optimisation framework for participation of ESSs in the FRP market. The proposed model formulates the optimal bidding strategy of ESSs considering the real-time energy, flexible ramp-up and ramp-down marginal price signals and the associated uncertainties. In addition, as the market participants cannot directly submit bids for the FRP, the corresponding energy bidding adjustments required to award the proper FRP amounts are elaborated. The mathematical model is linearised and its application in real-time market is investigated. The proposed framework is numerically analysed through which its effectiveness on enhancing the ESS profitability in the real-time electricity markets is verified.