Robust Security-constrained Unit Commitment Research Articles

Decentralized robust unit commitment for AC/DC interconnected power systems considering wind power uncertainty

The growing penetration of wind energy and the increasing AC/DC interconnections of regional power grids critically need to coordinate the multi-area unit commitment and reserve schedules. This paper proposes a decentralized robust optimization framework for the unit commitment and reserve allocation into bulk AC/DC interconnected systems. In the proposed framework, the scheduling problem is decomposed and handled by the analytical target cascading (ATC) technique. The upper-level master problem coordinates and updates the transmission plan of the high-voltage direct current (HVDC) tie-line. The lower-level regional sub-problems are formulated as robust security-constrained unit commitment models to co-optimize the generation and flexible reserve scheme in a parallel manner. The regional sub-problems precisely model the time-coupled flexible reserve supply of multiple flexible resources to cope with the wind power uncertainty and are solved by the column-and-constraint generation algorithm. Numerical simulations are conducted and comparative analysis is performed to validate the effectiveness and feasibility of the proposed framework.

Robust Pricing of Energy and Ancillary Services in Combined Electricity and Natural Gas Markets

Rapid growth of gas-fired generators strengthens the interdependency of electricity and natural gas markets. To meet the uncertainty challenge, a robust day-ahead market clearing framework for the integrated electricity and natural gas system (IEGS) is presented. First, a robust security-constrained unit commitment (SCUC) model is built considering the joint dispatch of ancillary services. Regulation-up/down reserve is scheduled to balance electrical load/wind power uncertainties, spinning reserve is to manage N-1 generator outage, and natural gas reserve is to withstand gas load uncertainty and provide fuel for gas-fired electrical reserve. The SCUC model is a two-stage mixed-integer nonlinear optimization problem so that a sequential linear approximation-based Column & Constraint Generation (SLA-based C&CG) algorithm is proposed. Then, according to SCUC solutions, an economic dispatch model is derived to obtain market clearing and pricing results. Based on locational marginal pricing, novel definitions of electrical energy, natural gas and multiple ancillary service prices are proposed, which can reflect network limits and uncertainty effects. Numerical cases on two test IEGSs and a provincial-level IEGS demonstrate the high accuracy of proposed SLA-based C&CG algorithm and the impact of uncertainties on market clearing.

Robust flexibility driven security constrained unit commitment under wind uncertainty considering demand response and combined-cycle units

Operational flexibility aiming to mitigate variability impacts of Renewable Energy Resources (RES) inherently depends on inter-temporal operational status. Accordingly, in the current paper, a novel operational flexibility maximization procedure is developed within a robust Security Constrained Unit Commitment (SCUC) problem to find the most tolerable flexibility band in response to RES variability impacts. In addition, combined-cycle units (CCU) and incentive based demand response, from both generation and demand sides, are considered as flexibility providers because of their specific characteristics such as high ramping capacities and fast start-up/shut-down rates. However, unlike conventional units with single mode operation, a CCU unit is composedof multiple combustion turbines (CTs) and steamturbines (STs) that can operate in different modes. Since it is needed to decide the on/off statusand power output of each CT and ST unit at every timeinterval, the recourse decision layer will be non-convex. The challenging non-convex recourse decision level is cast as a mixed-integer program that is solved by an exact nested column-and-constraint generation algorithm. The capability of the proposed model is then investigated in standard IEEE 118-bus test system.

Congestion-aware robust security constrained unit commitment model for AC-DC grids

Due to the increasing penetration of wind energy, their natural volatility may cause power flow congestions by blocking some key transmission interfaces. To further reduce energy violations induced by uncertainty issues and ensure the system reliability, the controllability of High Voltage Direct Current (HVDC) system should be exploited in AC-DC grids. By leveraging the congestion management capabilities of HVDC, we propose a congestion-aware robust security constrained unit commitment (SCUC) model, to preemptively consider the plausible congestion circumstances in a more adaptive way in the day-ahead (DA) market. In our model, the conventional uncertainty budget sets are modified by the proposed congestion-aware factors, where the typical operational characteristics of traditional corrective actions and HVDC regulations in real-time (RT) market are formulated adaptively. Moreover, the feasibility region of proposed problem is further pruned by the optimality cut planes where more pertinent real-time information are included, thus the local optimal solution is eliminated and the superior economic benefits are obtained in our model. To solve this mix-integer linear problem (MILP), the model is divided into three parts including the DA decision model, the traditional corrective dispatch model, and the HVDC regulation dispatch model. Correspondingly, an improved three-level Benders Decomposition algorithm is developed to solve the model. The enhanced performance of the proposed model was validated in a modified IEEE 118-bus test case. The results show that, in our model, the flexible regulation of HVDC system optimally allocate the operational burdens between DA and RT markets, thus the congestion-aware robust SCUC model further captures the economic benefits when ensuring the model’s robustness.

An Improved Robust SCUC Approach Considering Multiple Uncertainty and Correlation

With the large‐scale integration of wind power and photovoltaic power, as well as the rapid development of power systems in recent years, it is of great significance to study meticulous day‐ahead scheduling methods further. A robust security‐constrained unit commitment (SCUC) approach with the considerations of uncertainty outputs and the corresponding probability correlations is proposed in this paper. First, an improved robust SCUC model is constructed according to the multiple uncertainties of outputs and their probability correlations. Then, Cholesky decomposition is used to convert the correlated random samples into independent ones so as to determine the worst scenario directly based on the sample characteristics. Finally, the model is solved by Benders decomposition method. The simulation results based on the IEEE 118‐bus system indicate that the proposed approach can effectively improve the economy while ensuring the robustness of the day‐ahead SCUC decisions under multiple uncertainties. Additionally, the worst scenario determination method based on Cholesky decomposition can effectively promote the compactness of the robust SCUC model and significantly improve the computational efficiency accordingly. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Techno-economic and environmental assessment of the coordinated operation of regional grid-connected energy hubs considering high penetration of wind power

Nowadays, the high penetration of renewable energy sources (RESs) with non-uniformly distributed patterns has created unprecedented challenges for regional power systems to maintain system flexibility and reliability. These technical challenges obligate power system operators to curtail part of the produced renewable energy at various scheduling intervals. Motivated by these challenges, grid-connected energy hubs are seen as a way forward to boost system flexibility, decrease the rate of renewable power curtailment, and increase energy efficiency. However, simplified models may significantly affect the performance of the grid-connected energy hubs in practice. Hence, this paper proposes a holistic structure to determine the optimal coordinated operation of the grid-connected energy hubs and the regional power system by relying on the high penetration of wind power. In this regard, various fundamental challenges that have not yet been addressed in an integrated manner, including the CO2 emission rate and the amount of curtailed renewable energy along with total operating costs of the integrated energy system, are among the main objectives of the optimization problem. The proposed structure is developed in the form of tractable mixed-integer nonlinear programming (MINLP) problem to handle the day-ahead security-constrained unit commitment (SCUC). The information-gap decision theory (IGDT)-based robust model is used for accurate modeling of wind power uncertainty. The characteristics of the proposed IGDT-based robust SCUC model and its benefits are investigated through several technical case studies conducted on the modified 6-bus and 24-bus test systems. The simulation results validate the effectiveness and feasibility of the proposed structure. According to the obtained results for the 6-bus test system, networked energy hubs can help the system operator to reduce the total operating cost, wind power curtailment cost, and CO2 emission cost by 16.62%, 100%, and 30.44%, respectively, through utilizing up-to-date energy conversion facilities and energy storage systems as well as managing energy demands. It can be seen that the proposed strategy is a very effective step towards achieving a 100% renewable energy system.

A novel robust security constrained unit commitment model considering HVDC regulation

To further improve the robustness and economic efficiency of the conventional security-constrained unit commitment (SCUC) problem when confronting system uncertainties, we propose a novel robust SCUC model considering the prompt and flexible controllability of high voltage direct current (HVDC) in asynchronous interconnected systems. Unlike the conventional method, the proposed model minimizes the total cost of pre-day commitment for the base case and real-time dispatch under extreme uncertainties when guaranteeing the generation units and HVDC can be adjusted adaptively and securely. The robustness and economic efficiency of the model are enhanced by optimizing their trade-off when integrating HVDC regulation. As the method involves unit commitment, short-term dispatch, and power rescheduling, an improved tri-level Benders decomposition algorithm is developed according to the structure of the model to solve this mixed-integer nonlinear programming problem. In computational experiments, the effectiveness of the proposed model was validated in a two-area HVDC interconnected asynchronous system under various uncertainties. Additionally, the superior cooperation between a day-ahead commitment plan and real-time dispatch in the novel SCUC model with HVDC regulation was verified.

Optimal demand response strategies to mitigate wind power variability and gas‐supply uncertainty in a multi‐resolution robust security constrained unit commitment

With the increasing penetration rate of renewable energy sources, variability impacts, aside from uncertainty, will increase the need for operational flexibility resources in power systems. Accordingly, in this study, flexibility provision from both generation and demand sides are considered in a day-ahead scheduling problem. Fast start gas-fired units, due to their agility in starting-up and high ramping capabilities are considered as generation side flexibility providers. However, the normal operation of these units strictly depends on a secure gas supply through connected gas pipelines. Thus, gas-supply uncertainty is considered in the proposed model to mimic the impacts of deviations in gas volume through pipelines. On the other hand, demand response programs (DRPs) with their specific characteristics are among powerful demand side flexibility providers. However, unlike the existing literature that considers a supplementary role for DRPs, this study introduces the main role for DRPs as flexibility providers through comprehensive modelling of versatile DRPs. The proposed day-ahead scheduling problem is a multi-resolution robust security constrained unit commitment that the robustness comes from the decision making against sub-hourly gas-supply uncertainty and wind power variability. The applicability of the proposed model is tested on both an 8-bus and IEEE-118-bus standard test systems.

Hierarchical and Robust Scheduling Approach for VSC-MTDC Meshed AC/DC Grid With High Share of Wind Power

This paper proposes a novel hierarchical and robust scheduling paradigm for the emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid system with high share of wind power. Considering the multilevel structure of the VSC-MTDC meshed AC/DC system, the scheduling problem is decomposed into three interactive levels according to the hierarchical analytical target cascading (ATC) technique. The low level is a two-stage adaptive robust security-constrained unit commitment problem for the AC system, which is solved by the column-and-constraint generation (C&CG) algorithm; the middle level is a day-ahead power transmission optimization problem for the VSC stations, where a day-ahead operation model for the VSC station is presented to fully use its flexible and controllable power adjustment capability to promote wind power accommodation; and the high level is a multi-period optimal power flow problem for the DC grid. An integrated ATC and C&CG algorithm is proposed to enable the hierarchical and robust scheduling. The parallel solution is used to accelerate the hierarchical scheduling. Simulations show that this formulation is effective in dealing with wind power uncertainty, promoting wind power accommodation, and improving the calculation efficiency.

Uncertainty Cost of Stochastic Producers: Metrics and Impacts on Power Grid Flexibility

The widespread presence of contingent generation, when coupled with the resulting volatility of the chronological net-load (i.e., the difference between stochastic generation and uncertain load) in today's modern electricity markets, engender the significant operational risks of an uncertain sufficiency of flexible energy capacity. In this article, we address several operational flexibility concerns that originate from the increase in generation variability captured within a security-constrained unit commitment (SCUC) formulation in smart grids. To quantitatively assess the power grid operational flexibility capacity, we first introduce two reference operation strategies based on a two-stage robust SCUC, one through a fixed and the other via an adjustable uncertainty set, for which the state-of-the-art techniques may not be always feasible, efficient, and practical. To address these concerns and to account for the effects of the uncertainty cost resulting from dispatch limitations of flexible resources, a new framework centered on the adjustable penetration of stochastic generation is proposed. Our hypothesis is that if the SCUC is scheduled with an appropriate dispatch level of stochastic generation, the system uncertainty cost will decrease, and subsequently, the system's ability to accommodate additional uncertainty will improve. Numerical simulations on a modified IEEE 73-bus test system verify the efficiency of the suggested assessment techniques.

Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products

Wind energy sources have created new challenges in power system scheduling to follow the network load. Gas fired units with high ramping could better deal with inherent uncertainties of wind power compared to other power generation sources. The natural gas system constraints affect the flexibility of natural gas-fired power plants in the electrical market. In this paper, three solutions have been proposed to cover the challenges of gas system constraints and the uncertainty of wind power: 1) using information-gap decision theory (IGDT) based robust approach to address the uncertainty caused by the intrinsic nature of wind power, 2) Integration of compressed air energy storage (CAES), and demand response (DR) in day-ahead scheduling and 3) considering flexible ramping products in order to ensure reliable operations, there must be enough ramp to eliminate the variability of wind power in real-time dispatch stage. This paper proposes an IGDT-based robust security constrained unit commitment (SCUC) model for coordinated electricity and natural gas systems with the integration of wind power and emerging flexible resources while taking the flexible ramping products into account. Numerical tests demonstrate the effect of emerging flexible resources on a reduction of system operation cost and the uncertainty of predicted wind power.

A Hierarchical Method for Robust SCUC of Multi-Area Power Systems With Novel Uncertainty Sets

This paper focuses on the interchange and generation scheduling problem of multi-area power systems, where decentralized decision procedure is preferred and the uncertainties of nodal injections should be considered. The problem is formulated as a multi-area robust security constrained unit commitment model, with a novel uncertainty set specified by the variance of system net load. We prove that such an uncertainty set can provide a more precise probabilistic guarantee than conventional budgeted sets. To solve the problem in decentralized manner, an upper-level robust convex optimization model is proposed to optimize the tie-line power flow and derive a generation interval for each area. Then through the coordinated uncertainty requirement decided by the generation interval, each regional system operator can solve a decoupled robust unit commitment problem independently. Besides, a modified outer approximation algorithm is developed to obtain higher-quality solution of the bilinear programming involved in the process. Simulation results on a two-area system demonstrate the effectiveness of the uncertainty set, and show the economic efficiencies of unit commitment solutions acquired from the hierarchical method.

Information-Gap Decision Theory for Robust Security-Constrained Unit Commitment of Joint Renewable Energy and Gridable Vehicles

This paper presents a new framework, utilizing information-gap decision theory (IGDT), for multiobjective robust security-constrained unit commitment of generating units in the presence of wind farms and gridable vehicles. Both the wind power and load demand uncertainties are considered, and modeled using a biobjective model. As the main advantage, the framework enables the system operator to take an appropriate operational decision with respect to the extremity of each uncertainty. The proposed problem is solved using a normal boundary intersection technique. Subsequently, VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR), a decision-making tool, is utilized to choose the best Pareto optimal solution. Finally, the IGDT-based framework presented in this paper is validated using a six-bus test system, the IEEE Reliability Test System with 24 buses, and the IEEE 118-bus system.

Corrections to “Two-Stage Robust Security Constrained Unit Commitment Considering the Spatiotemporal Correlation of Uncertainty Prediction Error” [2019 22891-22901

The authors inadvertently left out two coauthors to the above paper [1] . The names of the two authors are Bin Liu and Feng Liu.

Two-Stage Robust Security Constrained Unit Commitment Considering the Spatiotemporal Correlation of Uncertainty Prediction Error

Robust optimization (RO) is an important tool to solve the security-constrained unit commitment (SCUC) problem for a power system with large-scale wind power. The main disadvantage of RO is that it is overly conservative, and the conservativeness of RO can be attributed to the uncertainty set used in the formulation. This paper proposes a two-stage robust SCUC model considering the spatiotemporal correlation of the uncertainty prediction error. First, based on the historical data, a polyhedral uncertainty set that can describe the spatial-temporal correlation of uncertainties is established, and the analytical relationship between confidence probability and the uncertain set is given. Second, a two-stage robust SCUC model with the objective of minimizing the operating cost under the forecasting scenarios is proposed based on the polyhedral set. Third, the Benders decomposition method is used to solve the proposed model according to its characteristics. The simulation results on the modified IEEE-30 and IEEE-118 bus system demonstrate that the proposed method can reduce the conservativeness of RO and guarantee the security and economy of the unit commitment.

MILP Based Robust Short-Term Scheduling for Wind–Thermal–Hydro Power System With Pumped Hydro Energy Storage

The uncertainty of the wind power generation and complex constraints of the hydropower pose challenges for the short-term scheduling of coordinated wind power, thermal power, and cascaded hydroelectric system (WTHS). In this paper, a robust security-constrained unit commitment model is established for a WTHS. The proposed model ensures the utilization of wind power and economic return from the scheduling. Conservative adjustable uncertainty sets are used to characterize the uncertainty of wind power over temporal and spatial dimensions. In this model, pumped hydro energy storage (PHES) is incorporated to cope with the wind power fluctuations. A simplified affine policy is developed for the decision making of the adjustable variables. Based on a series of linearization techniques, the proposed model is formulated as a single-level mixed-integer linear programming (MILP) problem, where the numerical tests performed on the modified IEEE 30-bus, IEEE 118-bus, and Polish 2736-bus systems verify the effectiveness of the model. The comparative analyses quantitatively evaluate the contributions of the PHES in terms of economic performance and wind power accommodation. The test results reveal that the robustness of scheduling plans is enhanced by the use of the PHES, and the proposed approach is applicable to the large-scale power systems.

Two-Stage Robust Security-Constrained Unit Commitment Model Considering Time Autocorrelation of Wind/Load Prediction Error and Outage Contingency Probability of Units

The conservativeness of unit commitment models-based robust optimization (RO) depends on the modeling of uncertainty sets. This paper proposes a new two-stage robust security-constrained unit commitment (SCUC) model, which aims at minimizing the operating cost in the base scenario while guaranteeing that the robust solution can be adaptively and safely adjusted according to the uncertainties of wind power, load, and $N$ - $k$ fault. This new model has the following characteristics: 1) the temporal correlation of continuous uncertainties (i.e., wind power output and load) are studied and a time-correlation constraint is established to reduce the conservativeness of uncertainty sets in the proposed robust SCUC model; 2) the discrete characteristics of the uncertain set is used to describe the uncertainty of discrete $N$ - $k$ fault; 3) the outage probability of units with different capacity is also considered with a proposed probability criterion; and 4) the constraint approximation is simplified to a linear constraint that can be applied to RO. The proposed model is solved by the Benders decomposition and dual theory. The simulation results on modified IEEE-RTS-96 system show that the proposed method can effectively reduce the conservativeness of uncertain sets and ensure the economic and security of the optimization results.

Robust Constrained Operation of Integrated Electricity-Natural Gas System Considering Distributed Natural Gas Storage

A robust security-constrained unit commitment (robust SCUC) model is proposed in this paper to enhance the operational reliability of integrated electricity-natural gas system (IEGS) against possible transmission line outages. In this work, adjustable capability of natural gas contract is considered to avoid dramatic changes in real-time gas demand. Distributed natural gas storage is also included to smooth out power system demand curve and further improve operational efficiency at normal state and during contingencies. Nonlinear and nonconvex natural gas flow functions are relaxed into second-order cone (SOC) constraints, then the SOC-based column and constraint generation method is adopted to solve the proposed two-stage robust convex optimization problem. In this iterative method, the security-check subproblem feeds back worst case constraints to the first-stage master problem, until no violated scenarios can be detected. Simulations tested on 6-bus-6-node and 118-bus-10-node IEGS with natural gas storage show that the proposed storage model is effective in the robust SCUC solution for IEGS considering possible N - k contingencies with limited natural gas adjustments.

Security-Constrained Unit Commitment With Flexible Uncertainty Set for Variable Wind Power

Power system operation has recently witnessed major challenges, which are often due to large-scale integrations of wind power generation. In this paper, a two-stage robust security-constrained unit commitment (SCUC) model is proposed for managing the wind power uncertainty in the hourly scheduling of power system generation. Different from previous studies on robust SCUC, which considered a predefined uncertainty set, the proposed method applies a flexible uncertainty set for managing the variable wind power generation. The proposed method seeks a feasible and economic dispatch in the flexible uncertainty set, takes into account wind spillage and load curtailment risks, and makes a tradeoff between the optimal wind power absorption and the economic grid operation. Several case studies are applied to the proposed method and the corresponding solutions are analyzed in the paper. The impacts of major factors, including flexible generation resources and power transmission capacity, on the proposed solution are also discussed. The numerical results demonstrate the merits of the proposed method for managing large variations in the hourly wind power generation and lowering the power system operation cost in uncertain conditions.

Two-Stage Robust Security-Constrained Unit Commitment with Optimizable Interval of Uncertain Wind Power Output

Because wind power spillage is barely considered, the existing robust unit commitment cannot accurately analyze the impacts of wind power accommodation on on/off schedules and spinning reserve requirements of conventional generators and cannot consider the network security limits. In this regard, a novel double-level robust security-constrained unit commitment formulation with optimizable interval of uncertain wind power output is firstly proposed in this paper to obtain allowable interval solutions for wind power generation and provide the optimal schedules for conventional generators to cope with the uncertainty in wind power generation. The proposed double-level model is difficult to be solved because of the invalid dual transform in solution process caused by the coupling relation between the discrete and continuous variables. Therefore, a two-stage iterative solution method based on Benders Decomposition is also presented. The proposed double-level model is transformed into a single-level and two-stage robust interval unit commitment model by eliminating the coupling relation, and then this two-stage model can be solved by Benders Decomposition iteratively. Simulation studies on a modified IEEE 26-generator reliability test system connected to a wind farm are conducted to verify the effectiveness and advantages of the proposed model and solution method.