Security-constrained Unit Commitment Problem Research Articles

Security-Constrained Unit Commitment for AC-DC Grids With Generation and Load Uncertainty

The uncertainties in renewable generators and load demand make it a challenge for system operators to execute the security-constrained unit commitment (SCUC) program in an ac-dc grid. The SCUC is a nonlinear mixed-integer optimization problem due to the power flow equations, constraints imposed by the ac-dc converters, and the binary variables associated with the generators’ on/off state. In this paper, we study the SCUC problem in ac-dc grids with generation and load uncertainty. We introduce the concept of conditional value-at-risk to limit the risk of deviations in the load demand and renewable generation. We relax the binary variables and introduce a $l_1$ -norm regularization term to the objective function, and then use convex relaxation techniques to transform the problem into a semidefinite program (SDP). We develop an algorithm based on the iterative reweighted $l_1$ -norm approximation that involves solving a sequence of SDPs. Simulations are performed on an IEEE 30-bus test system. Results show that the proposed algorithm returns a solution within 2% gap from the global optimal solution for the underlying test system. When compared with the multi-stage algorithm in the literature, our algorithm has a lower running time and returns a solution with a smaller gap from the global optimal solution.

Moving beyond the optimal transmission switching: stochastic linearised SCUC for the integration of wind power generation and equipment failures uncertainties

This study recommends a stochastic optimization model for the security constrained unit commitment (SCUC), which incorporates the optimal transmission switching (OTS) for managing the uncertainty of wind power generation and equipment failures, i.e. unit/line outages. Also, this study presents a technique in stochastic SCUC model with the OTS action using the AC optimal power flow (AC OPF). The AC OPF provides a more accurate picture of power flow in the power system compared to the DC optimal power flow that is usually considered in the literature for the stochastic SCUC models and the OTS action. While the stochastic SCUC model with the OTS action based on AC OPF is a mixed-integer non-linear programming model, this study transforms it into a mixed-integer linear programming (MILP) model. The MILP approach uses a piecewise linear model of AC OPF, which allows the reactive power and voltage to be considered directly in power flow model. The proposed stochastic SCUC problem is evaluated on the 6 bus, IEEE 118-bus and 662-bus test systems in pre- and post-OTS action. Obtained results demonstrate the effectiveness of the proposed model.

Impact Evaluation of Electric Vehicle Parking on Solving Security-Constrained Unit Commitment Problem

In this paper, the employment of a vehicle-to-grid (V2G) system in the security-constrained unit commitment (SCUC) problem is considered. SCUC has gained remarkable attention from researchers in the field of electric power systems, aiming to determine the generation schedule in which the system operator maximizes the system security and minimizes the generation costs, while satisfying the system and units’ constraints. Tremendous technological advances in recent years have attracted the attention of system operators to utilize novel sources of electricity, accompanied with thermal units. To this end, V2G technology recently drew remarkable consideration as a new energy resource. V2G reduces the dependence of electricity production procedures on small-scale and costly thermal units, and subsequently has a strong impact on the operation costs and ameliorates the management of load vacillations. This paper presents the use of V2G in scheduling and operating power systems. A successful technique for investigating the impacts of V2G on a real power system is running SCUC on power systems in which electric vehicle parking is installed on different buses. In order to assess its applicability, the proposed method has been applied in two case studies: the IEEE 6-bus system and the extended IEEE 30-bus system. This study presents two simulation scenarios: the SCUC problem was first evaluated separately, and then in the presence of some electrical vehicles connected to the grid. The results demonstrate the reduction of the total operation cost. In addition, by using the proposed method, the operator can specify the optimal number of vehicles needed in the parking each hour. The results can help the system operators and designers in designing, planning, and operating such power systems.

Security Constrained Unit Commitment Using Line Outage Distribution Factors

Security-constrained unit commitment (SCUC) problem is one of the necessary tools for system operators to make operational planning and real-time operation. The internalization of transmission network and security constraints (e.g., N-1 criterion) could lead to different decisions in the generation dispatch. However, the computational burden of this problem is challenging mainly due to its inherent large problem size. Therefore, this paper proposes an N-1 security constrained formulation based on the line outage distribution factors (LODF) instead of the one based on injection sensitivity factors (ISF). This formulation is at the same time more compact than analogous formulations for contingency constraints; hence, it presents a lower computational burden. The computational efficiency of the proposed formulation is shown by solving the SCUC of the IEEE 118 bus system with LODF and ISF. Additionally, an iterative methodology for filtering the active N-1 congestion constraints is detailed, and its implementation for large-scale systems is described. The results show that the proposed filter reduces the computational time by approximately 70% in comparison to the complete formulation of N-1 constraints in SCUC.

Algorithm for the N-2 Security-Constrained Unit Commitment Problem with Transmission Switching

Most power grid systems are operated to be N-1 secure, meaning that the system can withstand the failure of any one component. There is increasing interest in more stringent security standards, where the power grid must be able to survive the (nearly) simultaneous failure of k components (i.e., N-k). However, this improved reliability criterion significantly increases the number of contingency scenarios that must be considered when solving the unit commitment problem. Additional computational complexity is introduced when taking into account transmission switching. This relatively inexpensive method of redirecting power flows in the grid has been proposed as a way of introducing flexibility to better survive failure events. We present an algorithm for solving the unit commitment problem that simultaneously addresses both the challenges of the N-k security requirement and the use of transmission switching during operation. We analyze the algorithmic performance and present computational results for the IEEE24 and RTS-96 test systems for k = 1 and 2. We also include a discussion of how this approach might be extended to solve problems with k ≥ 3. The online supplement, and data, are available at https://doi.org/10.1287/ijoc.2017.0751 .

Novel methods for Solving Economic Dispatch of Security-Constrained Unit Commitment Based on Linear Programming

There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.

Stochastic Security-Constrained Scheduling of Coordinated Electricity and Natural Gas Infrastructures

This paper proposes a coordinated stochastic model for studying the interdependence of electricity and natural gas transmission networks (referred to as EGTran). The coordinated model incorporates the stochastic power system conditions into the solution of security-constrained unit commitment problem with natural gas network constraints. The stochastic model considers random outages of generating units and transmission lines, as well as hourly forecast errors of day-ahead electricity load. The Monte Carlo simulation is applied to create multiple scenarios for the simulation of the uncertainties in the EGTran model. The nonlinear natural gas network constraints are converted into linear constraints and incorporated into the stochastic model. Numerical tests are performed in a six-bus system with a seven-node gas transmission network and the IEEE 118–bus power system with a ten-node gas transmission network. Numerical results demonstrate the effectiveness of EGTran to analyze the impact of random contingencies on power system operations with natural gas network constraints. The proposed EGTran model could be utilized by grid operators for the short-term commitment and dispatch of power systems in highly interdependent conditions with relatively large natural gas-fired generating units.

Security-Constrained Unit Commitment Problem including thermal and pumped storage units: An MILP formulation by the application of linear approximations techniques

This paper presents a new approach for solving Security Constrained Unit Commitment (SCUC) problems based on the application of several linear approximation techniques. Model considers thermal units, transmission constraints, and Pumped Storage Units (PSUs), which are important in power systems during peak and off-peak demand periods. Particularly, the proposed MILP model takes into account the hydraulic heads of PSUs for generating and pumping modes through linear methods of operation point selection. Therefore, a more realistic model is presented in comparison with other models available in the literature. To verify the effectiveness of the proposed approach, a modified IEEE 31-bus power system with two PSUs is tested. Our results indicate that the implementation of PSUs can achieve production cost savings compared with power systems in which thermal generation supplies the entire electricity demand. For improving the power system operations and maintenance, different indicators obtained from results are reported in graphs. This information is useful to identify the most critical parts of the systems and make recommendations for corrective or future actions.

Security Constrained Unit Commitment (SCUC) formulation and its solving with Modified Imperialist Competitive Algorithm (MICA)

One of the most important optimization problems in operation planning of power systems is unit commitment (UC). Consideration of transmission lines and operation constraints in UC problem leads to a more general problem known as Security Constrained Unit Commitment (SCUC). The SCUC can be formulated as a very large scale mixed-integer problem in practical utility grids. Solving SCUC can take tremendous time due to its huge dimension. In this paper, a formulation of SCUC problem, considering practical constraints and nonlinear characteristics including bus voltage limits, line flow limits, in addition to prevailing constraints such as hourly power demand, system spinning reserves, ramp up and down limits, minimum up and down time (MUT/MDT) limits, and emission limits, is presented. The Modified Imperialistic Competitive Algorithm (MICA), using a priority list (PL) for defining the initial state, is used to solve the mentioned optimization problem. The effectiveness of MICA method to solve the SCUC problem is shown on IEEE 30-bus and 118-bus test systems and is compared with the application of some heuristic methods i.e. genetic algorithm (GA), particle swarm optimization (PSO) and other mathematical approaches i.e. mixed integer programming (MIP).

Constraint Screening for Security Analysis of Power Networks

Consider a general security-constrained unit commitment (SCUC) problem for an arbitrary power network. This problem includes discrete variables corresponding to commitment parameters as well as demand and generation constraints, among others. Aside from its nonconvexity, SCUC is a large-scale problem for real-world systems due to the security constraints. The main objective of this paper is to propose an algorithm to eliminate a vast majority of linear security constraints in the high-dimensional mixed-integer SCUC problem in order to arrive at an equivalent reduced-order SCUC problem. To this end, we develop a parallel and computationally cheap algorithm for finding a minimal subset of security constraints whose satisfaction guarantees the satisfaction of all security constraints. The proposed algorithm does not depend on the unknown unit commitment parameters and allows the load forecasts to be imprecise. More specifically, a low-order model of the SCUC problem is found based on the topology of the power system, given lower and upper bounds on nodal power injections (to accommodate uncertainties in loads and generation productions), and the normal and emergency line ratings. This algorithm is tested on several power systems with as many as 5500 buses, for which each set of security constraints with millions of conditions is reduced to a minimal subset with only a few hundred conditions.

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).

Security Constrained Unit Commitment Incorporating Interline Power Flow Controller

Security-constrained unit commitment (SCUC) problem is solved using Artificial Bee Colony (ABC) algorithm incorporating Interline Power Flow Controller (IPFC). The objective of the SCUC problem is to obtain the minimum operating cost simultaneously maintaining the system security. The SCUC problem involves unit commitment as the main problem and security-constrained Economic Dispatch (SCED) as the sub problem. The solution of the SCUC problem is also investigated during contingency with a single line outage. Binary coded artificial bee colony (BABC) is used for solving the UC problem (master problem) and real coded artificial bee colony algorithm (RABC) is used for solving the SCED sub problem. The effectiveness of the proposed methodology is tested and validated on a 6 bus system and an IEEE 118 bus test system. The effectiveness of IPFC in a power system network ensuring system security is thoroughly investigated and the results are compared with that of existing methods available in the literature.

IGDT‐based robust optimal utilisation of wind power generation using coordinated flexibility resources

This study investigates the application of a robust method to solve the problem of security constrained unit commitment (SCUC) with flexible resources for managing the uncertainty of significant wind power generation (WPG) to sustain the load-generation balance. The flexible resources include up/down ramping capability of thermal units, hourly demand response, energy storage system and transmission switching action through an integrated scheme. The application of mixed-integer linear programming to deal with the SCUC problem with flexibility resources has been discussed in this study using information-gap decision theory (IGDT) to realise a robust strategy for power system decision maker. Besides, this study proposes an effective solution strategy based on Benders' decomposition to solve the proposed problem. Numerical simulation results on the modified six-bus system and IEEE 118-bus system clearly demonstrate the benefits of applying flexibility resources for managing the WPG uncertainty and validate the applicability of the proposed IGDT-based SCUC model.

Security Constraint Unit Commitment on Combined Solar Thermal Generating Units Using ABC Algorithm

In this paper, Security Constrained Unit Commitment (SCUC) problem with combined Thermal- Solar generating units is solved using Artificial Bee Colony (ABC) algorithm. SCUC problem aims to obtain minimum generation cost while satisfying the system, network and security constraints. The SCUC problem is divided into Unit Commitment Problem (UCP) which is considered as the master problem and Security Constrained Economic Dispatch (SCED) is considered as the sub problem. Here, both thermal and solar generations are considered in UCP and SCED solutions. Binary Coded ABC Algorithm is used to solve the UCP and Real Coded ABC Algorithm is used for solving the SCED problem. The constraints such as spinning reserves, hourly load demands, ramp up/ramp down limits of generators, minimum up/down limits, line flow and voltage limits are considered in the problem formulation. Beta distribution function is employed to forecast the solar power generation in different seasons. The comparison is carried out with and without incorporating solar generation. The proposed method is validated on a 6 bus system and a South Indian 86 bus utility.

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.

Cutting planes for the multistage stochastic unit commitment problem

As renewable energy penetration rates continue to increase in power systems worldwide, new challenges arise for system operators in both regulated and deregulated electricity markets to solve the security-constrained coal-fired unit commitment problem with intermittent generation (due to renewables) and uncertain load, in order to ensure system reliability and maintain cost effectiveness. In this paper, we study a security-constrained coal-fired stochastic unit commitment model, which we use to enhance the reliability unit commitment process for day-ahead power system operations. In our approach, we first develop a deterministic equivalent formulation for the problem, which leads to a large-scale mixed-integer linear program. Then, we verify that the turn on/off inequalities provide a convex hull representation of the minimum-up/down time polytope under the stochastic setting. Next, we develop several families of strong valid inequalities mainly through lifting schemes. In particular, by exploring sequence independent lifting and subadditive approximation lifting properties for the lifting schemes, we obtain strong valid inequalities for the ramping and general load balance polytopes. Finally, branch-and-cut algorithms are developed to employ these valid inequalities as cutting planes to solve the problem. Our computational results verify the effectiveness of the proposed approach.

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.

Enhanced Security-Constrained Unit Commitment With Emerging Utility-Scale Energy Storage

We introduce emerging utility-scale energy storage (e.g., batteries) as part of the set of control measures in a corrective form of the security-constrained unit commitment (SCUC) problem. This enhanced SCUC (ESCUC) leverages utility-scale energy storage for multiple applications. In the base case, the storage units are optimally charged and discharged to realize economic operation. Immediately following a contingency, the injections of storage units are adjusted almost instantly to alleviate short-term emergency overloads, thereby avoiding potential cascading outages and giving slow ramping generating units time to adjust their output. The ESCUC is a large two-stage mixed-integer programming problem. A Benders decomposition has been developed to solve this problem. In order to achieve computational tractability, we present several acceleration techniques to improve the convergence of the proposed algorithm. Case studies on the RTS-79 and RTS-96 systems demonstrate the effectiveness of the proposed approach.

Security-Constrained Unit Commitment Considering Demand Response Resource as Virtual Power Plant

Abstract: This paper presents a new methodology to security-constrained unit commitment (SCUC) problem with demand response resource (DRR) which is regarded as virtual power plant (VPP). In this paper, based on DRR bids information submitted to Korea Power Exchange (KPX), price elasticity and peak load are calculated and DRR cost function is obtained. The scheduling includes generator characteristics, DRR and reliability constraints Cost functions for generator and DRR are modeled as a piecewise linear function and an Mixed Integer Linear Programming (MILP) based method is applied to solve the optimization problem. Proposed methodology is tested and validated on The IEEE RTS-24 system. Through numerical simulation, DRR has demonstrated the decrease in the total operation cost as well as the curtailment of peak load.