To address the environmental concern and improve the economic efficiency, the wind power is rapidly integrated into smart grids. However, the inherent uncertainty of wind energy raises operational challenges. To ensure the cost-efficient, reliable and robust operation, it is critically important to find the optimal decision that can correctly and rigorously hedge against all sources of uncertainty. In this paper, we propose data-driven stochastic unit commitment (SUC) to guide the power grids scheduling. Specifically, given the finite historical data, the posterior predictive distribution is developed to quantify the wind power prediction uncertainty accounting for both inherent stochastic uncertainty of wind power generation and input model estimation error. For complex power grid systems, a finite number of scenarios is used to estimate the expected cost in the planning horizon. To further control the impact of finite sampling error induced by using the sample average approximation (SAA), we propose a parallel computing based optimization solution methodology, which can quickly find the reliable optimal unit commitment decision hedging against various sources of uncertainty. The empirical study over six-bus and 118-bus systems demonstrates that our approach can provide more efficient and robust performance than the existing deterministic and stochastic unit commitment approaches.
This paper proposes a new concept called virtual inertia scheduling (VIS) to efficiently handle the high penetration of inverter-based resources (IBRs). VIS is an inertia management framework that targets security-constrained and economy-oriented inertia scheduling and generation dispatch of power systems with a large scale of renewable generations. Specifically, it schedules the proper power setting points and reserved capacities of both synchronous generators and IBRs, as well as the control modes and control parameters of IBRs to provide secure and cost-effective inertia support. First, a u…
Cascading failures have become a severe threat to interconnected modern power systems. The ultrahigh complexity of the interconnected networks is the main challenge toward the understanding and management of cascading failures. In addition, high penetration of wind power integration introduces large uncertainties and further complicates the problem into a massive scenario simulation problem. This paper proposes a framework that enables a fast cascading path searching under high penetration of wind power. In addition, we ease the computational burden by formulating the cascading path searching …
This paper proposes a new deep learning (DL) based model-free robust method for bulk system on-line load restoration with high penetration of wind power. Inspired by the iterative calculation of the two-stage robust load restoration model, the deep neural network (DNN) and deep convolutional neural network (CNN) are respectively designed to find the worst-case system condition of a load pickup decision and evaluate the corresponding security. In order to find the optimal result within a limited number of checks, a load pickup checklist generation (LPCG) algorithm is developed to ensure the opt…
The utilization of renewable energy sources (RESs) has become significant throughout the world especially over the last two decades. Although high-level RESs penetration reduces negative environmental impact compared to conventional fossil fuel based energy generation, control issues become more complex as well as total inertia to the system is significantly decreased due to removal of conventional synchronous generators. Some other technical issues, high uncertainties, low fault ride through capability, high fault current, low generation reserve, and low power quality, arise due to RESs integ…
The increasing demand of large scale wind integration in the conventional power system brings a lot of challenges. One of them is the stability of the power system when subjected to a large disturbance, such as a fault. This paper proposes a probabilistic risk-based framework for computing a global instability index, incorporating angle, voltage, and frequency stability, for a large disturbance. Moreover, the impact of high wind penetration on this index is also observed. Case studies and associated simulations are conducted on the IEEE 39-bus test system using DIgSILENT PowerFactory software.…
In this paper, a two-stage stochastic day-ahead (DA) scheduling model is proposed incorporating wind power units and compressed air energy storage (CAES) to clear a co-optimized energy and reserve market. The two-stage stochastic programming method is employed to deal with the wind power generation uncertain nature. A linearized AC optimal power flow (LAC-OPF) approach with consideration of network losses, reactive power, and voltage magnitude constraints is utilized in the proposed two-stage stochastic DA scheduling model. Using an engineering insight, a two-level LAC-OPF (TL-LAC-OPF) approac…
The undergoing transition from conventional to converter-interfaced renewable generation leads to significant challenges in maintaining frequency stability due to declining system inertia. In this paper, a novel control framework for Synthetic Inertia (SI) provision from Wind Turbines (WTs) is proposed, which eliminates the secondary frequency dip and allows the dynamics of SI from WTs to be analytically integrated into the system frequency dynamics. Furthermore, analytical system frequency constraints with SI provision from WTs are developed and incorporated into a stochastic system schedulin…
This work presents a suite of two optimisation models for the short-term scheduling and redispatch of a virtual power plant (VPP) composed of a wind farm and a Li-ion battery, that participates in the day-ahead energy and secondary regulation reserve markets of the Iberian electricity market. First, a two-stage stochastic mixed-integer linear programming model is used to obtain the VPP's generation and reserve schedule and the opportunity cost of the energy stored in the battery. The model has an hourly resolution and a look-ahead period beyond the markets' scheduling horizon and considers the…
This paper proposes a stochastic optimal preparation and resource allocation method for upcoming extreme weather events in distribution systems, which can assist utilities to achieve faster and more efficient post-event restoration. With the objective of maximizing served load and minimizing operation cost, this paper develops a two-stage stochastic mixed-integer linear programming (SMILP) model. The first-stage determines the optimal positions and numbers of mobile resources, fuel resources, and labor resources. The second-stage considers network operational constraints and repair crew schedu…
Islamic Azad University（伊斯兰阿扎德大学）；Iranian University of Science and Technology（伊朗科技大学）；Shiraz University of Technology（设拉子理工大学）；Electric reliability council of Texas（得克萨斯州电力可靠性委员会）
In terms of the operation of microgrids, optimal scheduling is a vital issue that must be taken into account. In this regard, this paper proposes an effective framework for optimal scheduling of renewable microgrids considering energy storage devices, wind turbines, micro turbines. Due to the nonlinearity and complexity of operation problems in microgrids, it is vital to use an accurate and robust optimization technique to efficiently solve this problem. To this end, in the proposed framework, the teacher learning-based optimization is utilized to efficiently solve the scheduling problem in th…
In order to prevent the potential frequency instability due to the high Power Electronics (PE) penetration under an unintentional islanding event, this paper presents a novel microgrid scheduling model which explicitly models the system frequency dynamics as well as the long/short term uncertainty associated with renewable energy resources and load. Synthetic Inertia (SI) control is applied to regulating the active power output of the Inverter-Based Generators (IBGs) to support the post-islanding frequency evaluation. The uncertainty associated with the noncritical load shedding is explicitly …
In this paper, we deal with the power regulation of tethered-wing systems and demonstrate advantages of variable-pitch control in mitigating the dynamic mechanical loads and power fluctuations. The proposed scheme is based on a strategy that maximizes the energy capture during low-speed wind and prevents overloads during the high-speed wind. To realize this strategy, we use a tether reeling-speed controller to track the optimal generator speed during low-speed wind and a MIMO speed-force controller for power limitation during high-speed wind. The controllers are synthesized using H-infinity me…
The All-Island power system (AIPS) of Ireland and Northern Ireland currently accommodates up to 75% of system non-synchronous penetration (SNSP) (e.g., wind). These unprecedented levels of renewable penetration challenge the operation of the power system. The AIPS is not always able to accommodate all of the available renewable generation due to binding operational and technical constraints. In this context, this paper analyses wind energy curtailment in the AIPS using actual data. It is found that there is a positive correlation between the installed wind capacity and curtailment levels, and …
Nonsynchronous generations such as photovoltaics (PVs) are expected to undermine bulk power systems (BPSs) frequency response at high penetration levels. Though the underlying mechanism has been relatively well understood, the accurate assessment and effective enhancement of the U.S. interconnections frequency response under extra-high PV penetration conditions remains an issue. In this paper, the industry-provided full-detail interconnection models were further validated by synchrophasor frequency measurements and realistically-projected PV geographic distribution information were used to dev…
Despite the promising outlook, the numerous economic and environmental benefits of offshore wind energy are still compromised by its high operations and maintenance (O&M) expenditures. On one hand, offshore-specific challenges such as site remoteness, harsh weather, transportation requirements, and production losses, significantly inflate the O&M costs relative to land-based wind farms. On the other hand, the uncertainties in weather conditions, asset degradation, and electricity prices largely constrain the farm operator's ability to identify the time windows at which maintenance is possible,…
The penetration of distributed energy resources (DERs) is increasing dramatically. Due to the uncertainty of DERs, the operation of the distribution system is facing higher risks and challenges. To overcome such challenges, a two-stage chance-constrained convex AC optimal power flow (ACOPF) model is proposed in this paper, which can increase the economic efficiency of distribution system operation and manage the intermittency of DERs. In the first stage, a convex second-order cone programming (SOCP)-based ACOPF model is proposed in which the detailed models and limitations of DER, namely, dema…
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…
Constant rise in energy consumption that comes with the population growth and introduction of new technologies has posed critical issues such as efficient energy management on the consumer side. That has elevated the importance of the use of renewable energy sources, particularly photovoltaic (PV) system and wind turbine. This work models and discusses design options based on the hybrid power system of grid and battery storage. The effects of installed capacity on renewable penetration (RP) and cost of electricity (COE) are investigated for each modality. For successful operation of hybrid pow…
Regarding the variability of renewable energy sources (RESs), especially in the operation time periods, their high penetration faces the net load pattern of the power system with a major ramp rate challenge. Although employing a market-based mechanism by the independent system operator (ISO) can address this challenge, it may not be possible to handle this challenge in all networks. In such networks, the required flexibility can be supplied by decreasing the ramp rate of the purchased power of distribution companies (Discos) from the market since their net load has an important impact on the s…
Examples of the different events affecting wind power fluctuations are shown.The behaviors and the responses of the Spanish power system and wind power plants experiencing such events were analyzed. Examples presented in this chapter show that some of the wind power integration issues are related to low-voltage ride-through. They are solved through strict grid code enforcement. Other solutions to manage the reserve power generation and the wind power fluctuations are also very important in order to achieve high levels of wind power penetration. In the Spanish case, this could require increasin…
Unit Commitment with N-1 Security and Wind Uncertainty
Texas A&M University（德克萨斯农工大学）；Massachusetts Institute of Technology（麻省理工学院）；ETH Zurich（苏黎世联邦理工学院）；Los Alamos National Laboratory（洛斯阿拉莫斯国家实验室）；Columbia University（哥伦比亚大学）
Due to the penetration of renewable energy resources and load deviation, uncertainty handling is one of the main challenges for power system; therefore the need for accurate decision-making in a power system under the penetration of uncertainties is essential. However, decision makers should use suitable methods for uncertainty management. In this chapter, some of the uncertainty modeling methods in power system studies are analyzed. At first, multiple uncertain parameters that the power system deals with are introduced, then some useful uncertainty modeling methods are introduced. To show the…
Virtual power plant (VPP) provides a flexible solution to distributed energy resources integration by aggregating renewable generation units, conventional power plants, energy storages, and flexible demands. This paper proposes a novel model for determining the optimal offering strategy in the day-ahead energy-reserve market and the optimal self-scheduling plan. It considers exogenous uncertainties (or called decision-independent uncertainties, DIUs) associated with market clearing prices and available wind power generation, as well as the endogenous uncertainties (or called decision-dependent…
In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area modes that are closely related to the system's inherent stability characteristics, a novel algorithm that leverages on recent advances in wide-area measurement systems (WAMSs) and ESS technologies is developed. It is shown that the proposed approach can smooth the wind power fluctuations in near real-time using a small additional ESS capacity and thus signifi…
In this report, we provide a technical sequence on tackling the solar PV and demand forecast as well as optimal scheduling problem proposed by the IEEE-CIS 3rd technical challenge on predict + optimize for activity and battery scheduling. Using the historical data provided by the organizers, a simple pre-processing approach with a rolling window was used to detect and replace invalid data points. Upon filling the missing values, advanced time-series forecasting techniques, namely tree-based methods and refined motif discovery, were employed to predict the baseload consumption on six different …
Emission-Aware Reinforcement Learning for Sustainable Electric Vehicle Charging and Carbon Dioxide Reduction Under Varying Renewable Penetration
organization= nasc Research, School of Computer Science \& IT, University College Cork , country = IE；organization= School of Computing, Engineering；Digital Technologies, Teesside University , country= UK；organization= International Energy Research Centre, Tyndall National Institute, Cork , country = IE；Radiation Technologies Group, CCDCU, Faculty of Engineering；Technology, Sunway University , country = Malaysia；organization= Department of Physics, College of Science, Korea University , country = Republic of Korea
We analyze the dynamics of the power grid with a high penetration of renewable energy sources using the ORNL-PSERC-Alaska (OPA) model. In particular we consider the power grid of the Balearic Islands with a high share of solar photovoltaic power as a case study. Day-to-day fluctuations of the solar generation and the use of storage are included in the model. Resilience is analyzed through the blackout distribution and performance is measured as the average fraction of the demand covered by solar power generation. We find that with the present consumption patterns and moderate storage, solar ge…
Operations and Maintenance (O&M) constitute a major contributor to offshore wind's cost of energy. Due to the harsh and remote environment in which offshore turbines operate, there has been a growing interest in opportunistic maintenance scheduling for offshore wind farms, wherein grouping maintenance tasks is incentivized at times of opportunity. Our survey of the literature, however, reveals that there is no unified consensus on what constitutes an "opportunity" for offshore maintenance. We therefore propose an opportunistic maintenance scheduling approach which defines an opportunity as eit…
In the context of transition towards cleaner and sustainable energy production, microgrids have become an effective way for tackling environmental pollution and energy crisis issues. With the increasing penetration of renewables, how to coordinate demand response and renewable generations is a critical and challenging issue in the field of microgrid scheduling. To this end, a bi-level scheduling model is put forward for isolated microgrids with consideration of multi-stakeholders in this paper, where the lower- and upper-level models respectively aim to the minimization of user cost and microg…
A whole-system, investment-optimising model has been used to examine the change in total cost of meeting demand for electricity when Smart Local Energy Systems (SLES) are deployed. Our assumption is that SLES, alongside their other features, enhance the flexibility of electricity consumption through demand-side response (DSR) and facilitate use of local energy storage. We find that with the flexibility of SLES present, variable renewables such as offshore wind can displace firm but more expensive low-carbon sources such as CCS. Considering a 100 gCO2/kWh emissions target in 2030, a 10% penetra…
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…
Lane Department of Computer Science and Electrical Engineering, West Virginia University（计算机科学与电气工程系，西弗吉尼亚大学）
Despite the relentless progress of deep learning models in analyzing the system conditions under cyber-physical events, their abilities are limited in the power system domain due to data availability issues, cost of data acquisition, and lack of interpretation and extrapolation for the data beyond the training windows. In addition, the integration of distributed energy resources (DERs) such as wind and solar generations increases the complexities and nonlinear nature of power systems. Therefore, an interpretable and reliable methodology is of utmost need to increase the confidence of power sys…
