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An iteration-variable-correction (IVC) based method is proposed for solving optimal power flow (OPF) of transmission-distribution-coupled (TDC) systems. First, a TDC system can be divided into a single coordinator and multiple agents. Then, the basic formulation, subproblem construction, and selection of iteration variables are given based on the conventional heterogeneous decomposition algorithm (HGD). Considering the limitations of the conventional HGD, the IVC is proposed. According to the general theory of the IVC, when it is applied to solve TDC OPF, the voltage magnitude of boundary buses and the multipliers corresponding to boundary power injections will be corrected every four iterations with first-order and second-order differential operations on historical results in the previous four iterations. The quadratic convergence of the IVC is proved under several weak assumptions. The numerical experiments demonstrate that the proposed IVC has the same accuracy as the method based on the centralized OPF model. Also, better convergence and efficiency can be achieved under the IVC compared with some conventional decomposition methods, including alternating direction method of multipliers, auxiliary problem principle method, analytical target cascading method, and the HGD. [ABSTRACT FROM AUTHOR]

Considering that the conventional synchronous splitting (MSS) method for power flow calculation of coupled transmission and active distribution (TDC) systems has limitations in efficiency and convergence due to the penetration of distributed generations (DGs) and loop operation, this paper proposes an asynchronous forward-backward-splitting power flow algorithm of TDC systems. In this algorithm, the transmission system operator (TSO) acts as a coordinator and processes forward steps while the distribution system operators (DSOs) act as agents and process backward steps. Two first-in-first-out queues are introduced to realize an asynchronous mechanism, and thus, the TSO does not have to wait for the slowest DSO to complete its power flow calculation and power injection update before the next iteration can proceed. This asynchronous mechanism has a higher efficiency compared with a synchronous one when communication delays exist. In addition, the conventional fixed-point iteration in the MSS method is replaced with the Krasnosel’skii-Mann iteration. The proposed algorithm with appropriate settings will achieve better convergence, especially when active distribution networks are considered, where volt-walt-control-typed and volt-var-control-typed DGs are penetrated. The linear convergence of the proposed algorithm is proved under several assumptions and the parameter tuning issue is discussed with numerical experiments. [ABSTRACT FROM AUTHOR]

The ever-increasing integration of variable wind energy requests for a power system with high flexibility. In this paper, we formulate the real-time economic dispatch problem as a multi-stage robust program to leverage flexible resources, especially energy storage systems, in a broader timescale, and also to avoid the risk of high costs in critical scenarios. The multi-stage robust program is decomposed to the dynamic programming form and the fast robust dual dynamic programming (FRDDP) algorithm is developed to solve it efficiently. To tackle the nonconvexities caused by the inter-temporal constraints of ESSs, an estimation-correction method is developed, and measures of the approximation accuracy are presented. Comprehensive case studies comprising units up to 1371 are carried out to verify the effectiveness of the proposed model. Numerical results show that compared with the existing ones, the proposed multi-stage robust model achieves lower cost under the worst-case scenario and shows better scalability in large-scale systems. [ABSTRACT FROM AUTHOR]

This paper introduces a novel successive-intersection-approximation-based power flow method for integrated transmission and distribution networks (I-T&D). In this method, the entire I-T&D is split into the transmission network part, distribution network part, and boundary part. Then, alternate iterations are processed between a transmission network (TN) and several distribution networks (DNs) by exchanging the voltage and power injection of boundary buses. Particularly, the voltage magnitude of the boundary buses will be modified every two iterations by obtaining an intersection with the results in the previous two iterations. The local quadratic convergence of the method is proved strictly. The numerical experiment demonstrates that the proposed method has the same accuracy as the method based on the global model. Also, better convergence and efficiency can be achieved under the proposed method compared with the master-slave-splitting method in several different circumstances, DNs with loops, DNs with distributed generations, DNs with on-load tap changers, large-scale systems, etc. Besides, the proposed method is applied in the contingency analysis, achieving satisfying convergence and efficiency. [ABSTRACT FROM AUTHOR]

Considering the increasing coupling between transmission and distribution networks, an affine arithmetic-based interval power flow algorithm of integrated transmission and distribution (I-T&D) networks is proposed. First, a novel two-step approximation method for sine and cosine functions is proposed to reduce the number of noise variables in the affine form of the injected power, as the basis of the proposed algorithm. Then, this algorithm is divided into four stages, which are implemented alternatively between a transmission system operator (TSO) and multiple distribution system operators (DSOs) by exchanging parameters at TSO-DSO boundaries. Three-phase unbalanced I-T&D networks and boundary tap changer action are also discussed. In addition, an asynchronous power flow method is proposed to mitigate the influences of communication networks on the proposed interval power flow algorithm. Numerical experiments demonstrate the effectiveness of the proposed two-step approximation method, as well as the conservative property, fairly good approximation effect, high efficiency, and low data exchange amount of the proposed algorithm in various circumstances, including single-phase and three-phase networks, varying degrees of unbalance, various smart inverter controls, etc. [ABSTRACT FROM AUTHOR]

To satisfy the robust and real-time requirements of power flow calculation for large-scale power systems, a globally convergent method is proposed with trust-region techniques, which shows satisfying robustness and convergence. Then, this method is combined with Newton's method to achieve a two-stage algorithm, benefiting from their different advantages. In the first stage, the proposed globally convergent method is used for searching power flow solution. When the values of state variables in a certain iteration are close enough to the real operational point, the algorithm enters the second stage to use Newton's method to achieve the solution. This two-stage algorithm can achieve an accurate solution for solvable cases, and can also achieve a least-square solution, which is an approximate solution for unsolvable cases. Numerical experiments show that the proposed globally convergent method and two-stage algorithm have better robustness and efficiency than the existing methods in previous research. They have universality for well- and ill-conditioned systems as well as the cases under ill-conditioned operational modes, heavy loads and inappropriate initial values. They can also handle different limit violations, such as reactive power limit in PV buses and voltage limit with tap changers action, which could significantly benefit real practice. [ABSTRACT FROM AUTHOR]

This paper proposes a new problem formulation to simplify the mathematical representation for a hybrid ac/dc domestic energy system. Instead of building the formulation from a component level, the new formulation is built at the whole system level such that all power transfers between ac/dc or dc/ac are reflected in the ac power drawn from the main grid. This is achieved by assigning the ac power drawn from the grid as a piecewise function of local dc power, each slope in the function represents the conversion efficiency, making it flexible to consider a wide range of conversion efficiencies for different system components. The new formulation substantially reduces the number of variables/constraints, improves efficiency modelling accuracy and increases the search efficacy. The piecewise functions are directly solved by a mixed integer linear programming (MILP). The performance of the proposed formulation is illustrated by the hybrid ac/dc energy systems at a primary school in the U.K. The results show that the proposed problem formulation and the MILP solution method provide an effective optimal control strategy for a mixed ac/dc domestic energy system in the presence of variable tariffs and differing conversion efficiency, achieved a cost saving of 24% increase in energy bills compared with the traditional approach. [ABSTRACT FROM AUTHOR]

This paper discusses how fast-response distributed battery energy storage could be used to implement post-contingency corrective control actions. Immediately after a contingency, the injections of distributed batteries could be adjusted to alleviate overloads and reduce flows below their short-term emergency rating. This ensures that the post-contingency system remains stable until the operator has redispatched the generation. Implementing this form of corrective control would allow operators to take advantage of the difference between the short- and long-term ratings of the lines and would therefore increase the available transmission capacity. This problem is formulated as a two-stage, enhanced security-constrained OPF problem, in which the first-stage optimizes the pre-contingency generation dispatch, while the second-stage minimizes the corrective actions for each contingency. Case studies based on a six-bus test system and on the RTS 96 demonstrate that the proposed method provides effective corrective actions and can guarantee operational reliability and economy. [ABSTRACT FROM PUBLISHER]

In this paper, the concept of normal measurement rate (NMR) is defined based on the theory of uncertainty in measurement and a robust state estimator named maximum normal measurement rate (MNMR) estimator is proposed. Comparison is made between the MNMR estimator and other robust estimators. The robustness and precision of this estimator is tested with the IEEE 14-bus, 30-bus, and 118-bus systems. Simulation results show that the MNMR estimator is effective in identifying bad data and is also time efficient. [ABSTRACT FROM PUBLISHER]

An analytical method based on generalized polynomial chaos (gPC) is proposed for probabilistic load flow (PLF). The method preserves the nonlinearity of power flow equations whose rectangular formulations are adopted to facilitate the gPC expansion. The feasibility of the method is demonstrated by case studies from a 9-bus system. [ABSTRACT FROM AUTHOR]

Previous work has shown that robust state estimator based on maximum normal measurement rate is accurate and reliable. However, in the existing algorithm, the optimal solutions cannot be obtained due to the approximation of evaluation function. Besides, there are no noise-filtering effects on normal measurements. To deal with these two problems, this letter presents an improved algorithm to get a more accurate solution with higher normal measurement rate. Numerical tests on different systems show the proposed algorithm is efficient. [ABSTRACT FROM PUBLISHER]