Distributed power flow loss minimization control for future grid

In this paper, a novel decentralized algorithm is proposed to minimize power flow loss in a large-scale future grid connecting with many real-time-distributed generation systems by which power flows bi-directionally. The DC-power loss at each link is defined as the product of resistance and the square of current that can be considered as a quadratic flow cost. We employ the notion of tie-sets that reduces the complexity of the power flow loss problem by dividing a power network into a set of loops that forms a linear vector space on which the power loss problem can be formulated as a convex optimization problem. As finding a solution in each tie-set enables global optimization, we realize parallel computing within a system of independent tie-sets by integrating autonomous agents. Simulation results demonstrate the minimization of the power loss on every link by iteratively optimized power flows and show the superiority against the traditional centralized optimization scheme

Chance-Constrained ADMM Approach for Decentralized Control of Distributed Energy Resources

Distribution systems are undergoing a dramatic transition from a passive circuit that routinely disseminates electric power among downstream nodes to the system with distributed energy resources. The distributed energy resources come in a variety of technologies and typically include photovoltaic (PV) arrays, thermostatically controlled loads, energy storage units. Often these resources are interfaced with the system via inverters that can adjust active and reactive power injections, thus supporting the operational performance of the system. This paper designs a control policy for such inverters using the local power flow measurements. The control actuates active and reactive power injections of the inverter-based distributed energy resources. This strategy is then incorporated into a chance-constrained, decentralized optimal power flow formulation to maintain voltage levels and power flows within their limits and to mitigate the volatility of (PV) resources

Can Distribution Grids Significantly Contribute to Transmission Grids' Voltage Management?

Power generation in Germany is currently transitioning from a system based on large, central, thermal power plants to one that heavily relies on small, decentral, mostly renewable power generators. This development poses the question how transmission grids' reactive power demand for voltage management, covered by central power plants today, can be supplied in the future. In this work, we estimate the future technical potential of such an approach for the whole of Germany. For a 100% renewable electricity scenario we set the possible reactive power supply in comparison with the reactive power requirements that are needed to realize the simulated future transmission grid power flows. Since an exact calculation of distribution grids' reactive power potential is difficult due to the unavailability of detailed grid models on such scale, we optimistically estimate the potential by assuming a scaled, averaged distribution grid model connected to each of the transmission grid nodes. We find that for all except a few transmission grid nodes, the required reactive power can be fully supplied from the modeled distribution grids. This implies that - even if our estimate is overly optimistic - distributed reactive power provisioning will be a technical solution for many future reactive power challenges

Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

Optimal Ensemble Control of Loads in Distribution Grids with Network Constraints

Flexible loads, e.g. thermostatically controlled loads (TCLs), are technically feasible to participate in demand response (DR) programs. On the other hand, there is a number of challenges that need to be resolved before it can be implemented in practice en masse. First, individual TCLs must be aggregated and operated in sync to scale DR benefits. Second, the uncertainty of TCLs needs to be accounted for. Third, exercising the flexibility of TCLs needs to be coordinated with distribution system operations to avoid unnecessary power losses and compliance with power flow and voltage limits. This paper addresses these challenges. We propose a network-constrained, open-loop, stochastic optimal control formulation. The first part of this formulation represents ensembles of collocated TCLs modelled by an aggregated Markov Process (MP), where each MP state is associated with a given power consumption or production level. The second part extends MPs to a multi-period distribution power flow optimization. In this optimization, the control of TCL ensembles is regulated by transition probability matrices and physically enabled by local active and reactive power controls at TCL locations. The optimization is solved with a Spatio-Temporal Dual Decomposition (ST-D2) algorithm. The performance of the proposed formulation and algorithm is demonstrated on the IEEE 33-bus distribution model.Comment: 7 pages, 6 figures, accepted PSCC 201

Efficient and Risk-Aware Control of Electricity Distribution Grids

This article presents an economic model predictive control (EMPC) algorithm for reducing losses and increasing the resilience of medium-voltage electricity distribution grids characterized by high penetration of renewable energy sources and possibly subject to natural or malicious adverse events. The proposed control system optimizes grid operations through network reconfiguration, control of distributed energy storage systems (ESSs), and on-load tap changers. The core of the EMPC algorithm is a nonconvex optimization problem integrating the ESSs dynamics, the topological and power technical constraints of the grid, and the modeling of the cascading effects of potential adverse events. An equivalent (i.e., having the same optimal solution) proxy of the nonconvex problem is proposed to make the solution more tractable. Simulations performed on a 16-bus test distribution network validate the proposed control strategy

Tradeoffs between AC power quality and DC bus ripple for 3-phase 3-wire inverter-connected devices within microgrids

Visions of future power systems contain high penetrations of inverters which are used to convert power from dc (direct current) to ac (alternating current) or vice versa. The behavior of these devices is dependent upon the choice and implementation of the control algorithms. In particular, there is a tradeoff between dc bus ripple and ac power quality. This study examines the tradeoffs. Four control modes are examined. Mathematical derivations are used to predict the key implications of each control mode. Then, an inverter is studied both in simulation and in hardware at the 10 kVA scale, in different microgrid environments of grid impedance and power quality. It is found that voltage-drive mode provides the best ac power quality, but at the expense of high dc bus ripple. Sinusoidal current generation and dual-sequence controllers provide relatively low dc bus ripple and relatively small effects on power quality. High-bandwidth dc bus ripple minimization mode works well in environments of low grid impedance, but is highly unsuitable within higher impedance microgrid environments and/or at low switching frequencies. The findings also suggest that the certification procedures given by G5/4, P29 and IEEE 1547 are potentially not adequate to cover all applications and scenarios