A Heuristic algorithm to solve the unit commitment problem for real-life large-scale power systems (original) (raw)
Related papers
A MIQCP formulation to solve the unit commitment problem for large-scale power systems
International Journal of Electrical Power & Energy Systems, 2012
In this paper, a mixed integer quadratically constrained program to solve the unit commitment problem is presented. It is the most complete model found in the literature until now and it can be used to solve real-life, large-scale power systems. The model considers thermal conventional plants, independent power producers, interruptible loads, and a simplified representation of combined cycle plants and hybrid combined cycle plants using the aggregated model. The objective function includes variable generation costs and fixed start-up costs. Important constraints like spinning reserve, power flows in tie-lines, and quadratic fuel consumption constraints are included, among others. Also, the status of every single unit is considered; if the unit is available, if the unit can be committed, and if the unit can be dispatched. The model is implemented in Intel (R) Fortran 11.0 and solved using the commercial optimization software IBM CPLEX 12.1. To prove the usefulness of the formulation, a real life power system is solved for a twenty-four hour planning horizon based on the nodal representation of the Mexican Power System.
An Optimization Framework for Power Systems Planning Considering Unit Commitment Constraints
Advances in Energy Systems Engineering, 2016
This chapter presents a generic mixed integer linear programming (MILP) model that integrates the unit commitment problem (UCP), i.e., daily energy planning with the long-term generation expansion planning (GEP) framework. Typical daily constraints at an hourly level such as start-up and shutdown related decisions (start-up type, minimum up and down time, synchronization, soak and desynchronization time constraints), ramping limits, system reserve requirements are combined with representative yearly constraints such as power capacity additions, power generation bounds of each unit, peak reserve requirements, and energy policy issues (renewables penetration limits, CO 2 emissions cap and pricing). For modelling purposes, a representative day (24 h) of each month over a number of years has been employed in order to determine the optimal capacity additions, electricity market clearing prices, and daily operational planning of the studied power system. The model has been tested on an illustrative case study of the Greek power system. Our approach aims to provide useful insight into strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level by providing the optimal energy roadmap under real operating and design constraints.
A new MILP-based approach for unit commitment in power production planning
International Journal of Electrical Power and Energy Systems, 2013
This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker.
Unit Commitment in Composite Generation & Transmission Systems using Dynamic Programming
… -Cum-Conference on Recent Trends in …, 2012
In this paper, a unit commitment problem is being described & its solution using dynamic programming for 5 unit system over 24 hour time horizon is being presented. This also means that it is desirable to find the optimal generating unit commitment (UC) in the power system for the next H hours. The main objective of this paper is to reduce the total production cost includes fuel cost, maintenance cost etc. The 3 versions of DP are presented and their results are compared.
Solving the Unit Commitment Problem in Power Generation by Primal and Dual Methods
Progress in Industrial Mathematics at ECMI 96, 1997
The unit commitment problem in power plant operation planning is addressed. For a real power system comprising coal-and gas-red thermal and pumpedstorage hydro plants a large-scale mixed integer optimization model for unit commitment is developed. Then primal and dual approaches to solving the optimization problem are presented and results of test runs are reported.
Mixed-integer formulation of unit commitment problem for power systems: Focus on start-up cost
IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, 2013
In this work, the Mixed-Integer (MIP) formulation for unit commitment problem (UC) for power systems is discussed. A new formulation for the start-up cost is suggested as well. This new formulation of the start-up cost exploits the transformation of the conditional statements into inequalities that comprise linear combination of binary variables. Solutions of the suggested optimization problem were obtained. A comparison between these solutions and those of a strategy common in literature is held to show that the new strategy gives same results with less number of constraints and tighter capture of the startup cost.
52nd IEEE Conference on Decision and Control, 2013
Unit Commitment (UC) is a minimization problem that aims to schedule the required generating units in a power system over some time horizon to meet the demand based on minimizing the production cost. In this paper, we present a novel technique to minimize such functions based on Mixed-integer formulation, neglecting the time horizon and most of the constraints. This technique can be considered as a first step in a better and tighter mixed-integer formulation of the unit commitment problem, especially for isolated power systems that contain a small number of generating units. Data from isolated power systems on marine vessels are used to test this technique. The proposed technique requires more constraints and binary variables. However, the numerical results presented in this work, show that the proposed method gives more efficient results for low demand, and close results to those obtained from local minimizers when the demand is high. The computational time of the suggested method does not seem to be explicitly longer than the time taken by the local minimizers, especially for small isolated power systems.
European Journal of Operational Research, 2008
The paper addresses the unit commitment in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which means that production planning must be done in coordination. We introduce in this paper the DP-RSC1 algorithm, which is a variant of the dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units and sequential commitment of units one by one. The time complexity of DP-RSC1 is proportional to the number of generating units in the system, the number of periods over the planning horizon and the time for solving a single-period economic dispatch problem. We have compared the DP-RSC1 algorithm with realistic power plants against the unit decommitment algorithm and the traditional priority listing method. The results show that the DP-RSC1 algorithm gives somewhat more accurate results (0.08-0.5% on average, maximum 10% for the individual sub-case) and executes 3-5 times faster on average than the unit decommitment algorithm. It is not surprising that the solution quality of the DP-RSC1 algorithm is much better than that of the priority listing method.
Unit Commitment Problem in Electrical Power System: A Literature Review
International Journal of Electrical and Computer Engineering (IJECE), 2018
Unit commitment (UC) is a popular problem in electric power system that aims at minimizing the total cost of power generation in a specific period, by defining an adequate scheduling of the generating units. The UC solution must respect many operational constraints. In the past half century, there was several researches treated the UC problem. Many works have proposed new formulations to the UC problem, others have offered several methodologies and techniques to solve the problem. This paper gives a literature review of UC problem, its mathematical formulation, methods for solving it and Different approaches developed for addressing renewable energy effects and uncertainties.