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
A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Ak...A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.展开更多
Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interacti...Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interactions from service providers.Intruders can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered VMs.The existing system has issues with execution time and false-positive rates.Hence,the overall system performance is degraded considerably.The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position.Allocation of SECURITY Resources accepts a safety game in a simple format as input andfinds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear Programming(MILP)framework is used in the algorithm.The VM challenge is reduced by afirewall-based controlling mechanism combining behavior-based detection and signature-based virus detection.The pro-posed method is focused on detecting malware attacks effectively and providing better security for the VMs.Finally,the experimental results indicate that the pro-posed security method is efficient.It consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.展开更多
In this paper,a mixed integer linear programming(MILP)formulation for robust state estimation(RSE)is proposed.By using the exactly linearized measurement equations instead of the original nonlinear ones,the existingmi...In this paper,a mixed integer linear programming(MILP)formulation for robust state estimation(RSE)is proposed.By using the exactly linearized measurement equations instead of the original nonlinear ones,the existingmixed integer nonlinear programming formulation for RSE is converted to a MILP problem.The proposed approach not only guarantees to find the global optimum,but also does not have convergence problems.Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency.展开更多
在优化左转错位交叉口相位相序的基础上,提出了3套左转错位交叉口信号配时策略的混合整数规划(mixed integer linear programming,MILP)模型。MILP-1模型以交叉口通行能力最大为目标函数,以排队长度约束、最小绿灯时间约束、最大等待时...在优化左转错位交叉口相位相序的基础上,提出了3套左转错位交叉口信号配时策略的混合整数规划(mixed integer linear programming,MILP)模型。MILP-1模型以交叉口通行能力最大为目标函数,以排队长度约束、最小绿灯时间约束、最大等待时间约束共同构成约束集合。MILP-2模型引入进口道重要程度的概念,修正目标函数,调整优化方向,以期获得最真实的配时方案。通过引入若干等式约束,可以得到简化模型MILP-3,并可运用分枝定界算法予以求解。广州市白云区金钟横云龙路口是一个典型的左转错位交叉口,分别运用MILP-1模型、MILP-2模型及MILP-3模型进行配时设计,求解结果表明:3个模型均能得到合理的优化结果,且以MILP-2优化效果最佳,MILP-3优化速度最快。展开更多
针对采用设计水头的水电站混合整数线性规划(mixed integer linear programming,MILP)调度模型计算的出库流量与实际出库流量偏差较大的问题,提出了基于运行数据的水电站MILP模型最优代表水头选取方法。首先,基于运行数据采用MILP模型,...针对采用设计水头的水电站混合整数线性规划(mixed integer linear programming,MILP)调度模型计算的出库流量与实际出库流量偏差较大的问题,提出了基于运行数据的水电站MILP模型最优代表水头选取方法。首先,基于运行数据采用MILP模型,拟合出使模型计算出库流量过程与水电站实际出库流量过程偏差最小的代表水头;然后,在实际调度中,以日平均入库流量和日平均出力作为该代表水头特征向量,根据预测入库流量和日计划电量即可选取最优代表水头。计算实例表明,相比于传统固定水头,该方法能够更好地反应水电站实际的出库过程,有利于提高电网制定调度计划中梯级水电站上下游水量匹配精度。展开更多
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.
基金Project supported by the National Creative Research Groups Science Foundation of China (No. 60421002)the National "Tenth Five-Year" Science and Technology Research Program of China (No.2004BA204B08)
文摘A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.
文摘Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interactions from service providers.Intruders can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered VMs.The existing system has issues with execution time and false-positive rates.Hence,the overall system performance is degraded considerably.The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position.Allocation of SECURITY Resources accepts a safety game in a simple format as input andfinds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear Programming(MILP)framework is used in the algorithm.The VM challenge is reduced by afirewall-based controlling mechanism combining behavior-based detection and signature-based virus detection.The pro-posed method is focused on detecting malware attacks effectively and providing better security for the VMs.Finally,the experimental results indicate that the pro-posed security method is efficient.It consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.
基金This work was supported in part by the National High Technology Research and Development Program(2012AA 050208)in part by the National Natural Science Foundation of China(51407069)in part by the Fundamental Research Funds for the Central Universities(2014QN02).
文摘In this paper,a mixed integer linear programming(MILP)formulation for robust state estimation(RSE)is proposed.By using the exactly linearized measurement equations instead of the original nonlinear ones,the existingmixed integer nonlinear programming formulation for RSE is converted to a MILP problem.The proposed approach not only guarantees to find the global optimum,but also does not have convergence problems.Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency.
文摘在优化左转错位交叉口相位相序的基础上,提出了3套左转错位交叉口信号配时策略的混合整数规划(mixed integer linear programming,MILP)模型。MILP-1模型以交叉口通行能力最大为目标函数,以排队长度约束、最小绿灯时间约束、最大等待时间约束共同构成约束集合。MILP-2模型引入进口道重要程度的概念,修正目标函数,调整优化方向,以期获得最真实的配时方案。通过引入若干等式约束,可以得到简化模型MILP-3,并可运用分枝定界算法予以求解。广州市白云区金钟横云龙路口是一个典型的左转错位交叉口,分别运用MILP-1模型、MILP-2模型及MILP-3模型进行配时设计,求解结果表明:3个模型均能得到合理的优化结果,且以MILP-2优化效果最佳,MILP-3优化速度最快。
文摘针对采用设计水头的水电站混合整数线性规划(mixed integer linear programming,MILP)调度模型计算的出库流量与实际出库流量偏差较大的问题,提出了基于运行数据的水电站MILP模型最优代表水头选取方法。首先,基于运行数据采用MILP模型,拟合出使模型计算出库流量过程与水电站实际出库流量过程偏差最小的代表水头;然后,在实际调度中,以日平均入库流量和日平均出力作为该代表水头特征向量,根据预测入库流量和日计划电量即可选取最优代表水头。计算实例表明,相比于传统固定水头,该方法能够更好地反应水电站实际的出库过程,有利于提高电网制定调度计划中梯级水电站上下游水量匹配精度。
