Day-ahead Security-constrained Unit Commitment Research Articles

Optimal Energy Reserve Scheduling in Integrated Electricity and Gas Systems Considering Reliability Requirements

With the growing interdependence between the electricity system and the natural gas system, the operation uncertainties in either subsystem, such as wind fluctuations or component failures, could have a magnified impact on the reliability of the whole system due to energy interactions. A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system (IEGS). Therefore, this paper proposes a day-ahead security-constrained unit commitment (SCUC) model for the IEGS to schedule the operation and reserve si-multaneously considering reliability requirements. Firstly, the multi-state models for generating units and gas wells are established. Based on the multi-state models, the expected unserved energy cost (EUEC) and the expected wind curtailment cost (EWC) criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS. Furthermore, the EUEC and EWC criteria are incorporated into the day-ahead SCUC model, which is noncon-vex and mathematically reformulated into a solvable mixed-integer second-order cone programming (MISOCP) problem. The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system. Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation.

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.

Integrated data‐driven framework for fast SCUC calculation

Security-constrained unit commitment (SCUC) is one of the most important optimisation problems for operation planning of power systems. Indeed, with the fast expansion of power grids and the increasing growth of heterogeneous market participants in electricity markets, the day-ahead SCUC continuously encounters significant performance challenges. To improve the computational performance of SCUC and achieve solutions of good quality, an integrated framework which combines a data-driven approach and a variable-aggregation method is presented in this study. The variable-aggregation method effectively approximates the original network security constraints with a reduced number of variables. Moreover, as aggregated constraints could reduce the feasible region of the original SCUC and potentially degrade solution quality for certain SCUC instances, it is preferable to only apply such an aggregation approach towards difficult SCUC instances. Therefore, a data-driven classification method, by adopting relevant SCUC input data as features, is integrated to first predict whether a SCUC instance is ‘easy’ or ‘hard’. To this end, the integrated framework could improve the overall performance of SCUC instances, by and large, in terms of computational efficiency and solution quality. Numerical results illustrate the effectiveness of the proposed integrated framework.

An Integrated Preventive Operation Framework for Power Systems During Hurricanes

Severe weather is the primary cause of power outages in the U.S. Despite the availability of weather forecast information, such data are not systematically integrated into operation models. This article proposes an integrated framework to convert weather forecast into appropriate information for preventive operation during hurricanes so that the power outages induced by hurricanes can be reduced. To achieve this goal, first, a structural model of the transmission towers is developed to estimate failure probabilities based on the wind speed. These probabilities are then integrated within a day-ahead security-constrained unit commitment framework to guide preventive operation. The resulting day-ahead schedule will be more reliable as it will rely less on the elements that are likely to fail. Simulation studies, conducted on the IEEE 118-bus system affected by synthesized Irma and Harvey hurricanes, showed that the proposed framework was able to prevent 33% to 83% of the blackouts. Further research is required to investigate the impacts of flooding, damage to the distribution network, and weather forecast uncertainty.

A Distributed Framework for Solving and Benchmarking Security Constrained Unit Commitment With Warm Start

This paper discusses several methods to improve commercial optimization solver performance on day-ahead security constrained unit commitment through warm start and lazy constraint settings. Data analytics is performed to greatly improve the quality of the initial commitment solution and lazy constraint setting. A distributed optimization framework is proposed to take advantage of the diversity from prevalent solvers (GUROBI and CPLEX) and different warm start strategies. A systematic distribution profile based benchmarking method is also proposed.

Uplift Allocation of Voltage and Local Reliability Constraints

Centralized electricity markets currently do not optimize reactive power and voltage in the market clearing software. Voltage and local reliability (VLR) commitment requirements are mostly identified through out of market operational procedures. Failure to maintain VLR may incur voltage collapse, generation, transformer loss, or even blackout. Midcontinent Independent System Operator (MISO) employs binary constraints, minimum/maximum generation constraints, interface constraints, and manual commitments to address VLR requirement in the market clearing process and ensure adequate commitment for reliability. This paper integrates binary VLR constraints in day-ahead security constrained unit commitment to improve market efficiency. However, VLR constraints may cause uplift cost, and sometimes the associated uplift cost can be significant. An uplift cost allocation method with the consideration of resources commitment reasons is developed in this paper. The proposed approach is considered for implementation in MISO market clearing process and a MISO test case is used to validate the effectiveness of the proposed approach.

Distributed Dispatch Approach for Bulk AC/DC Hybrid Systems With High Wind Power Penetration

For bulk AC/DC hybrid transmission systems with high wind power penetration, this paper presents a distributed dispatch approach to the security-constrained unit commitment (SCUC) problem. To fully use the flexible adjustment capability of the HVDC tie-line to promote inter-regional wind power accommodation, an operation model for the HVDC tie-line is presented. Then, a distributed SCUC approach based on the analytical target cascading technique is proposed, where the day-ahead SCUC problem is decomposed into an upper-level master problem and parallel subproblems of lower level regional dispatch. The master problem is in charge of determining the day-ahead transmission plan for the HVDC tie-line, and the lower-level dispatch centers independently solve their SCUC problems in parallel in accordance with the hierarchical and partitioned power scheduling mode. Simulations show that considering the flexible and controllable nature of the HVDC tie-line, the proposed distributed dispatch approach for bulk AC/DC hybrid systems has the advantages of promoting inter-regional wind power accommodation and improving the economics of the overall system operation while relieving the peak regulation pressure of the receiving-side system.

Stochastic Multi-Timescale Power System Operations With Variable Wind Generation

This paper describes an integrated operational simulation tool that combines various stochastic unit commitment and economic dispatch models together that consider stochastic loads and variable generation at multiple operational timescales. The tool includes four distinct configurable sub-models within: day-ahead security-constrained unit commitment (SCUC), real-time SCUC, real-time security-constrained economic dispatch (SCED), and automatic generation control (AGC). The unit commitment and dispatch sub-models within can be configured to meet multiple load and variable generation (VG) scenarios with configurable first stage and second-stage decisions determined where first-stage decisions are passed on and second-stage decisions are later determined by other sub-models in a continuous manner. The progressive hedging algorithm (PHA) is applied to solve the stochastic models to maintain the computational tractability of the proposed models. Comparative case studies, considering various configurations of stochastic and deterministic sub-models are conducted in low wind and high wind penetration scenarios to highlight the advantages of the stochastic programming during different decision-making processes. The effectiveness of the proposed method is evaluated with sensitivity tests using both economic and short-term reliability metrics to provide a broader view of its impact at different timescales and decision-making processes.

Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration

The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen (P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub (EH) with both a P2H facility (electrolyzer) and a gas-to-power (G2P) facility (hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment (SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming (MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration (HWP).

Improving Large Scale Day-Ahead Security Constrained Unit Commitment Performance

As part of the day-ahead market clearing process, MISO solves one of the most challenging Security Constrained Unit Commitment (SCUC) models. With footprint expansions and increased activity from financial traders, the day-ahead market unit commitment encounters significant performance challenges from time to time. This paper reviews MISO's day-ahead market clearing process and identifies the factors contributing to these performance challenges. It then shares techniques that have been developed to overcome these challenges. Three alternative backup solving approaches were developed. An incremental solving algorithm is proposed to better handle the iterative market clearing process and to perform solution polishing and commitment reason identification. Numerical results based on MISO data are presented.

Market Implications and Pricing of Dynamic Reserve Policies for Systems With Renewables

Static reserve policies are used within security-constrained unit commitment (SCUC) and security constrained economic dispatch (SCED) to ensure reliability. A common policy is that 10-min reserve must exceed the largest contingency. However, this condition does not guarantee reliability because voltage and thermal limits can hinder reserve deliverability. Many operators use zonal reserve markets to ensure reserves are dispersed across the grid. Such zonal models attempt to anticipate transmission bottlenecks, which is a difficult task when the future system state is uncertain. This paper examines the market implications of dynamic reserve policies used to mitigate uncertainty from renewable resources and contingencies. We study the market implications of policies recently proposed in the literature, such as hourly zones within day-ahead SCUC and an algorithm that formally disqualifies reserves that are expected to be undeliverable. A locational reserve pricing scheme is also proposed in connection with scenario-based reserve disqualification. Analysis on the RTS-96 test case shows that dynamic zones and reserve disqualification, along with the proposed compensation scheme, help direct reserve payments toward resources that more effectively respond to contingencies.