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Power systems are undergoing fundamental changes with increasing penetration of renewable energies. A reactive power ancillary service market is of significance to incentivize private providers, such as thermal power units and renewable power plants (RPPs), to participate in maintaining voltage security. Because of the local nature of reactive power, one of the recognized issues is that monopolistic participants may have great market power and strategically manipulate their costs. To pursue economic efficiency, this paper proposes an incentive-compatible mechanism based on Vickery-Clarke-Groves (VCG) auctions for the day-ahead reactive power ancillary service market. The obligations of reactive power ancillary service are quantified in the VCG-based market mechanism. Depending on the expected performance of participants compared with the corresponding obligations, payments are obtained for thermal power units, RPPs, and loads. Hence, providers have the incentive to declare their true costs and undertake obligations. Furthermore, a scarcity price is employed to reward the provision of scarce reactive power resources and ensure reliable market clearing. The proposed mechanism is illustrated using the IEEE 24-bus and 118-bus systems. The results verify the effectiveness of the proposed mechanism. Moreover, high rewards or penalties are observed for voltage weak areas, thereby inducing appropriate investments in reactive power capacities. [ABSTRACT FROM AUTHOR]

With the increasing development of AC/DC hybrid power systems, local synchronous generators in receiving-end grids are being replaced by high-voltage direct current (HVDC) power. The risk of short-term voltage instability exists because of the decline in dynamic reactive power resources from generators, the presence of high-proportioned induction motors and the demand for vast reactive power of HVDC under AC faults. In this situation, unit commitment (UC) should take short-term voltage stability into account. Hence, crucial generators can be retained to provide sufficient dynamic reactive power. This paper proposes a UC model incorporating short-term voltage stability constraints (SVSCUC). Furthermore, a decomposition-based solution approach is presented, which involves an alternate iterative solving of UC and differential-algebraic equations (DAEs). Time-domain simulation (TDS) is utilized to quantify the stability with an indicator. Linear stable cuts are formulated through trajectory sensitivity analysis and added into the UC. The UC is decomposed into a master problem based on mixed-integer linear programming (MILP) and subproblems. The SVSCUC is illustrated using benchmark systems and a real system in eastern China. The results show the effectiveness and efficiency of the proposed methods. Violations of short-term voltage stability for credible contingencies are eliminated under the commitment of SVSCUC. [ABSTRACT FROM AUTHOR]

In this paper, we review the emerging challenges and research opportunities for voltage control in smart grids. For transmission grids, the voltage control for accommodating wind and solar power, fault-induced delayed voltage recovery, and measurement-based Thévenin equivalent for voltage stability analysis are reviewed. For distribution grids, the impact of high penetration of distributed energy resources is analyzed, typical control strategies are reviewed, and the challenges for local inverter Volt–Var control is discussed. In addition, the motivation, state-of-the-art, and future directions of the coordination of transmission system operators (TSO) and distribution system operators (DSO) are also thoroughly discussed. [ABSTRACT FROM AUTHOR]

The decentralized unit commitment problem (DUCP) solved by autonomous distributed agents has been studied by many researchers. Several methods based on traditional distributed optimization approaches have been proposed for solving the DUCP. However, these existing methods do not determine the unit commitment (UC) decisions in a distributed manner or cannot theoretically guarantee convergence and optimality. This paper proposes a method for formulating and solving the DUCP using a recently published parallelizable augmented Lagrangian method, referred to as SDM-GS-ALM. SDM-GS-ALM is a parallelizable method for solving large-scale non-convex problems, and under mild conditions, its optimality and convergence have been proven. The DUCP can be modelled as a mixed-integer linear programming problem, and in this case, its global optimal solution can be obtained via SDM-GS-ALM. This paper focuses on the DUCP in integrated heat and electricity systems. The proposed model and solution method are both general and can be applied directly to solve the DUCP in power systems. The optimality and convergence of the proposed method are demonstrated in case studies. In three test systems, the gaps between the optimal objective values of the centralized UC problem and the DUCP are less than 0.001%. [ABSTRACT FROM AUTHOR]

This paper proposes a new distance-based distributionally robust unit commitment (DB-DRUC) model via Kullback–Leibler (KL) divergence, considering volatile wind power generation. The objective function of the DB-DRUC model is to minimize the expected cost under the worst case wind distributions restricted in an ambiguity set. The ambiguity set is a family of distributions within a fixed distance from a nominal distribution. The distance between two distributions is measured by KL divergence. The DB-DRUC model is a “min-max-min” programming model; thus, it is intractable to solve. Applying reformulation methods and stochastic programming technologies, we reformulate this “min-max-min” DB-DRUC model into a one-level model, referred to as the reformulated DB-DRUC (RDB-DRUC) model. Using the generalized Benders decomposition, we then propose a two-level decomposition method and an iterative algorithm to address the RDB-DRUC model. The iterative algorithm for the RDB-DRUC model guarantees global convergence within finite iterations. Case studies are carried out to demonstrate the effectiveness, global optimality, and finite convergence of a proposed solution strategy. [ABSTRACT FROM AUTHOR]

The recent rapid development of distributed generation (DG) necessitates the consideration of transmission–distribution interactions in voltage stability assessment (VSA), and how to perform a transmission–distribution-coupled static VSA (TDVSA) has become a pressing problem. To resolve this urgent issue, this paper first theoretically analyzes the impacts of the voltage-maintaining capacity and low-voltage tripping of DG units on the static voltage stability of an integrated transmission–distribution system and then proposes a distributed TDVSA method that fully considers these impacts when assessing the voltage stability of the integrated system. As the core of the method, a distributed continuation power flow algorithm is designed that includes a distribution-equivalencing-based predictor, a distributed transmission–distribution corrector, and a step-length regulator and requires only a limited amount of data to be exchanged between the transmission system operator (TSO) and the distribution system operator (DSO). Numerical simulations show that even in the case of low DG penetration, a cascading low-voltage tripping event can significantly degrade an integrated system's voltage stability, and only the proposed distributed TDVSA method can produce an accurate assessment. In addition, the number of iterations between the TSO and DSO is shown to be limited, indicating the potential of applying the proposed method to future grids. [ABSTRACT FROM PUBLISHER]

Because distributed generations are extensively integrated into active distribution grids (ADGs), the transmission and distribution coordinated economic dispatch (TDCED) should be investigated to optimally dispatch the generation resources and evaluate the locational marginal prices (LMPs) of the entire system. In this paper, the TDCED problem is formulated, and a new heterogeneous decomposition (HGD) algorithm is proposed. In the HGD algorithm, the transmission LMP at the boundary bus and ADGs' power are exchanged among transmission and ADGs. The optimality and convergency of HGD are proven and numerically verified. In addition, several related issues are further discussed: a) methods to improve the convergency of HGD, b) considerations regarding security issues and voltage constraints in TDCED and corresponding modified HGD algorithms, and c) the practicality of HGD in either separate or transparent interaction modes of transmission and distribution in future grids. Numerical simulations indicate that the generation resources are optimally utilized and that LMPs are reasonably evaluated in TDCED. Congestion in the traditional isolated dispatch mode can also be prevented. Moreover, simulations on several systems from T6D2 to T300D60 verify that the HGD algorithm is an efficient and robust algorithm with limited communication burdens to solve TDCED. [ABSTRACT FROM PUBLISHER]

In this letter, an improved real-time, short-term voltage stability monitoring method is introduced. The impact of voltage magnitude oscillation on the calculation of the Lyapunov exponent is analyzed, and a phase rectification method to eliminate the negative influence of oscillation is proposed. The simulation work was conducted on the provincial power grid at Guangdong in China. Based on our simulation results, the proposed method is expected to improve the effectiveness of short-term voltage stability monitoring. [ABSTRACT FROM PUBLISHER]

Deep learning is considered to be a promising method for total transfer capability (TTC) evaluation due to its high speed and accuracy for nonlinear and complicated problems. However, the operating scenarios of power systems are complex and ever changing. It is difficult to train a single deep model using an overly complex dataset containing operating scenarios with high variability. In addition, making the deep model transparent to validate for operators is another challenge to its application in the power system. To enable the practical application of deep models in TTC evaluation, the operating sample space is clustered into simpler spaces via a two-stage clustering method, and the idea of neighborhood model for the deep TTC evaluation network (DTEN) is proposed. Then, the local post hoc interpretability for the DTEN based on first-order control variable sensitivity is presented. During the interpretability analysis, the quasi-steady state is introduced to assess the coupling effects among different inputs. Case studies on the IEEE 39-bus system and a real-world regional system in China validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the rapid growth of distributed generators, the distribution static voltage stability assessment (D-VSA) becomes as important as the transmission voltage stability assessment (T-VSA). However, the T-VSA and D-VSA normally treat the transmission and distribution separately, neglecting the interactions between transmission and distribution (T-D). This letter studies the impact of coupled T-D on VSA via physical analysis and numerical simulation. We observe that without considering the T-D interaction, D-VSA may exaggerate the actual load margin significantly, and T-VSA may either exaggerate or underestimate the actual load margin, both of which are unreliable. Hence, the coupled T-D interactions must be considered in both T-VSA and D-VSA. [ABSTRACT FROM AUTHOR]

Storage-concerned economic dispatch (ED) problems with complementarity constraints are strongly non-convex and hard to solve. In this letter, an exact relaxation method is proposed to relax the non-convex ED to a convex form under two sufficient conditions, which can be further generalized for other problems of similar structures. A mathematical proof is provided, and the numerical tests verify the effect of this method. [ABSTRACT FROM PUBLISHER]

This letter presents a real-time electric vehicle (EV) smart-charging method (N-RT), that not only considers currently connected EVs, but also uses a prediction of the EVs that are expected to plug in in the future. Numerical tests show that the N-RT method improves valley-filling under various levels of prediction accuracy. [ABSTRACT FROM AUTHOR]

Transmission–distribution coordinated energy management (TDCEM) is recognized as a promising solution to the challenge of high distributed energy resource (DER) penetration, but there is a lack of a distributed computation method that universally and effectively works for the TDCEM. To bridge this gap, this paper presents a generalized master–slave-splitting (G-MSS) method. This method is based on a general-purpose transmission–distribution coordination model called G-TDCM, which enables the G-MSS to be applicable to most of the central functions of the TDCEM. In this G-MSS method, a basic heterogeneous decomposition (HGD) algorithm is first derived from the heterogeneous decomposition of the coupling constraints in the optimality conditions of the G-TDCM. Its optimality and convergence properties are proved. Then, inspired by the sufficient conditions for convergence, a modified HGD algorithm that utilizes the subsystem's response function is developed and demonstrated to converge faster. The distributed G-MSS method is then demonstrated to successfully solve a series of central functions of the TDCEM, e.g., power flow, contingency analysis, voltage stability assessment, economic dispatch, and optimal power flow. The severe issues of over-voltage and erroneous assessment of the system security that are caused by DERs are thus resolved by the G-MSS method with modest computation cost. [ABSTRACT FROM AUTHOR]

In this letter, we propose a data-driven warm start approach, empowered by an artificial neural network, to boost the efficiency of convex relaxations in optimal gas flow. Case studies show that this approach significantly decreases the number of iterations for the convex-concave procedure algorithm, while optimality and feasibility of the solution can still be guaranteed. We also confirm the robustness of this algorithm, and show that this approach can be extended to the optimal dispatch of large-scale electricity-gas coupled integrated energy systems. [ABSTRACT FROM AUTHOR]

Increasing distributed energy resources (DERs) may result in reactive power imbalance in a transmission power system (TPS). An active distribution power system (DPS) having DERs reportedly can work as a reactive power prosumer to help balance the reactive power in the TPS. The reactive power potential (RPP) of a DPS, which is the range between the maximal inductive and capacitive reactive power that the DPS can reliably provide, should be accurately estimated. However, an accurate estimation is difficult because of the network constraints, mixed discrete and continuous variables, and the considerable uncertainty in the DPS. To solve this problem, this paper proposes a robust RPP estimation method based on two-stage robust optimization, where the uncertainty in DERs and the boundary-bus voltage is considered. In this two-stage robust model, the RPP is pre-estimated in the first stage and its robust feasibility for any possible instance of the uncertainty is checked via a tractable problem in the second stage. The column-and-constraint generation algorithm is adopted, which solves this model in finite iterations. Case studies show that this robust method yields a completely reliable RPP, and also that a DPS, even under the uncertainty, is still an effective reactive power prosumer for the TPS. [ABSTRACT FROM AUTHOR]

In future smart grids, with distribution networks having loops more frequently, current transmission contingency analysis (TCA) which usually neglects the distribution power flow variations after a contingency may leave out severe outages. With more distribution management systems deployed on the distribution side, a new transmission CA method based on global power flow (GPF) analysis which integrates both the transmission and distribution power flow is proposed in this paper (named as GTCA) to address the problem. The definition and new features of GTCA are first introduced. Then, the necessity of GTCA is physically illustrated. Difference in the results of GTCA and TCA is mathematically analyzed. A GPF-embedded algorithm of performing GTCA is then provided. The data exchange process and the performance with communication interruptions are discussed. As multiple contingencies are considered in GTCA, several approaches are proposed and discussed to reduce communication burdens and improve the computational efficiency. Plenty of numerical tests are performed in several systems to verify the theoretical analysis. With theoretical analysis and numerical verification, it is suggested that GTCA should be performed instead of TCA to avoid potential false alarms, especially in the condition that DNs are more frequently looped in the future smart grids. [ABSTRACT FROM PUBLISHER]

With increasingly large scale of intermittent and non-dispatchable resources being integrated into power systems, the power flow problem presents greater uncertainty. In order to obtain the upper and lower bounds of power flow solutions including voltage magnitudes, voltage angles and line flows, Cartesian coordinates-based power flow is utilized in this paper. A quadratically constrained quadratic programming (QCQP) model is then established to formulate the interval power flow problem. This non-convex QCQP model is relaxed to linear programming problem by introducing convex and concave enclosures of the original feasible region. To improve the solutions bounds while still encompassing the true interval solution, optimality-based bounds tightening (OBBT) method is employed to find a better outer hull of the feasible region. Numerical results on IEEE 9-bus, 30-bus, 57-bus, and 118-bus test systems validate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

As traditional transmission contingency screening (TCS) methods neglect impacts of distribution grids, the contingency selection result may not be always satisfactory, especially when distribution networks are more frequently looped in a smart grid. Two new contingency screening methods considering impacts of distribution grids are proposed in this letter. The first one is based on global power flow, and the second only utilizes distribution network equivalencing. Numerical tests show both new methods can give more reliable results than TCS. [ABSTRACT FROM AUTHOR]

This letter presents a constraint relaxation optimal power flow (OPF) model to tackle the issues when traditional OPF is infeasible under large variations such as wind generation output. In this model, the original hard constraints are relaxed into soft constraints and the objective function is adjusted for the cost of constraint violations. To guarantee the equivalence to the original OPF model when there are feasible solutions, an exact penalty function method is introduced to justify the selection of penalty factor of constraint violations. By solving an optimization problem, the lower bound of the proper penalty factor is obtained. The results of a 6-bus test system show that the proposed method achieves the same solution when the original OPF has feasible region, and an optimal solution can be obtained with minimum constraint violation when original OPF has no feasible region. Lastly, three large IEEE systems are tested to verify the effectiveness of proposed method. [ABSTRACT FROM PUBLISHER]