With the goal of electricity system decarbonization, conventional synchronous generators are gradually replaced by converter-interfaced renewable generations. Such transition is causing concerns over system frequency and rate-of-change-of-frequency (RoCoF) security due to significant reduction in system inertia. Existing efforts are mostly derived from uniform system frequency response model which may fail to capture all characteristics of the systems. To ensure the locational frequency security, this paper presents a deep neural network (DNN) based RoCoF-constrained unit commitment (DNN-RCUC) model. RoCoF predictor is trained to predict the highest locational RoCoF based on a high-fidelity simulation dataset. Training samples are generated from models over various scenarios, which can avoid simulation divergence and system instability. The trained network is then reformulated into a set of mixed-integer linear constraints representing the locational RoCoF-limiting constraints in unit commitment. The proposed DNN-RCUC model is studied on the IEEE 24-bus system. Time domain simulation results on PSS/E demonstrate the effectiveness of the proposed algorithm.
With increasing installation of wind and solar generation, conventional synchronous generators in power systems are gradually displaced resulting in a significant reduction in system inertia. Maintaining system frequency within acceptable ranges becomes more critical for the stability of a power system. In this paper, we first study the impact of inter-area oscillations on the system rate-of-change-of-frequency (RoCoF) security; then, the limitations on locational RoCoFs accounting for G-1 contingency stability are derived. By enforcing these frequency related constraints, a location based RoC…
This paper evaluates the frequency performance of an AC system when primary frequency response is provided by inverter-based resources located at remote-areas. Due to potentially larger wave propagation constants over longer lines, fast active power response from inverter based resources may have a negative impact on the system frequency response. Within this context, this paper presents a control performance analysis is presented in order to identify limitations for improving the frequency stability when inverter-based resources in remote locations use local frequency measurements. Our result…
Conventional synchronous generators are gradually being replaced by inverter-based resources, such transition introduces more complicated operation conditions. And the reduction in system inertia imposes challenges for system operators on maintaining system rate-of-change-of-frequency (RoCoF) security. This paper presents a selectively linearized neural network (SNLNN) based RoCoF-constrained unit commitment (SLNN-RCUC) model. A RoCoF predictor is first trained to predict the system wide highest locational RoCoF based on a high-fidelity simulation dataset. Instead of incorporating the complete…
Large-scale integration of renewable energy sources (RES) brings huge challenges to the power system. A cost-effective reserve deployment and uncertainty pricing mechanism are critical to deal with the uncertainty and variability of RES. To this end, this paper proposes a novel locational marginal pricing mechanism in day-ahead market for managing uncertainties from RES. Firstly, an improved multi-ellipsoidal uncertainty set (IMEUS) considering the temporal correlation and conditional correlation of wind power forecast is formulated to better capture the uncertainty of wind power. The dimensio…
If a disturbance rocks a low-inertia power system, the frequency decline may be too rapid to arrest before it triggers undesirable responses from generators and loads. In the worst case, this instability could lead to blackout and major equipment damage. Electric utilities, to combat this, study inertia adequacy in systems that are particularly vulnerable. This process, involving detailed transient simulations, usually leads to a notion of a system-wide inertia floor. Ongoing questions in this analysis are in how to set the inertial floor and to what extent the location of frequency control re…
In Part I of this paper we have introduced the closed-form conditions for guaranteeing regional frequency stability in a power system. Here we propose a methodology to represent these conditions in the form of linear constraints and demonstrate their applicability by implementing them in a generation-scheduling model. This model simultaneously optimises energy production and ancillary services for maintaining frequency stability in the event of a generation outage, by solving a frequency-secured Stochastic Unit Commitment (SUC). We consider the Great Britain system, characterised by two region…
The relevant integration of wind power into the grid has involved a remarkable impact on power system operation, mainly in terms of security and reliability due to the inherent loss of the rotational inertia as a consequence of such new generation units decoupled from the grid. In these weak scenarios, the contribution of wind turbines to frequency control is considered as a suitable solution to improve system stability. With regard to frequency response analysis and grid stability, most contributions introduce wind control discuss generation tripping for isolated power systems under arbitrary…
On the path towards power systems with high renewable penetrations and ultimately carbon-neutral, more and more synchronous generation is being displaced by variable renewable generation that does not currently provide system inertia nor reactive power support. This could create serious issues of power system stability in the near future, and countries with high renewable penetrations such as Ireland are already facing these challenges. Therefore, this paper aims at answering the questions of whether and how explicitly including inertia and reactive power constraints in generation expansion pl…
The objective-based forecasting considers the asymmetric and non-linear impacts of forecasting errors on decision objectives, thus improving the effectiveness of its downstream decision-making process. However, existing objective-based forecasting methods are risk-neutral and not suitable for tasks like power system inertia management and unit commitment, of which decision-makers are usually biased toward risk aversion in practice. To tackle this problem, this paper proposes a generic risk-aware objective-based forecasting method. It enables decision-makers to customize their forecasting with …
Most renewable energy sources (RES) do not provide any inertial response. Their integration in a power grid implies a highly reduced level of system inertia, which leads to a deteriorated frequency performance. Then, the requirement for frequency response is significantly increased in order to maintain frequency security. Alternatively, enhanced provision of inertia from auxiliary sources may alleviate this problem. However, the benefits of inertia provision are not yet fully understood. In this paper, an inertia-dependent Stochastic Unit Commitment (SUC) tool is applied to quantify the econom…
This paper studies the procurement and pricing of inertial response using a frequency-constrained unit commitment formulation, which co-optimizes the provision of energy and inertia services while accounting for their complementary properties. The proposed approach builds on a two-step process that allows to differentiate between the units being online for energy purposes and the ones committed additionally solely for inertia provision. Subsequently, three novel pricing and payment schemes that reimburse inertia providers in a transparent and fair manner according to their individual participa…
Given the increasing penetration in renewable generation, the UK power system is experiencing a decline in system inertia and an increase in frequency response (FR) requirements. Faster FR products are a mitigating solution that can cost-effectively meet the system balancing requirements. Thus, this paper proposes a mixed integer linear programming (MILP) unit commitment model which can simultaneously schedule inertial response, mandatory FR, as well as a sub-second FR product - enhanced frequency response (EFR). The model quantifies the value of providing faster reacting FR products in compar…
Power systems are shifted from conventional bulk generation toward renewable generation. This trend leads to the frequency security problem due to the decline of system inertia. On the other hand, natural gas-fired units are frequently scheduled to provide operational flexibility due to their fast adjustment ability. The interdependence between power and natural gas systems is thus intensified. In this paper, we study the frequency constrained scheduling problem from the perspective of an integrated electricity-gas system under variable wind power. We propose a distributionally robust (DR) cha…
University of Arizona（亚利桑那大学）；New York University（纽约大学）
This paper seeks to design a machine learning twin of the optimal power flow (OPF) optimization, which is used in market-clearing procedures by wholesale electricity markets. The motivation for the proposed approach stems from the need to obtain the digital twin, which is much faster than the original, while also being sufficiently accurate and producing consistent generation dispatches and locational marginal prices (LMPs), which are primal and dual solutions of the OPF optimization, respectively. Availability of market-clearing tools based on this approach will enable computationally tractab…
