Generally, the procedure for Solving Security constrained unit commitment (SCUC) problems within Lagrangian Relaxation framework is partitioned into two stages: one is to obtain feasible SCUC states;the other is to so...Generally, the procedure for Solving Security constrained unit commitment (SCUC) problems within Lagrangian Relaxation framework is partitioned into two stages: one is to obtain feasible SCUC states;the other is to solve the economic dispatch of generation power among all the generating units. The core of the two stages is how to determine the feasibility of SCUC states. The existence of ramp rate constraints and security constraints increases the difficulty of obtaining an analytical necessary and sufficient condition for determining the quasi-feasibility of SCUC states at each scheduling time. However, a numerical necessary and sufficient numerical condition is proposed and proven rigorously based on Benders Decomposition Theorem. Testing numerical example shows the effectiveness and efficiency of the condition.展开更多
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 t...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.展开更多
This paper studies the rolling security-constrained unit commitment(RSCUC)problem with AC power flow and uncertainties.For this NP-hard problem,it is modeled as a Markov decision process,which is then solved by a tran...This paper studies the rolling security-constrained unit commitment(RSCUC)problem with AC power flow and uncertainties.For this NP-hard problem,it is modeled as a Markov decision process,which is then solved by a transfer-based approximate dynamic programming(TADP)algorithm proposed in this paper.Different from traditional approximate dynamic programming(ADP)algorithms,TADP can obtain the commitment states of most units in advance through a decision transfer technique,thus reducing the action space of TADP significantly.Moreover,compared with traditional ADP algorithms,which require to determine the commitment state of each unit,TADP only needs determine the unit with the smallest on-state probability among all on-state units,thus further reducing the action space.The proposed algorithm can also prevent the iter-ative update of value functions and the reliance on rolling forecast information,which makes more sense in the rolling decision-making process of RSCUC.Finally,nu-merical simulations are carried out on a modified IEEE 39-bus system and a real 2778-bus system to demonstrate the effectiveness of the proposed algorithm.展开更多
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 powe...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).展开更多
In this paper,a strength-constrained unit commitment(UC)model incorporating system strength constraints based on the weighted short-circuit ratio(WSCR)is proposed.This model facilitates the comprehensive assessment of...In this paper,a strength-constrained unit commitment(UC)model incorporating system strength constraints based on the weighted short-circuit ratio(WSCR)is proposed.This model facilitates the comprehensive assessment of area-wide system strength in power systems with high inverter-based resource(IBR)penetration,thereby contributing to the mitigation of weak grid issues.Unlike traditional models,this approach considers the interactions among multiple IBRs.The UC problem is initially formulated as a mixed-integer nonlinear programming(MINLP)model,reflecting WSCR and bus impedance matrix modification constraints.To enhance computational tractability,the model is transformed into a mixed-integer linear programming(MILP)form.The effectiveness of the proposed approach is validated through simulations on the IEEE 5-bus,IEEE 39-bus,and a modified Korean power system,demonstrating the ability of the proposed UC model enhancing system strength compared to the conventional methodologies.展开更多
Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerg...Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerging power grids,fruitful research results on SCUC have been obtained.Therefore,it is essential to review current work and propose future directions for SCUC to meet the needs of developing power systems.In this paper,the basic mathematical model of the standard SCUC is summarized,and the characteristics and application scopes of common solution algorithms are presented.Customized models focusing on diverse mathematical properties are then categorized and the corresponding solving methodologies are discussed.Finally,research trends in the field are prospected based on a summary of the state-of-the-art and latest studies.It is hoped that this paper can be a useful reference to support theoretical research and practical applications of SCUC in the future.展开更多
With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangemen...With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangement for the long-term power generation plan has become more crucial. Security-constrained unit commitment(SCUC) is a critical technical means to optimize the long-term power generation plan. However, the plentiful power sources and the complex grid structure in largescale power systems will bring great difficulties to long-term SCUC. In this paper, we propose a fast calculation method for long-term SCUC of large-scale power systems with renewable energy. First, a method for unit status reduction based on temporal decomposition is proposed, which will reduce plenty of binary variables and intertemporal constraints in SCUC. Then,an efficient redundant constraint identification(RCI) method is developed to reduce the number of network constraints. Furthermore, a joint accelerated calculation framework for status reduction and RCI is formed, which can reduce the complexity of long-term SCUC while ensuring a high-precision feasible solution. In case studies, numerical results based on two test systems ROTS2017 and NREL-118 are analyzed, which verify the effectiveness and scalability of the proposed calculation method.展开更多
Contingency analysis is an important building block in the stability and reliability analysis of power grid operations. However, due to the large number of transmission lines,in practice only a limited number of conti...Contingency analysis is an important building block in the stability and reliability analysis of power grid operations. However, due to the large number of transmission lines,in practice only a limited number of contingencies could be evaluated. This paper proposes a graph theory based N-1 contingency selection method to effectively identify the most critical contingencies, which can be used in security-constrained unit commitment(SCUC) problems to derive secure and economic operation decisions of the power grid. Specifically, the power flow transferring path identification algorithm and the vulnerability index are put forward to rank individual contingencies according to potential transmission line overloads. Effectiveness of the proposed N-1 contingency selection method is quantified by applying the corresponding SCUC solution to the full N-1 security evaluation, i. e., quantifying total post-contingency generation-load imbalance in all N-1 contingencies. Numerical results on several benchmark IEEE systems, including5-bus, 24-bus, and 118-bus systems, show effectiveness of the proposed method. Compared with existing contingency selection methods which usually resort to full power flow calculations,the proposed method relies on power gird topology to effectively identify critical contingencies for facilitating the optimal scheduling of SCUC problems.展开更多
As the issues of security and stability of power systems are becoming increasingly significant,it is necessary to consider the constraints of the static voltage stability and transient stability,which are closely rela...As the issues of security and stability of power systems are becoming increasingly significant,it is necessary to consider the constraints of the static voltage stability and transient stability,which are closely related to the active power dispatch of power systems,in the daily power dispatch,i.e.the unit commitment.However,due to the complexity of these constraints and limitation of the existing analysis methods,there has been no unit commitment model reported so far that can deal with these security constraints.On the other hand,as lack of effective measures to evaluate the security margin of dispatch schemes,it is difficult for power system operators to integrate both the security and economy of power systems in unit commitment.To resolve the above-mentioned issues,a security region based security-constrained unit commitment model is presented in the paper,which gives consideration to both the security and economy of power systems.For the first time,the active power flow constraint,the static voltage stability constraint and the transient stability constraint are taken into account in unit commitment at the same time.The model presented in the paper takes the operating cost,the branch transmission capacity margin,the static voltage stability margin and the transient stability margin as sub-objectives.By adjusting the weighting factors of sub-objectives,it is convenient to adjust the preference on the security and economy of power systems and reach a balance.The IEEE RTS-24 test system is adopted to validate the correctness and the efficiency of the proposed model.展开更多
In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and fl...In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.展开更多
Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenario...Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.展开更多
The Unit Commitment Problem(UCP)corresponds to the planning of power generation schedules.The objective of the fuel-based unit commitment problem is to determine the optimal schedule of power generators needed to meet...The Unit Commitment Problem(UCP)corresponds to the planning of power generation schedules.The objective of the fuel-based unit commitment problem is to determine the optimal schedule of power generators needed to meet the power demand,which also minimizes the total operating cost while adhering to different constraints such as power generation limits,unit startup,and shutdown times.In this paper,four different binary variants of the Bald Eagle Search(BES)algorithm,were introduced,which used two variants using S-shape,U-shape,and V-shape transfer functions.In addition,the best-performing variant(using an S-shape transfer function)was selected and improved further by incorporating two binary operators:swap-window and window-mutation.This variation is labeled Improved Binary Bald Eagle Search(IBBESS2).All five variants of the proposed algorithm were successfully adopted to solve the fuel-based unit commitment problem using seven test cases of 4-,10-,20-,40-,60-,80-,and 100-unit.For comparative evaluation,34 comparative methods from existing literature were compared,in which IBBESS2 achieved competitive scores against other optimization techniques.In other words,the proposed IBBESS2 performs better than all other competitors by achieving the best average scores in 20-,40-,60-,80-,and 100-unit problems.Furthermore,IBBESS2 demonstrated quicker convergence to an optimal solution than other algorithms,especially in large-scale unit commitment problems.The Friedman statistical test further validates the results,where the proposed IBBESS2 is ranked the best.In conclusion,the proposed IBBESS2 can be considered a powerful method for solving large-scale UCP and other related problems.展开更多
Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with bo...Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with both high input and output, it has an obvious economic significance to improve its operating efficiency. For an example, an unit is 10 GW scale, if its standard coal consumption can be decreased with 1 g/kW·h, it can save about 5 000 tons standard coal per year. It will be discussed mainly that how to establish optimization model and its numerical algorithm for operating management of the electric power system. The idea on establishing optimization model is how to dispatch work state of units or power plants, so that total cost of fuel consumption for generation is reduced to the minimum. Here the dispatch is to decide which unit or plant to operate, which unit or plant to stop running, how much power should be generated for those operating units or plants at each given time interval.展开更多
Unit commitment (UC) is to determine the optimal unit status and generation level during each time interval of the scheduled period. The purpose of UC is to minimize the total generation cost while satisfying system d...Unit commitment (UC) is to determine the optimal unit status and generation level during each time interval of the scheduled period. The purpose of UC is to minimize the total generation cost while satisfying system demand, reserve requirements, and unit constraints. Among the UC constraints, an adequate provision of reserve is important to ensure the security of power system and the fast-response reserve is essential to bring system frequency back to acceptable level following the loss of an online unit within a few seconds. In this paper, the authors present and solve a UC problem including the frequency-based reserve constraints to determine the optimal FRR requirements and unit MW schedules. The UC problem is solved by using Lagrangian Relaxation-based approach and compared with the actual system schedules. It is observed that favorable reserve and unit MW schedules are obtained by the proposed method while the system security is maintained.展开更多
Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considerin...Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.展开更多
The solar and wind renewable energy is developing very rapidly to fulfill the energy gap. This specific increasing share of renewable energy is a reaction to the ecological trepidations to conciliate economics with se...The solar and wind renewable energy is developing very rapidly to fulfill the energy gap. This specific increasing share of renewable energy is a reaction to the ecological trepidations to conciliate economics with security due to the new challenges in power system supply. In solar and wind renewable energy, the only partially predictable is the output with very low controllability which creates unit commitment problems in thermal units. In this research paper, a different linear formulation via mixed integer is presented that only requires “binary variables” and restraints concerning earlier stated models. The framework of this model allows precisely the costs of time-dependent startup & intertemporal limitations, for example, minimum up & down times and a ramping limit. To solve the unit commitment problem efficiently, a commercially available linear programming of mixed-integer is applied for sizeable practical scale. The results of the simulation are shown in conclusions.展开更多
This paper presents a new hybrid approach that combines Modified Priority List (MPL) with Charged System Search (CSS), termed MPL-CSS, to solve one of the most crucial power system’s operational optimization problems...This paper presents a new hybrid approach that combines Modified Priority List (MPL) with Charged System Search (CSS), termed MPL-CSS, to solve one of the most crucial power system’s operational optimization problems, known as unit commitment (UC) scheduling. The UC scheduling problem is a mixed-integer nonlinear problem, highly-dimensional and extremely constrained. Existing meta-heuristic UC solution methods have the problems of stopping at a local optimum and slow convergence when applied to large-scale, heavily-constrained UC applications. In the first step of the proposed method, initial hourly optimum solutions of UC are obtained by Modified Priority List (MPL);however, the obtained UC solution may still be possible to be further improved. Therefore, in the second step, the CSS is utilized to achieve higher quality solutions. The UC is formulated as mixed integer linear programming to ensure the tractability of the results. The proposed method is successfully applied to a popular test system up to 100 units generators for both 24-hr and 168-hr system. Computational results show that both solution cost and execution time are superior to those of published methods.展开更多
This paper presents a new method based on an immune-tabu hybrid algorithm to solve the thermal unit commitment （TUC） problem in power plant optimization. The mathematical model of the TUC problem is established by a...This paper presents a new method based on an immune-tabu hybrid algorithm to solve the thermal unit commitment （TUC） problem in power plant optimization. The mathematical model of the TUC problem is established by analyzing the generating units in modem power plants. A novel immune-tabu hybrid algorithm is proposed to solve this complex problem. In the algorithm, the objective function of the TUC problem is considered as an antigen and the solutions are considered as antibodies, which are determined by the affinity computation. The code length of an antibody is shortened by encoding the continuous operating time, and the optimum searching speed is improved. Each feasible individual in the immune algorithm （IA） is used as the initial solution of the tabu search （TS） algorithm after certain generations of IA iteration. As examples, the proposed method has been applied to several thermal unit systems for a period of 24 h. The computation results demonstrate the good global optimum searching performance of the proposed immune-tabu hybrid algorithm. The presented algorithm can also be used to solve other optimization problems in fields such as the chemical industry and the power industry.展开更多
This paper presents a novel approach to solve the Multi-Area unit commitment problem using particle swarm optimization technique. The objective of the multi-area unit commitment problem is to determine the optimal or ...This paper presents a novel approach to solve the Multi-Area unit commitment problem using particle swarm optimization technique. The objective of the multi-area unit commitment problem is to determine the optimal or a near optimal commitment strategy for generating the units. And it is located in multiple areas that are interconnected via tie lines and joint operation of generation resources can result in significant operational cost savings. The dynamic programming method is applied to solve Multi-Area Unit Commitment problem and particle swarm optimization technique is embedded for computing the generation assigned to each area and the power allocated to all committed unit. Particle Swarm Optimization technique is developed to derive its Pareto-optimal solutions. The tie-line transfer limits are considered as a set of constraints during the optimization process to ensure the system security and reliability. Case study of four areas each containing 26 units connected via tie lines has been taken for analysis. Numerical results are shown comparing the cost solutions and computation time obtained by using the Particle Swarm Optimization method is efficient than the conventional Dynamic Programming and Evolutionary Programming Method.展开更多
Renewable energy sources(RES)such as wind turbines(WT)and solar cells have attracted the attention of power system operators and users alike,thanks to their lack of environmental pollution,independence of fossil fuels...Renewable energy sources(RES)such as wind turbines(WT)and solar cells have attracted the attention of power system operators and users alike,thanks to their lack of environmental pollution,independence of fossil fuels,and meager marginal costs.With the introduction of RES,challenges have faced the unit commitment(UC)problem as a traditional power system optimization problem aiming to minimize total costs by optimally determining units’inputs and outputs,and specifying the optimal generation of each unit.The output power of RES such as WT and solar cells depends on natural factors such as wind speed and solar irradiation that are riddled with uncertainty.As a result,the UC problem in the presence of RES faces uncertainties.The grid consumed load is not always equal to and is randomly different from the predicted values,which also contributes to uncertainty in solving the aforementioned problem.The current study proposes a novel two-stage optimization model with load and wind farm power generation uncertainties for the security-constrained UC to overcome this problem.The new model is adopted to solve the wind-generated power uncertainty,and energy storage systems(ESSs)are included in the problem for further management.The problem is written as an uncertain optimization model which are the stochastic nature with security-constrains which included undispatchable power resources and storage units.To solve the UC programming model,a hybrid honey bee mating and bacterial foraging algorithm is employed to reduce problem complexity and achieve optimal results.展开更多
文摘Generally, the procedure for Solving Security constrained unit commitment (SCUC) problems within Lagrangian Relaxation framework is partitioned into two stages: one is to obtain feasible SCUC states;the other is to solve the economic dispatch of generation power among all the generating units. The core of the two stages is how to determine the feasibility of SCUC states. The existence of ramp rate constraints and security constraints increases the difficulty of obtaining an analytical necessary and sufficient condition for determining the quasi-feasibility of SCUC states at each scheduling time. However, a numerical necessary and sufficient numerical condition is proposed and proven rigorously based on Benders Decomposition Theorem. Testing numerical example shows the effectiveness and efficiency of the condition.
文摘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.
基金supported in part by the State Key Laboratory of HVDC(No.SKLHVDC-2021-KF-09)in part by the National Natural Science Foundation of China(No.51977081).
文摘This paper studies the rolling security-constrained unit commitment(RSCUC)problem with AC power flow and uncertainties.For this NP-hard problem,it is modeled as a Markov decision process,which is then solved by a transfer-based approximate dynamic programming(TADP)algorithm proposed in this paper.Different from traditional approximate dynamic programming(ADP)algorithms,TADP can obtain the commitment states of most units in advance through a decision transfer technique,thus reducing the action space of TADP significantly.Moreover,compared with traditional ADP algorithms,which require to determine the commitment state of each unit,TADP only needs determine the unit with the smallest on-state probability among all on-state units,thus further reducing the action space.The proposed algorithm can also prevent the iter-ative update of value functions and the reliance on rolling forecast information,which makes more sense in the rolling decision-making process of RSCUC.Finally,nu-merical simulations are carried out on a modified IEEE 39-bus system and a real 2778-bus system to demonstrate the effectiveness of the proposed algorithm.
基金supported by National Natural Science Foundation of China(No.51377035)NSFC-RCUK_EPSRC(No.51361130153)
文摘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).
基金partially supported by Korea Electrotechnology Research Institute(KERI)Primary research program through the National Research Council of Science&Technology(NST)funded by the Ministry of Science and ICT(MSIT)(No.25A01038)partially supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2024-00218377).
文摘In this paper,a strength-constrained unit commitment(UC)model incorporating system strength constraints based on the weighted short-circuit ratio(WSCR)is proposed.This model facilitates the comprehensive assessment of area-wide system strength in power systems with high inverter-based resource(IBR)penetration,thereby contributing to the mitigation of weak grid issues.Unlike traditional models,this approach considers the interactions among multiple IBRs.The UC problem is initially formulated as a mixed-integer nonlinear programming(MINLP)model,reflecting WSCR and bus impedance matrix modification constraints.To enhance computational tractability,the model is transformed into a mixed-integer linear programming(MILP)form.The effectiveness of the proposed approach is validated through simulations on the IEEE 5-bus,IEEE 39-bus,and a modified Korean power system,demonstrating the ability of the proposed UC model enhancing system strength compared to the conventional methodologies.
基金supported in part by the National Natural Science Foundation of China(No.51607104)。
文摘Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerging power grids,fruitful research results on SCUC have been obtained.Therefore,it is essential to review current work and propose future directions for SCUC to meet the needs of developing power systems.In this paper,the basic mathematical model of the standard SCUC is summarized,and the characteristics and application scopes of common solution algorithms are presented.Customized models focusing on diverse mathematical properties are then categorized and the corresponding solving methodologies are discussed.Finally,research trends in the field are prospected based on a summary of the state-of-the-art and latest studies.It is hoped that this paper can be a useful reference to support theoretical research and practical applications of SCUC in the future.
基金supported by the National Key R&D Program of China (No.2017YFB0902200)。
文摘With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangement for the long-term power generation plan has become more crucial. Security-constrained unit commitment(SCUC) is a critical technical means to optimize the long-term power generation plan. However, the plentiful power sources and the complex grid structure in largescale power systems will bring great difficulties to long-term SCUC. In this paper, we propose a fast calculation method for long-term SCUC of large-scale power systems with renewable energy. First, a method for unit status reduction based on temporal decomposition is proposed, which will reduce plenty of binary variables and intertemporal constraints in SCUC. Then,an efficient redundant constraint identification(RCI) method is developed to reduce the number of network constraints. Furthermore, a joint accelerated calculation framework for status reduction and RCI is formed, which can reduce the complexity of long-term SCUC while ensuring a high-precision feasible solution. In case studies, numerical results based on two test systems ROTS2017 and NREL-118 are analyzed, which verify the effectiveness and scalability of the proposed calculation method.
文摘Contingency analysis is an important building block in the stability and reliability analysis of power grid operations. However, due to the large number of transmission lines,in practice only a limited number of contingencies could be evaluated. This paper proposes a graph theory based N-1 contingency selection method to effectively identify the most critical contingencies, which can be used in security-constrained unit commitment(SCUC) problems to derive secure and economic operation decisions of the power grid. Specifically, the power flow transferring path identification algorithm and the vulnerability index are put forward to rank individual contingencies according to potential transmission line overloads. Effectiveness of the proposed N-1 contingency selection method is quantified by applying the corresponding SCUC solution to the full N-1 security evaluation, i. e., quantifying total post-contingency generation-load imbalance in all N-1 contingencies. Numerical results on several benchmark IEEE systems, including5-bus, 24-bus, and 118-bus systems, show effectiveness of the proposed method. Compared with existing contingency selection methods which usually resort to full power flow calculations,the proposed method relies on power gird topology to effectively identify critical contingencies for facilitating the optimal scheduling of SCUC problems.
文摘As the issues of security and stability of power systems are becoming increasingly significant,it is necessary to consider the constraints of the static voltage stability and transient stability,which are closely related to the active power dispatch of power systems,in the daily power dispatch,i.e.the unit commitment.However,due to the complexity of these constraints and limitation of the existing analysis methods,there has been no unit commitment model reported so far that can deal with these security constraints.On the other hand,as lack of effective measures to evaluate the security margin of dispatch schemes,it is difficult for power system operators to integrate both the security and economy of power systems in unit commitment.To resolve the above-mentioned issues,a security region based security-constrained unit commitment model is presented in the paper,which gives consideration to both the security and economy of power systems.For the first time,the active power flow constraint,the static voltage stability constraint and the transient stability constraint are taken into account in unit commitment at the same time.The model presented in the paper takes the operating cost,the branch transmission capacity margin,the static voltage stability margin and the transient stability margin as sub-objectives.By adjusting the weighting factors of sub-objectives,it is convenient to adjust the preference on the security and economy of power systems and reach a balance.The IEEE RTS-24 test system is adopted to validate the correctness and the efficiency of the proposed model.
文摘In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.
基金the Science and Technology Project of State Grid Corporation of China,Grant Number 5108-202304065A-1-1-ZN.
文摘Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.
文摘The Unit Commitment Problem(UCP)corresponds to the planning of power generation schedules.The objective of the fuel-based unit commitment problem is to determine the optimal schedule of power generators needed to meet the power demand,which also minimizes the total operating cost while adhering to different constraints such as power generation limits,unit startup,and shutdown times.In this paper,four different binary variants of the Bald Eagle Search(BES)algorithm,were introduced,which used two variants using S-shape,U-shape,and V-shape transfer functions.In addition,the best-performing variant(using an S-shape transfer function)was selected and improved further by incorporating two binary operators:swap-window and window-mutation.This variation is labeled Improved Binary Bald Eagle Search(IBBESS2).All five variants of the proposed algorithm were successfully adopted to solve the fuel-based unit commitment problem using seven test cases of 4-,10-,20-,40-,60-,80-,and 100-unit.For comparative evaluation,34 comparative methods from existing literature were compared,in which IBBESS2 achieved competitive scores against other optimization techniques.In other words,the proposed IBBESS2 performs better than all other competitors by achieving the best average scores in 20-,40-,60-,80-,and 100-unit problems.Furthermore,IBBESS2 demonstrated quicker convergence to an optimal solution than other algorithms,especially in large-scale unit commitment problems.The Friedman statistical test further validates the results,where the proposed IBBESS2 is ranked the best.In conclusion,the proposed IBBESS2 can be considered a powerful method for solving large-scale UCP and other related problems.
文摘Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with both high input and output, it has an obvious economic significance to improve its operating efficiency. For an example, an unit is 10 GW scale, if its standard coal consumption can be decreased with 1 g/kW·h, it can save about 5 000 tons standard coal per year. It will be discussed mainly that how to establish optimization model and its numerical algorithm for operating management of the electric power system. The idea on establishing optimization model is how to dispatch work state of units or power plants, so that total cost of fuel consumption for generation is reduced to the minimum. Here the dispatch is to decide which unit or plant to operate, which unit or plant to stop running, how much power should be generated for those operating units or plants at each given time interval.
文摘Unit commitment (UC) is to determine the optimal unit status and generation level during each time interval of the scheduled period. The purpose of UC is to minimize the total generation cost while satisfying system demand, reserve requirements, and unit constraints. Among the UC constraints, an adequate provision of reserve is important to ensure the security of power system and the fast-response reserve is essential to bring system frequency back to acceptable level following the loss of an online unit within a few seconds. In this paper, the authors present and solve a UC problem including the frequency-based reserve constraints to determine the optimal FRR requirements and unit MW schedules. The UC problem is solved by using Lagrangian Relaxation-based approach and compared with the actual system schedules. It is observed that favorable reserve and unit MW schedules are obtained by the proposed method while the system security is maintained.
文摘Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.
文摘The solar and wind renewable energy is developing very rapidly to fulfill the energy gap. This specific increasing share of renewable energy is a reaction to the ecological trepidations to conciliate economics with security due to the new challenges in power system supply. In solar and wind renewable energy, the only partially predictable is the output with very low controllability which creates unit commitment problems in thermal units. In this research paper, a different linear formulation via mixed integer is presented that only requires “binary variables” and restraints concerning earlier stated models. The framework of this model allows precisely the costs of time-dependent startup & intertemporal limitations, for example, minimum up & down times and a ramping limit. To solve the unit commitment problem efficiently, a commercially available linear programming of mixed-integer is applied for sizeable practical scale. The results of the simulation are shown in conclusions.
文摘This paper presents a new hybrid approach that combines Modified Priority List (MPL) with Charged System Search (CSS), termed MPL-CSS, to solve one of the most crucial power system’s operational optimization problems, known as unit commitment (UC) scheduling. The UC scheduling problem is a mixed-integer nonlinear problem, highly-dimensional and extremely constrained. Existing meta-heuristic UC solution methods have the problems of stopping at a local optimum and slow convergence when applied to large-scale, heavily-constrained UC applications. In the first step of the proposed method, initial hourly optimum solutions of UC are obtained by Modified Priority List (MPL);however, the obtained UC solution may still be possible to be further improved. Therefore, in the second step, the CSS is utilized to achieve higher quality solutions. The UC is formulated as mixed integer linear programming to ensure the tractability of the results. The proposed method is successfully applied to a popular test system up to 100 units generators for both 24-hr and 168-hr system. Computational results show that both solution cost and execution time are superior to those of published methods.
基金Project partially supported by the Lamar Research Enhancement Grant and the National Science Foundation Grant (No. DUE-0737173) to Dr. W. Zhu at Lamar University
文摘This paper presents a new method based on an immune-tabu hybrid algorithm to solve the thermal unit commitment （TUC） problem in power plant optimization. The mathematical model of the TUC problem is established by analyzing the generating units in modem power plants. A novel immune-tabu hybrid algorithm is proposed to solve this complex problem. In the algorithm, the objective function of the TUC problem is considered as an antigen and the solutions are considered as antibodies, which are determined by the affinity computation. The code length of an antibody is shortened by encoding the continuous operating time, and the optimum searching speed is improved. Each feasible individual in the immune algorithm （IA） is used as the initial solution of the tabu search （TS） algorithm after certain generations of IA iteration. As examples, the proposed method has been applied to several thermal unit systems for a period of 24 h. The computation results demonstrate the good global optimum searching performance of the proposed immune-tabu hybrid algorithm. The presented algorithm can also be used to solve other optimization problems in fields such as the chemical industry and the power industry.
文摘This paper presents a novel approach to solve the Multi-Area unit commitment problem using particle swarm optimization technique. The objective of the multi-area unit commitment problem is to determine the optimal or a near optimal commitment strategy for generating the units. And it is located in multiple areas that are interconnected via tie lines and joint operation of generation resources can result in significant operational cost savings. The dynamic programming method is applied to solve Multi-Area Unit Commitment problem and particle swarm optimization technique is embedded for computing the generation assigned to each area and the power allocated to all committed unit. Particle Swarm Optimization technique is developed to derive its Pareto-optimal solutions. The tie-line transfer limits are considered as a set of constraints during the optimization process to ensure the system security and reliability. Case study of four areas each containing 26 units connected via tie lines has been taken for analysis. Numerical results are shown comparing the cost solutions and computation time obtained by using the Particle Swarm Optimization method is efficient than the conventional Dynamic Programming and Evolutionary Programming Method.
文摘Renewable energy sources(RES)such as wind turbines(WT)and solar cells have attracted the attention of power system operators and users alike,thanks to their lack of environmental pollution,independence of fossil fuels,and meager marginal costs.With the introduction of RES,challenges have faced the unit commitment(UC)problem as a traditional power system optimization problem aiming to minimize total costs by optimally determining units’inputs and outputs,and specifying the optimal generation of each unit.The output power of RES such as WT and solar cells depends on natural factors such as wind speed and solar irradiation that are riddled with uncertainty.As a result,the UC problem in the presence of RES faces uncertainties.The grid consumed load is not always equal to and is randomly different from the predicted values,which also contributes to uncertainty in solving the aforementioned problem.The current study proposes a novel two-stage optimization model with load and wind farm power generation uncertainties for the security-constrained UC to overcome this problem.The new model is adopted to solve the wind-generated power uncertainty,and energy storage systems(ESSs)are included in the problem for further management.The problem is written as an uncertain optimization model which are the stochastic nature with security-constrains which included undispatchable power resources and storage units.To solve the UC programming model,a hybrid honey bee mating and bacterial foraging algorithm is employed to reduce problem complexity and achieve optimal results.
