Randomized Branching Strategy in Solving SCUC Model

Security-Constrained Unit Commitment (SCUC) problem and subsequently employing Flexible AC Transmission Systems (FACTS) controllers including Optimal Unified Power Flow Controller (OUPFC) play a crucial role in power systems operation and control in terms of increasing the security of energy transmission networks. The principal objective of the SCUC problem is to acquire the minimum operating cost simultaneously maintaining the security of the system. In this paper, significant attention is paid particularly to simultaneously control SCUC and OUPFC, since energy loss reduction and transmission lines capacity release can be effectively achieved with incorporating SCUC and OUPFC, and subsequently setting the effective variables. In this regard, the SCUC problem with the presence of OUPFC is solved as Nonlinear Programming with Discontinuous Derivatives (DNLP) framework and the proposed algorithm is implemented on two IEEE 14-bus and IEEE 30-bus systems using General Algebraic Modeling System (GAMS) software in order to optimize the total fuel cost, power losses and cost of OUPFC installation as objective functions in the multi-objective framework. The simulation results show the capability of the proposed algorithm to simultaneously determine the optimal location of the OUPFC and its settings in the SCUC problem and to improve the controllability of the power system operation.

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 constrained unit commitment (SCUC) is one of the most important daily tasks that independent system operators (ISOs) or regional transmission organizations (RTOs) must accomplish in daily electric power market. Security constraints have long been regarded as difficult constraints for unit commitment problems. If the inactive security constraints can be identified and eliminated, the SCUC problem can be greatly simplified. In this paper, a necessary and sufficient condition for a security constraint to be inactive is established. It is proved that all inactive constraints can be identified by solving a series of small-scale mixed integer linear programming (MILP) problems. More importantly, an analytical sufficient condition is established and most of the inactive constraints can be quickly identified without solving MILP or linear programming (LP) problems. A very important feature of the conditions obtained is that they are only related to the load demands and parameters of the transmission network. Numerical testing is performed for three power grids and the results are impressive. Over 85% of the security constraints are identified as inactive and the crucial transmission lines affecting the total operating cost are among those associated with the remaining security constraints, providing useful information for transmission planning.

-In this paper, Security-Constrained Unit Commitment (SCUC) model is proposed in a restructured power system. This model consists of a closed-loop modified Unit Commitment (UC) and Security-constrained Optimal Power Flow (SCOPF). The objective of this SCUC model is to obtain the maximum social welfare-based system operating cost while maintaining the system security. In conventional power systems, the demand was forecasted before market operation and determined as a fixed constant. Supplying this demand was therefore considered as a constraint. However, in restructured power system which is based on Standard Market Design (SMD), DISCOs offer the demand and their proposed prices; therefore the demand is modeled as an elastic load. Independent System Operator (ISO) is responsible for operating the power market. The ISO performed the power market using the SCUC software to obtain feasible and economical operation as much as possible. In this paper, Harmony Search Algorithm (HSA) has been implemented to solve SCUC problem. Since the SCUC problem is a non-linear, mixed integer, large scale and non-convex problem, harmony search optimization is addressed as an efficient technique to overcome the aforementioned challenges. The simulation results show that the presented method is both satisfactory and consistent with expectation.

-In this paper, Security-Constrained Unit Commitment (SCUC) model is proposed in a restructured power system. This model consists of a closed-loop modified Unit Commitment (UC) and Security-constrained Optimal Power Flow (SCOPF). The objective of this SCUC model is to obtain the maximum social welfare-based system operating cost while maintaining the system security. In conventional power systems, the demand was forecasted before market operation and determined as a fixed constant. Supplying this demand was therefore considered as a constraint. However, in restructured power system which is based on Standard Market Design (SMD), DISCOs offer the demand and their proposed prices; therefore the demand is modeled as an elastic load. Independent System Operator (ISO) is responsible for operating the power market. The ISO performed the power market using the SCUC software to obtain feasible and economical operation as much as possible. In this paper, Harmony Search Algorithm (HSA) has been implemented to solve SCUC problem. Since the SCUC problem is a non-linear, mixed integer, large scale and non-convex problem, harmony search optimization is addressed as an efficient technique to overcome the aforementioned challenges. The simulation results show that the presented method is both satisfactory and consistent with expectation.

Unit commitment, one of the most critical tasks in electric power system operations, faces new challenges as the supply and demand uncertainty increases dramatically due to the integration of variable generation resources such as wind power and price responsive demand. To meet these challenges, we propose a two-stage adaptive robust unit commitment model for the security constrained unit commitment problem in the presence of nodal net injection uncertainty. Compared to the conventional stochastic programming approach, the proposed model is more practical in that it only requires a deterministic uncertainty set, rather than a hard-to-obtain probability distribution on the uncertain data. The unit commitment solutions of the proposed model are robust against all possible realizations of the modeled uncertainty. We develop a practical solution methodology based on a combination of Benders decomposition type algorithm and the outer approximation technique. We present an extensive numerical study on the real-world large scale power system operated by the ISO New England. Computational results demonstrate the economic and operational advantages of our model over the traditional reserve adjustment approach.

In traditional electricity market unit commitment (UC) is done only for the reduction of operating cost. In the deregulated electricity market, for a secure and economical hourly generation schedule of the day ahead market, independent system operator (ISO) executes the security constrained unit commitment (SCUC) problem. The objective of the paper is to develop scheduling algorithm using hybrid particle swarm optimization (PSO) for electric generation that accounts directly for system security requirements. The proposed SCUC formulation includes constraints, such as hourly power demand, system reserves, ramp up/down limits, minimum ON/OFF duration limits. The innovation of our approach is to capture the system security requirements within a network flow sub-problem that is solved in conjunction with the unit commitment problem. To solve such SCUC model, a binary coded particle swarm optimization (BPSO) is used for unit commitment master problem and real coded particle swarm optimization (RPSO) is used for the economic dispatch sub-problem. The effectiveness of the suggested method to solve the SCUC problem is validated on different test systems.

Out of step with the rapid growth of China's electricity load demand, the infrastructure of power grid in many areas is not strong enough to insure the security of power system operation. In this case, considering the strict N-1 conditions of lines and transformers, the situation that there is no feasible solution for the security-constrained unit commitment (SCUC) might occasionally occur. In order to address this issue, a homogenized-overload model based on SCUC is proposed in this paper. The homogenized-overload model could obtain a reasonable, suboptimal solution reducing the security risks by lowering the average overload level and reducing the number of overload lines without sacrificing the economy of unit commitment. To identify the overload line set, an identifying method based on the Benders decomposition algorithm is also proposed. The homogenized-overload model and the identifying method are tested respectively in a 6-bus system case and a real provincial power system in China. Simulation results show the validity of the model and the method.

Considering the economics and securities for the operation of a power system, this paper presents a new adaptive dynamic programming approach for security-constrained unit commitment (SCUC) problems. In response to the “curse of dimension” problem of dynamic programming, the approach solves the Bellman’s equation of SCUC approximately by solving a sequence of simplified single stage optimization problems. An extended sequential truncation technique is proposed to explore the state space of the approach, which is superior to traditional sequential truncation in daily cost for unit commitment. Different test cases from 30 to 300 buses over a 24 h horizon are analyzed. Extensive numerical comparisons show that the proposed approach is capable of obtaining the optimal unit commitment schedules without any network and bus voltage violations, and minimizing the operation cost as well.

A novel robust security constrained unit commitment model considering HVDC regulation

This paper proposes an optimal estimation approach for the security-constrained unit commitment (SCUC) problem, which has the potential to be applied to some problems in the power system. A large number of numerical tests based on different systems show that the optimal operating cost of SCUC is not sensitive to the fluctuation of the injected power. The function between operating cost and the injected power can be obtained easily through using a simple data fitting method. Further tests show that the change in the power network topology will not have an excessive impact on the fitting effect, and the penetration rate of renewable energy is the main challenge. This conclusion can be used to quickly obtain the lower bound of the SCUC solution, and other actual scenarios that only focus on operating costs.

One of the most important tasks for day-ahead electricity markets is to do the Security-Constrained Unit Commitment (SCUC). SCUC generally combines the needs of unit commitment, network limits, and regulation in a constrained optimization problem for different time frames. Different electricity markets utilize different SCUC methods. The main goal of this work is to introduce SCUC operation experience in several electricity markets and summarize significant issues in the current SCUC problem. For instance, in addition to traditional constraints in the SCUC process, this work also investigates the effect of frequency stability, transmission switching, or optimal generation scheduling on the SCUC methods. Additionally, the integration of renewable energy also bring the impact to the traditional SCUC methods. The above mentioned issues concerning the SCUC topic will be studied herein.

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 .

This paper investigates the effects of Demand Response Programs (DRPs) on the behavior of electricity market players in the day-ahead energy market. To this end, an electricity market environment is proposed based on the multi-agent systems in order to model the strategic self-scheduling of each market player as an individual agent. In such oligopolistic environment, market interactions are considered by using a game theoretic model and the market transactions are cleared by means of a security constrained unit commitment problem. Different types of DRPs are also considered consisting of Time Of Use (TOU), Real Time Pricing (RTP), Critical Peak Pricing (CPP), and Emergency Demand Response Program (EDRP). The proposed model is applied on a modified IEEE six-bus test system. The numerical results indicate that different types of DRPs differently affect the oligopolistic behavior of market players that should be studied by the system operators before their implementation.

This paper proposes solving short-term unit commitment (UC) problems with security constraints by hybrid chaotic particle swarm optimization (CPSO). The objective of security-constrained UC (SC-UC) is to minimize the total generation cost, which is the sum of both transition cost and production cost of the scheduled combination units. The proposed CPSO method, which involves the chaotic map and the chaotic turbulence, can avoid premature convergence of PSO and escape local minima. Moreover, the proposed hybrid CPSO method has the ability of solving both the continuous and the discrete optimal programming problems. Two power systems are demonstrated for verifying the feasibility and effectiveness of the proposed method in solving SC-UC problems with constraints of a nonlinear generator and operation security assessment taken into consideration. The simulation results show that the proposed CPSO-based SC-UC method is indeed capable of obtaining efficiently high-quality UC solutions and enhancing the system security of UC operation.