Robust Security-constrained Unit Commitment Model Research Articles

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.

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.

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 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.

A Multi-Band Uncertainty Set Based Robust SCUC With Spatial and Temporal Budget Constraints

The dramatic increase of renewable energy resources in recent years, together with the long-existing load forecast errors and increasingly involved price sensitive demands, has introduced significant uncertainties into power systems operation. In order to guarantee the operational security of power systems with such uncertainties, robust optimization has been extensively studied in security-constrained unit commitment (SCUC) problems, for immunizing the system against worst uncertainty realizations. However, traditional robust SCUC models with single-band uncertainty sets may yield over-conservative solutions in most cases. This paper proposes a multi-band robust model to accurately formulate various uncertainties with higher resolution. By properly tuning band intervals and weight coefficients of individual bands, the proposed multi-band robust model can rigorously and realistically reflect spatial/temporal relationships and asymmetric characteristics of various uncertainties, and in turn could effectively leverage the tradeoff between robustness and economics of robust SCUC solutions. The proposed multi-band robust SCUC model is solved by Benders decomposition (BD) and outer approximation (OA), while taking the advantage of integral property of the proposed multi-band uncertainty set. In addition, several accelerating techniques are developed for enhancing the computational performance and the convergence speed. Numerical studies on a 6-bus system and the modified IEEE 118-bus system verify the effectiveness of the proposed robust SCUC approach for enhancing uncertainty modeling capabilities and mitigating conservativeness of the robust SCUC solution.

Robust Security-Constrained Unit Commitment and Dispatch With Recourse Cost Requirement

With increasing renewable energy resources, price- sensitive loads, and electric-vehicle charging stations in the power grid, uncertainties on both power generation and consumption sides become critical factors in the Security-Constrained Unit Commitment (SCUC) problem. Recently, worst scenario based robust optimization approaches are employed to consider uncertainties. This paper proposes a non-conservative robust SCUC model and an effective solution approach. The contributions of this paper are three-fold. First, the commitment and dispatch solution obtained in this paper can be directly used in day-ahead market as it overcomes two issues, conservativeness and absence of robust dispatch, which are the two largest obstacles to applying robust SCUC in real markets. Secondly, a new concept recourse cost requirement, similar to reserve requirement, is proposed to define the upper bound of re-dispatch cost when uncertainties are revealed. Thirdly, a novel decomposition approach is proposed to effectively address the well-known computational challenge in robust approaches. Simulation results on the IEEE 118-bus system validate the effectiveness of the proposed novel model and solution approach.

Robust SCUC Considering Continuous/Discrete Uncertainties and Quick-Start Units: A Two-Stage Robust Optimization With Mixed-Integer Recourse

This paper presents a comprehensive two-stage robust security-constrained unit commitment (SCUC) approach, which minimizes the operation cost of the base case while guaranteeing that the robust solution can be adaptively and securely adjusted in response to continuous load and wind uncertainty intervals as well as discrete $N-K$ generation and transmission contingency security criteria. In addition, corrective capabilities of both non-quick-start and quick-start units are rigorously formulated. Specifically, unit commitment of quick-start units is adaptively adjusted in the recourse stage for satisfying security constraints under various uncertainties, which introduces mixed-integer recourse to the proposed two-stage robust SCUC model. The proposed model is solved by the combination of modified Benders decomposition (BD) method and column-and-constraint generation (C&CG) algorithm, which decompose the original problem into a master UC problem for the base case and security checking subproblems for uncertainties. Numerical case studies on the modified IEEE 118-bus system illustrate the effectiveness of the proposed robust SCUC approach. Although the modified BD does not provide the tightest lower bound and may not guarantee the global optimality, robustness performance tests indicate that a reasonable threshold on the violation of security checking subproblems would guarantee good enough solutions from engineering point of view.

Comparison of variant robust SCUC models for operational security and economics of power systems under uncertainty

In electricity market, security-constrained unit commitment (SCUC) utilizes the detailed market information submitted by market participants to provide a financially viable and physically feasible unit commitment solution for Independent system operators (ISOs)/regional transmission owners (RTOs). With the dramatic increase of renewable energy resources in recent years, the robust optimization approach has been recently explored for solving the SCUC problem with various uncertainties. This paper focuses on the following questions: How variant robust SCUC models in terms of different worst-case definitions could impact operational security and economics of power systems under uncertainties? In addition, what is the proper robust SCUC model that can meet specific market operation needs of ISOs/RTOs for effectively operating the system? Four different robust SCUC models are investigated, including: (1) Minimax load shedding robust model, (2) Minimax economic dispatch (ED) cost robust model, (3) Minimax variance robust model, and (4) Minimax regret robust model. Outer approximation (OA) and Benders’ decomposition (BD) are used to solve the four robust models. Numerical case studies compare the performance of the four models and analyze their distinct characteristics for the market economic operation (such as locational marginal prices (LMP), regret costs, and base case costs) and system secure operation (such as load shedding (LS) quantities and Do-Not-Exceed (DNE) limits of power systems under uncertainties.

On the Robust Solution to SCUC With Load and Wind Uncertainty Correlations

With the increasing penetration of variable renewable generations, independent system operators (ISOs)/regional transmission organizations (RTOs) are faced with new challenges for the secure and economic operation of power systems. This paper proposes an effective approach for deriving robust solutions to the security-constrained unit commitment (SCUC) problem, which considers load and wind uncertainties via interval numbers. Different from most robust optimization-based SCUC approaches in literature which explore robust unit commitment (UC) solutions for immunizing against the worst economic scenario in terms of the highest minimum dispatch cost, the proposed robust SCUC model minimizes operation cost for the base case while guaranteeing that the robust UC and dispatch solutions could be adaptively and securely adjusted in response to uncertain intervals. Thus, the proposed model achieves smaller unit commitment costs while maintaining the solution robustness as compared with literature. In addition, the proposed model describes base case dispatches and corrective actions in uncertain intervals, which is more consistent with the current day-ahead and real-time markets. Furthermore, besides budget constraints used in literature, this paper also considers load and wind variability correlations in constructing uncertain intervals, which would eliminate unlike-to-happen scenarios and further limit the level of conservatism of the robust solution. The proposed robust SCUC model is solved by Benders decomposition, which decomposes the original problem into a master UC problem for the base case and subproblems for the base case network evaluation and the security checking for uncertain intervals. Feasibility cuts are generated and fed back to the master problem for further iterations when violations are identified in subproblems. Numerical case studies on the modified IEEE 118-bus system illustrate the effectiveness of the proposed robust SCUC model for the secure and economic operation of power systems under various uncertainties.