Security Constraint Unit Commitment Research Articles

Robust optimization of transactive flexibility oriented scheduling of joint electricity and gas supplies

The power system with flexibility provision will lead to the expansion of the utilization of renewable energy resources. Providing flexibility is one of the basic challenges for power system operators and developers, which is addressed in this study. Moreover, the security of the gas supply system is important for power system operators, because the operation of gas-fired units depends significantly on the gas supply. In this study, the availability of pipelines has been considered as a gas supply uncertainty. Then, an optimal uncertainty set is proposed for security constraint unit commitment (SCUC) which is calculated for managing the uncertainty of wind and gas supply in different scenarios of risk. Robust-based optimization has been implemented to obtain the optimal uncertainty set in which both feasibility and economic optimal robustness have been guaranteed. A new robust flexibility-based SCUC model has been applied using a demand response program (RFSCUCDRP). The transactive flexibility between flexible providers, such as thermal units and DR, and uncertainty producers, such as wind resources, has been determined in the proposed model. The problem has been implemented on the 6-bus and IEEE-118-bus standard test systems with different risk percentages. The operation costs of the 6-bus system with and without robust optimization are 89,094 $ and 119,475 $, respectively. It is concluded that robust optimization is ultimately economically better.

Fast Frequency Response for Future Low-Carbon Indian Power System: Challenges and Solutions

India has transitioned from being an energy-deficient nation to an energy-surplus nation. As of July 2023, India’s power system has seen a rapid transformation, with renewable energy, including large hydro, accounting for 40% of the total installed capacity at 177 GW. The ongoing energy transition has not only changed the country’s energy mix but also brought new challenges for system operators. The primary challenge is frequency instability due to the reduction of system inertia and governor-based primary frequency response (PFR) availability by large-scale integration of uncertain renewable energy resources (RES) such as wind and solar photovoltaic generators. Furthermore, the absence of frequency control ancillary services market, inadequate penetration of electric vehicles (EVs) and uncertainty of RES generation enhance the complexity of the frequency response services in the Indian power system. In this context, this paper presents a comprehensive review of the frequency response challenges of the future low-carbon Indian power system and underlines the new potential fast frequency response (FFR) services from advanced energy storage and renewable generation technologies. Such FFR services can be swiftly deployed in low-inertia grids through the integration of energy storage systems and inverter-based resources in a shorter span. Modeling of FFR services in security constraint unit commitment (SCUC) can enhance grid resiliency and facilitate high penetration of RES in the Indian power system without loss of frequency stability.

Retracted: Resiliency Enhancement of Distribution Power Grids Using Mobile Marine Power Source

In this paper, a new configuration security framework is developed for reliability and resiliency improvement of distribution networks by the coordination of the security-constraint unit commitment (SCUC) and mobile marine power sources (MMPSs) under both post-disaster and normal restoration operations. It is assumed that a MMPS contains non-dispatchable distributed generators (DGs), e.g., photovoltaics (PV), as well as dispatchable DGs, e.g., gas turbines and diesel generators. A mixed-integer linear programming model is formulated for coordinating MMPSs and SCUC under both normal and extreme conditions (e.g., natural disasters, cyber and physical attacks). To better characterize the uncertainties in renewable generation and electric load, a deep learning gated recurrent unit is adopted to forecast the PV power output. The proposed model is tested on the IEEE 69-bus distribution network to validate the effectiveness and merits of MMPSs. Results show that reliability and resiliency could be enhanced by using MMPSs within the network.

Impact of implementing a price-based demand response program on the system reliability in security-constrained unit commitment problem coupled with wind farms in the presence of contingencies

Large scale penetration of highly intermittent wind energy sources has caused new challenges to the reliable operation of power systems. To address these challenges, demand response program is considered as an efficient solution to manage shift-able loads. In this paper, the impact of demand response on power system reliability has been evaluated by developing a two-stage stochastic security constraint unit commitment that considers both the wind volatility and line outages at the same time. The allocation of ramping products and spinning reserves to cover these uncertainties has also been modeled. wind curtailment and load shedding are considered as alternative strategies, and an optimal exchange between them and the use of spinning reserves and flexible ramping products has been modeled in the objective function. To assess the system reliability, the expected load not served (ELNS) index was evaluated in different cases. The proposed scheme as a mixed-integer linear programming problem was solved by a scenario-based two-stage stochastic programming method. The IEEE test systems 6-bus, modified 24-bus, and 118-bus were examined numerically. The results show that the simultaneous consideration of demand response and flexible ramping product coordinated with wind energy has adequate flexibility to reduce the reliability index and system operational cost.

A zonal optimization solution to reliability security constraint unit commitment with wind uncertainty

In restructured power systems, Independent System Operator manages and handles the Reliability-Security Constraint Unit Commitment problems including reliability and security issues. In this paper, a novel two-level optimization approach is proposed to achieve reliable, secure, and optimal generation units’ schedule while wind generation units are presents, in which the power system is divided to a number of zones. Uncertainties and time-dependent sources such as wind generation units are the most significant reasons for reliability challenges. In the proposed approach, load forecast and wind generation units’ uncertainty have been considered. An intelligent search technique is implemented for reliability study. The proposed method is evaluated by simulation of the 6-bus, 118-bus, and 4672-bus test systems. The two-level optimization is compared to robust optimization and centralized methods. The results show the effectiveness and significance of this method.

A novel evolving framework for energy management in wind‐gas reinforced unit commitment with demand response

This research work tries to investigate the provision of flexibility on both sides of production and demand security constraint unit commitment (SCUC) before the schedule is considered. To this end, a powerful heuristic technique based on modified firefly algorithm (FA) is devised to achieve the optimal solution. Moreover, fast-starting gas units (FGUs) are considered as providers of lateral flexibility as a result of their quickness in starting work and high ramp capability. Considering the fact that the normal operation of units is subject to the supply of reliable gas through connected gas transmission lines, the uncertainty of gas supply in the suggested model is considered to imitate the effects of deviation in the volume of gas over pipelines. The application of the suggested model has been tested on IEEE-118 bus.

Security-Constraint Unit Commitment for AC/DC Transmission Systems with Voltage Stability Constraint

Due to the inherent characteristics of weaker voltage supporting ability, line-commutated converter based HVDC technologies have significant effects on AC/DC hybrid power grid’s voltage stability. These has led to new challenges for power grid operators in terms of ensuring power system security. To address these challenges, a unit commitment of receiving-end in AC/DC hybrid grid is presented in this paper. In the proposed model, we employ static voltage stability constraints to guarantee enough voltage supporting capacity from thermal plants at HVDC feed-in area. Based on the characteristics of the model, Benders decomposition and mixed integer programming algorithm are used to get the optimal transmission power of HVDC and schedule of thermal generators. The study is done by considering IEEE-39 and Jiangsu power grid in eastern China, containing two and three HVDC transmission projections respectively. Numerical results on two benchmark problems illustrate the effectiveness of the proposed algorithm, both in terms of convergence rate and solution quality.

A Novel Strategy to Reduce Computational Burden of the Stochastic Security Constrained Unit Commitment Problem

The uncertainty related to the massive integration of intermittent energy sources (e.g., wind and solar generation) is one of the biggest challenges for the economic, safe and reliable operation of current power systems. One way to tackle this challenge is through a stochastic security constraint unit commitment (SSCUC) model. However, the SSCUC is a mixed-integer linear programming problem with high computational and dimensional complexity in large-scale power systems. This feature hinders the reaction times required for decision making to ensure a proper operation of the system. As an alternative, this paper presents a joint strategy to efficiently solve a SSCUC model. The solution strategy combines the use of linear sensitivity factors (LSF) to compute power flows in a quick and reliable way and a method, which dynamically identifies and adds as user cuts those active security constraints N − 1 that establish the feasible region of the model. These two components are embedded within a progressive hedging algorithm (PHA), which breaks down the SSCUC problem into computationally more tractable subproblems by relaxing the coupling constraints between scenarios. The numerical results on the IEEE RTS-96 system show that the proposed strategy provides high quality solutions, up to 50 times faster compared to the extensive formulation (EF) of the SSCUC. Additionally, the solution strategy identifies the most affected (overloaded) lines before contingencies, as well as the most critical contingencies in the system. Two metrics that provide valuable information for decision making during transmission system expansion are studied.

Resilient Distribution Networks Considering Mobile Marine Microgrids: A Synergistic Network Approach

This paper proposes a resilient and secure configuration for coastal distribution grids by integrating the security constraint unit commitment (SCUC) and mobile marine microgrids (MMMGs). In the proposed configuration, MMMGs can be connected to the coastal distribution grids in both normal and post-disaster operations. It is assumed that both MMMGs and SCUC networks include both dispatchable (e.g., gas turbines and diesel generators) and nondispatchable generators (e.g., photovoltaics and wind turbines). The proposed problem consists of realistic formulations that seek to minimize the total MMMGs and SCUC operation costs, while maximizing distribution grid resiliency. A heuristic technique, known as the collective decision optimization algorithm, is employed to address the complexity and nonlinearity of the formulated problem. Moreover, the unscented transform technique is adopted to model the uncertainties associated with renewable energy sources output and load demand. To show the effectiveness and merits of the proposed configuration, the IEEE 69-bus distribution network is selected and tested for both normal and post-disaster operations.

Optimal Reserve Determination Considering Demand Response in the Presence of High Wind Penetration and Energy Storage Systems

Qualification of the reserve requirement of power systems in the presence of load uncertainties and renewable energy resources is one of the most important challenges of system operators. Especially, existence of wind turbines with unavoidable volatility in their generated powers makes this problem more serious. In this paper, is proposed a probabilistic method for optimal determining of the spinning and non-spinning reserves. In this method, the required optimal reserve level would be determined via simultaneously optimizing the operation cost (OC) and the expected energy not supplied (EENS) cost under security constraint unit commitment. That is, OC includes the cost of both reserve market and energy markets and EENS is computed using a piecewise linear function. The demand response program is considered to provide the reserve service from the demand side. These improve the power system reliability and also reduce the OC. Besides, energy storage systems have been included as a promising approach to diminish the uncertainties of wind power and electrical load. The method is formulated in a two-stage stochastic programming framework, where the first stage represents the day-ahead market, and the second stage deals with the real-time market. Also, a multi-step algorithm has been presented to implement the proposed model. Finally, the well-known 3-buses and 24-buses test systems would be used to verify the efficiency of proposed model.

Evaluating the operational flexibility for wind energy integration in Nigeria using a security constraint unit commitment model

The study evaluated the flexible techno-economic operations of thermal plants for sustainable wind power integration into the Nigerian electricity industry using security constraint unit commitment approach. This provides empirical evidence on the thermal power plants capability to back-up variable generation from wind energy. Relative to the current generation mix, 10% and 20% wind energy penetration increased the system spinning reserve per day from 702.5 to 1507.5 and 2107.5 MW respectively. Thermal plants total numbers of start-up per day decreased from 23 to 14 and 18, and shutdown hours per day decreased from 52 to 44 and 49 hrs in 10% and 20% wind energy integrated system, respectively. Greenhouse emission reduction per day were 1746.6 and 3254.4 lb, and thermal plants operational revenue reduced by 3.7 and 7.0% daily in 10% and 20% wind energy integrated system, respectively.

Evaluating the operational flexibility for wind energy integration in Nigeria using a security constraint unit commitment model

Evaluating the operational flexibility for wind energy integration in Nigeria using a security constraint unit commitment model

A New Formulation to Reduce the Number of Variables and Constraints to Expedite SCUC in Bulky Power Systems

This paper proposes a new formulation to speed up the security constraint unit commitment (SCUC) solution in large scale power systems. The number of variables and prevailing constraints grow drastically as the number of system buses and the credible contingencies increase. So, as the first stage, inessential variables and constraints are eliminated and necessary variables for a tighter formulation are defined. Some constraints and variables are removed and some constraints are modified based on the results of a small sub-problem at each iteration of Benders decomposition algorithm. By utilizing the proposed framework, especially in the case of large number of severe contingencies, a large number of variables and constraints will be eliminated. Up- and down-going reserves are considered at both generation- and demand-sides. The IEEE RTS1 and RTS2 systems are studied as illustrative examples. The SCUC results drawn using the proposed algorithm are compared with those obtained by a conventional MIP-based algorithm to show the effectiveness of the proposed algorithm.

The Effects of Demand Response on Security-Constrained Unit Commitment

This paper aims to study the effect of the hourly demand response (DR) on security-constraint unit commitment (SCUC) problem with considering economic and security objectives. The demand side participation can solve some of the electricity market problems. Here, DR is take into consideration as one of the demand side management (DSM) parts. The DR is consist of fixed and responsive loads. The fixed loads satisfy in any circumstance and responsive loads can curtail or shift to other operating hours. The combination of SCUC with DR is a complex and the mixed integer non-linear problem. The bender’s decomposition is used as an optimization technique for solve this problem. This technique solves the problem by decompose it into master and sub problems. One of the effective of this manner is reducing the processing time. The performance and effectiveness of the proposed method are demonstrated on 6-, 24- and 118-bus test systems.

MIP Reformulation for Max-Min Problems in Two-Stage Robust SCUC

With increasing renewable penetration in power systems, considerable research efforts have been focused on how to accommodate the uncertainties from renewables in the Security-Constraint Unit Commitment (SCUC) problem. One of the candidate approaches to handling uncertainties is the two-stage Robust SCUC (RSCUC), which enables system to survive in any scenario. The survivability is guaranteed by the solution optimality of the max-min problem in the second stage. However, as the non-convex max-min problem is NP-hard, it is difficult to get the exact optimal solution in acceptable time. In this paper, we propose a new efficient formulation which recasts the max-min problem to a Mixed Integer Programming (MIP) problem using Binary Expansion (BE). The upper bound of the gap between the new MIP problem and the original max-min problem is derived. The gap, which quantifies the solution optimality of the max-min problem, is controllable. Two effective acceleration techniques are proposed to improve the performance of the MIP problem by eliminating inactive flow constraints and decomposing time-coupled uncertainty budget constraints. Accordingly, the computation burden of solving the max-min problem is reduced tremendously. The simulation results for the IEEE 118-Bus system validate and demonstrate the effectiveness of the new BE-based solution approach to the two-stage RSCUC and the acceleration techniques.

Flexibility evaluation of integrating solar power into the Nigerian electricity grid

The study evaluated the capability of current thermal generation to back-up variation generation from solar energy penetration into the Nigerian power grid from a system operation perspective using security constraint unit commitment model. This provides an empirical evidence of the impacts that can tip the balance towards a sustainable future low carbon electricity mix. Through 10 and 20% solar energy penetration scenarios, greenhouse reduction of 1975.70 and 3590.03 lb/day, respectively, can be achieved. However, daily peak-valley net demand difference to be supplied by the thermal plants will increase from 702.5 to 857.5 and 1607.5 MW, numbers of daily start-up will increase from 23 to 30 and 25, daily system spinning reserve will increase from 723 to 757 and 815 MW and daily idle hours of the thermal plants will increase from 52 to 71 and 72 h, in a 10 and 20% solar energy integrated system, respectively. The daily operational revenue of the thermal plants will also reduce by 5.5 and 7.9% in a 10 and 20% solar energy integrated system, respectively. These are useful data in developing policy framework for the future electricity market as the country diversify her energy source and mitigate greenhouse effect.

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.

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

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

Optimal scheduling of distributed battery storage for enhancing the security and the economics of electric power systems with emission constraints

In this paper, the sustainable day-ahead scheduling of electric power systems with the integration of distributed energy storage devices is investigated. The main objective is to minimize the hourly power system operation cost with a cleaner, socially responsible, and sustainable generation of electricity. Emission constraints are enforced to reduce the carbon footprint of conventional thermal generating units. The stationary electric vehicles (EV) are considered as an example of distributed storage and vehicle to grid (V2G) technology is considered to demonstrate the bilateral role of EV as supplier and consumer of energy. Battery storage can ease the impact of variability of renewable energy sources on power system operations and reduce the impact of thermal generation emission at peak hours. We model the day-ahead scheduling of electric power systems as a mixed-integer linear programing (MILP) problem for solving the hourly security-constraint unit commitment (SCUC). In order to expedite the real-time solution for large-scale power systems, we consider a two-stage model of the hourly SCUC by applying the Benders decomposition (BD). The Benders decomposition would separate the hourly generation unit commitment (UC) in the master problem from the power network security check in subproblem. The subproblem would check dc network security constraints for the given UC solution to determine whether a converged and secure dc power flow can be obtained. If any power network violations arise, corresponding Benders cuts are formed and added to the master problem for solving the next iteration of UC. The iterative process will continue until the network violations are eliminated and a converged hourly solution is found for scheduling the power generating units. Numerical simulations are presented to illustrate the effectiveness of the proposed MILP approach and its potentials as an optimization tool for sustainable operations of electric power grids.

Improving the Accuracy of Bus Load Forecasting by a Two-Stage Bad Data Identification Method

As a critical data input of security constraint unit commitment, bus load forecasting is currently conducted on a bus-by-bus fashion to improve the forecasting accuracy in most provinces in China. On such substation level forecasting, data quality is much worse than the aggregated power demand for the whole system, and identifying and restoring the inaccurate measurement and abnormal disturbance to retrieve the historical trend of load is urged to improve the forecasting accuracy. In this paper, a two-stage identification and restoration method is presented. The typical patterns of inaccurate measurement and abnormal disturbance are detected in the first stage based on statistical criteria independent with normal distribution. Historical trend is further retrieved in the second stage using frequency domain decomposition, and a typical daily curve is generated to compare with the data measurements. The deviations of the data measurements from the typical daily curve obey normal distribution and are used as criteria in the second stage. The effectiveness of the proposed methodology has been confirmed by examples in real bus load forecasting systems in this paper.