A model to incorporate Demand Response Programs in Security Constrained Unit Commitment

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.

Stochastic two-stage reliability-based Security Constrained Unit Commitment in smart grid environment

Implementing an applicable demand response (DR) program enables the complete demand-side potentials and ensures a secure, more economic and greener operation of the power systems with the integration of renewable energy. Therefore, the present paper proposes a stochastic security-constraint scheduling approach for optimum operation of both supply and demand sides via well-designed pricing and incentive schemes. The DR programs are time-of-use and emergency DR programs. The study addresses the Independent System Operator (ISO)'s viewpoint, and it aims at finding the optimal DR strategy (from a set of DR programs) in a way that an efficient electricity market is obtained, ensuring the security and environmental constraints. To this end, a security constraint unit commitment (SCUC) problem considering DR and renewable energy resources is proposed. Different indices are considered through a multi-objective problem for evaluating the efficiency of the market, security of the system, reliability and air pollution. These indices include market prices, social welfare, load factor (peak-to-valley proportion), air pollution, and power security, among others. In order to find the best DR strategy, a multi-objective problem is solved to consider all the mentioned indices.

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

This paper presents Security Constraint Unit Commitment (SCUC) backup plan considering single contingency. The proposed method leads solution to obtain optimal units and reserve schedule. In equivalent linear expression of the problem, shedding costs are used to avoid divergence and resolve congestion problem. Obtained load shedding in contingency case are utilized to achieve an optimal reserve requirements. Mixed Integer Linear Programming (MILP) is employed to minimize the total energy dispatch cost in 24 hours of a day. Numerical results show the proposed joint auction model can clear energy and reserve market while system violation and unit outage are considered.

This paper studies how to sample load more realistically and efficiently for security constraint unit commitment (SCUC) problems in order to achieve a high degree of robustness of the unit commitment (UC) solution. For example, given the UC solution, 95% of load profiles can be supplied. Principal component analysis (PCA) is introduced to find a clear feature of the historical load in two-dimensional space rather than the original high-dimensional load space, whose feature is hard to capture. Kernel density estimation (KDE) with Gaussian kernel is applied to form the probability density function (PDF), from which hourly load profiles are sampled. The load profiles based on sparse sampling are used to find the UC solution with high robustness while the load profiles based on dense sampling are used to verify the robustness of the obtained UC solution.

Unified solution of a non-convex SCUC problem using combination of modified Branch-and-Bound method with Quadratic Programming

-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 a re-structured environment, demand response (DR) programs are presented in a new style. The demand response program consists of demand-side management methods which answers to electricity price variations. With advent of electricity markets, the demand-side management programs was introduced into two categories: (1) energy efficiency program, (2) demand response program. This paper studies engagement of participants load in an electricity market having a grid with large and small loads interested to participate in the market, energy storage systems, micro-grids, and distributed generations. In the proposed scheme, it is supposed to have an aggregator which sends demand-side preferences including load curtailment, load shifting, onsite generation, and energy storage systems along with proposed value and prices and all respective system constraints to the independent system operator (ISO). In fact, load aggregators submit aggregated DR offers to the ISO in order to optimize final decisions on aggregators’ DR contributions in wholesale market. The main goal of this paper is to solve the operation problem considering demand-side, system, and pollution and reliability constraints. Compared to other methods, the results indicate that the explicit modeling of customer DR would provide ISOs with more flexible options for scheduling the available energy resources in day-ahead energy markets.

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.

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.

-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.

A pool-based electricity retail markets integrating renewable energy sources and electric vehicles in the presence of demand response program and conditional value at risk to enhance energy security

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.

In power markets, SO can maintain system security by preventively restraining the energy transactions or, if having procured sufficient reserves, by dispatching the reserves correctively after any contingency happens. The traditional security constrained unit commitment (SCUC) or economic dispatch (SCED), being with all the contingency constraints, probably leads to lower market efficiency. In this paper, a security coordinated economic dispatch (SCoED) model is presented for day-ahead energy and reserve joint market, which is formulated as a Stackelberg leader-follower problem, the upper level determining the energy and reserve procurement schedules subjecting to only the normal constraints while in the lower level, economic dispatch of the procured reserves is executed for every possible N-l contingency to maintain system security. A numerical example is carried out on a 6-bus system to compare the energy market efficiency and reserve procurement cost under the traditional SCED and the SCoED.