An approach to determine the local boundary of small disturbance voltage stability region in a cut-set power space:基于微扰的割集电压稳定域局部边界求解方法

A new approach to determine the local boundary of voltage stability region in a cut-set power space (CVSR) is presented. Power flow tracing is first used to determine the generator-load pair most sensitive to each branch in the interface. The generator-load pairs are then used to realize accurate small disturbances by controlling the branch power flow in increasing and decreasing directions to obtain new equilibrium points around the initial equilibrium point. And, continuous power flow is used starting from such new points to get the corresponding critical points around the initial critical point on the CVSR boundary. Then a hyperplane cross the initial critical point can be calculated by solving a set of linear algebraic equations. Finally, the presented method is validated by some systems, including New England 39-bus system, IEEE 118-bus system, and EPRI-1000 bus system. It can be revealed that the method is computationally more efficient and has less approximation error. It provides a useful approach for power system online voltage stability monitoring and assessment. This work is supported by National Natural Science Foundation of China (No. 50707019), Special Fund of the National Basic Research Program of China (No. 2009CB219701), Foundation for the Author of National Excellent Doctoral Dissertation of PR China (No. 200439), Tianjin Municipal Science and Technology Development Program (No. 09JCZDJC25000), National Major Project of Scientific and Technical Supporting Programs of China During the 11th Five-year Plan Period (No. 2006BAJ03A06). ©2009 State Grid Electric Power Research Institute Press.

Study on Hybrid Heat-Gas-Power Flow Algorithm for Integrated Community Energy System: 区域综合能源系统电/气/热混合潮流算法研究

With the integration of combined heat and power (CHP) units, air-conditioners and gas boilers, power, gas, and heat systems are becoming tightly linked to each other in the integrated community energy system (ICES). Interactions among the three systems are not well captured by traditional methods. To address this issue, a hybrid power-gas-heat flow calculation method was developed in this paper. In the proposed method, an energy hub model was presented to describe interactions among the three systems incorporating various CHP operating modes. In addition, three operating modes were proposed for the ICES including fully decoupled, partially coupled, and fully coupled. Numerical results indicated that the proposed algorithm can be used in the steady-state analysis of the ICES and reflect interactions among various energy systems.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Reduced gradient method combined with augmented Lagrangian and barrier for the optimal power flow problem

A new approach for solving the optimal power flow (OPF) problem is established by combining the reduced gradient method and the augmented Lagrangian method with barriers and exploring specific characteristics of the relations between the variables of the OPF problem. Computer simulations on IEEE 14-bus and IEEE 30-bus test systems illustrate the method. (c) 2007 Elsevier Inc. All rights reserved.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimal reactive power flow via the modified barrier Lagrangian function approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Security constrained optimal active power flow via network model and interior point method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A geometric interpretation for transmission real losses minimization through the optimal power flow and its influence on voltage collapse

This work presents an approach for geometric solution of an optimal power flow (OPF) problem for a two bus system (a slack and a PV busses). Additionally, the geometric relationship between the losses minimization and the increase of the reactive margin and, therefore, the maximum loading point, is shown. The algebraic equations for the calculation of the Lagrange multipliers and for the minimum losses value are obtained. These equations are used to validate the results obtained using an OPF program. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Continuation fast decoupled power flow with secant predictor

The conventional Newton and fast decoupled power flow methods are considered inadequate for obtaining the maximum loading point of power systems due to ill-conditioning problems at and near this critical point. At this point, the Jacobian matrix of the Newton method becomes singular. In addition, it is widely accepted that the P-V and Q-theta decoupling assumptions made for the fast decoupled power flow formulation no longer hold. However, in this paper, it is presented a new fast decoupled power flow that becomes adequate for the computation of the maximum loading point by simply using the reactive power injection of a selected PV bus as a continuation parameter. Besides, fast decoupled methods using V and 0 as parameters and a secant predictor are also presented. These new versions are compared to each other with the purpose of pointing out their features, as well as the influence of reactive power and transformer tap limits. The results obtained for the IEEE systems (14 and 118 buses) show that the characteristics of the conventional method are enhanced and the region of convergence around the singular solution is enlarged.

Alternative parameters for the continuation power flow method

The conventional Newton's method has been considered inadequate to obtain the maximum loading point (MLP) of power systems. It is due to the Jacobian matrix singularity at this point. However, the MLP can be efficiently computed through parameterization techniques of continuation methods. This paper presents and tests new parameterization schemes, namely the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, the reactive power at shunts (capacitor or reactor), the transmission lines power losses (real and reactive), and transmission lines power (real and reactive). Besides their clear physical meaning, which makes easier the development and application of continuation methods for power systems analysis, the main advantage of some of the proposed parameters is that its not necessary to change the parameter in the vicinity of the MLP. Studies on the new parameterization schemes performed on the IEEE 118 buses system show that the ill-conditioning problems at and near the MLP are eliminated. So, the characteristics of the conventional Newton's method are not only preserved but also improved. (C) 2003 Elsevier B.V. B.V. All rights reserved.

HOW TO EFFICIEN TLY INCORPORATE FACTS DEVICES IN OPTIMAL ACTIVE POWER FLOW MODEL

This paper presents for the first time how to easily incorporate facts devices in an optimal active power flow model such that an efficient interior-point method may be applied. The optimal active power flow model is based on a network flow approach instead of the traditional nodal formulation that allows the use of an efficiently predictor-corrector interior point method speed up by sparsity exploitation. The mathematical equivalence between the network flow and the nodal models is addressed, as well as the computational advantages of the former considering the solution by interior point methods. The adequacy of the network flow model for representing facts devices is presented and illustrated on a small 5-bus system. The model was implemented using Matlab and its performance was evaluated with the 3,397-bus and 4,075-branch Brazilian power system which show the robustness and efficiency of the formulation proposed. The numerical results also indicate an efficient tool for optimal active power flow that is suitable for incorporating facts devices.

Power flow for primary distribution networks considering uncertainty in demand and user connection

This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.

Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem

This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.