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Boming Zhang

Publications and source records attributed to Boming Zhang.

10 recordsLinked to original sources

Fractal structure of Christ-Lee model

This paper numerically investigates the dynamical properties of kink and antikink collisions in the Christ_Lee model in the regime of epsilon approaching the phi4 theory. With given epsilon and the initial velocity Vin, we exhibiting the formation of bion, scattering, and n_bounce states. Additionally, we show the self_similar fractal structures in the plot of Vout_Vin with given epsilon. Specially, we find the fractal structure in the plot of Vout versus epsilon, which is not reported previously. We computes the Box_counting dimension for these fractal structures. We find that the Box_dimension is positively correlated with epsilon, and approaches to Hausdorff dimension of the Sierpinski triangle when epsilon is sufficiently large.

cond-mat.stat-mech

Robust Capacity Assessment of Distributed Generation in Unbalanced Distribution Networks Incorporating ANM Techniques

To settle a large-scale integration of renewable distributed generations (DGs), it requires to assess the maximal DG hosting capacity of active distribution networks (ADNs). For fully exploiting the ability of ADNs to accommodate DG, this paper proposes a robust comprehensive DG capacity assessment method considering three-phase power flow modelling and active network management (ANM) techniques. The two-stage adjustable robust optimization is employed to tackle the uncertainties of load demands and DG outputs. With our method, system planners can obtain the maximum penetration level of DGs with their optimal sizing and sitting decisions. Meanwhile, the robust optimal ANM schemes can be generated for each operation time period, including network reconfiguration, on-load-tap-changers regulation, and reactive power compensation. In addition, a three-step optimization algorithm is proposed to enhance the accuracy of DG capacity assessment results. The optimality and robustness of our method are validated via numerical tests on an unbalanced IEEE 33-bus distribution system.

eess.SY

Optimal Residential Demand Response Considering the Operational Constraints of Unbalanced Distribution Networks

As a typical approach of demand response (DR), direct load control (DLC) enables load service entity (LSE) to adjust electricity usage of home-end customers for peak shaving during DLC event. Households are connected in low voltage distribution networks, which is three phase unbalanced. However, existing works have not considered the network constraints and operational constraints of three phase unbalanced distribution systems, thus may ending up with decisions that deviate from reality or even infeasible in real world. This paper proposes residential DLC considering associated constraints of three phase unbalanced distribution networks. Numerical tests on a modified IEEE benchmark system demonstrate the effectiveness of the method.

math.OC

Robust Reactive Power Optimization and Voltage Control Method for Active Distribution Networks via Dual Time-scale Coordination

In distribution networks, there are slow controlling devices and fast controlling devices for Volt-VAR regulation. These slow controlling devices, such as capacitors or voltage regulators, cannot be operated frequently and should be scheduled tens of minutes ahead (Hereafter named as slow control). Since of the uncertainties in predicting the load and distributed generation, the voltage violations cannot be eliminated by fast controlling devices with improper schedule of the slow controlling devices. In this paper we propose dual time-scale coordination for the Volt-VAR control scheme, corresponding to slow and fast control. In the case of slow control, a robust voltage and reactive power optimization model is developed. This guarantees that subsequent fast controls can maintain the system's voltage security if the uncertain parameters vary within predefined limits. This nonconvex optimization problem is relaxed to a mix integer second order conic problem, and the dual form of its sub-problem is also derived. Then a column-and-constraint generation algorithm was used to solve the robust convexified model. A conventional deterministic optimization model can be used to determine the fast control mechanism. Numerical tests were conducted on a real distribution feeder in China, a balanced IEEE 69-bus and unbalanced 123-bus benchmark distribution networks. The simulation results show that solving the deterministic model is not always feasible and voltage violation may occur. The robust model was shown to be effective with respect to all possible scenarios in the uncertainty set, with little compromise in terms of network losses.

eess.SY

Coordinated Multi-area Economic Dispatch via Critical Region Projection

A coordinated economic dispatch method for multi-area power systems is proposed. Choosing boundary phase angles as coupling variables, the proposed method exploits the structure of critical regions in local problems defined by active and inactive constraints. For a fixed boundary state given by the coordinator, local operators compute the coefficients of critical regions containing the boundary state and of the optimal cost functions then communicate them to the coordinator who in turn optimizes the boundary state to minimize the overall cost. By iterating between local operators and the coordinator, the proposed algorithm converges to the global optimal solution in finite steps, and it requires limited information sharing.

math.OC

Performance Analysis of Sparse Recovery Models for Bad Data Detection and State Esti-mation in Electric Power Networks

This paper investigates the sparse recovery models for bad data detection and state estimation in power networks. Two sparse models, the sparse L1-relaxation model (L1-R) and the multi-stage convex relaxation model (Capped-L1), are compared with the weighted least absolute value (WLAV) in the aspects of the bad data processing capacity and the computational efficiency. Numerical tests are conducted on power systems with linear and nonlinear measurements. Based on numerical tests, the paper evaluates the performance of these robust state estimation mod-els. Furthermore, suggestion on how to select parameter of sparse recovery models is also given when they are used in elec-tric power networks.

math.OC

An Exact Linearization Method for OLTC of Transformer in Branch Flow Model

The branch flow based optimal power flow(OPF) problem in radianlly operated distribution networks can be exactly relazed to a second order cone programming (SOCP) model without considering transformers. However, the introdution of nonlinear transformer models will make the OPF model non-convex. This paper presents an exact linearized transformer's OLTC model to keep the OPF model convex via binary expanstion scheme and big-M method. Validity of the proposed method is verified using IEEE 33-bus test system.

eess.SY

Distributed Robust Bilinear State Estimation for Power Systems with Nonlinear Measurements

This paper proposes a fully distributed robust state-estimation (D-RBSE) method that is applicable to multi-area power systems with nonlinear measurements. We extend the recently introduced bilinear formulation of state estimation problems to a robust model. A distributed bilinear state-estimation procedure is developed. In both linear stages, the state estimation problem in each area is solved locally, with minimal data exchange with its neighbors. The intermediate nonlinear transformation can be performed by all areas in parallel without any need of inter-regional communication. This algorithm does not require a central coordinator and can compress bad measurements by introducing a robust state estimation model. Numerical tests on IEEE 14-bus and 118-bus benchmark systems demonstrate the validity of the method.

eess.SY

A Fully Distributed Reactive Power Optimization and Control Method for Active Distribution Networks

This paper proposes a fully distributed reactive power optimization algorithm that can obtain the global optimum of non-convex problems for distribution networks without a central coordinator. Second-order cone (SOC) relaxation is used to achieve exact convexification. A fully distributed algorithm is then formulated corresponding to the given division of areas based on an alternating direction method of multipliers (ADMM) algorithm, which is greatly simplified by exploiting the structure of active distribution networks (ADNs). The problem is solved for each area with very little interchange of boundary information between neighboring areas. The standard ADMM algorithm is extended using a varying penalty parameter to improve convergence. The validity of the method is demonstrated via numerical simulations on an IEEE 33-node distribution network, a PG&E 69-node distribution system, and an extended 137-node system.

math.OC