An Asynchronous Forward-Backward-Splitting Power Flow Algorithm of Coupled Transmission and Active Distribution Systems

In order to overcome the disadvantages of a traditional gas distribution system of G-M type pulse tube cryocoolers, a novel active gas distribution system with a middle stage reservoir is proposed. Different from the traditional intake and exhaust processes, the refrigeration cycle with the active gas distribution system consists of an intake process from the middle stage reservoir, an intake process from the compressor, an exhaust process to the middle stage reservoir and an exhaust process to the compressor. Theoretical analysis shows that the active distribution system may significantly reduce the power consumption of the compressor due to the reduction of irreversible losses during the intake and exhaust processes. The self-made pulse tube cooler with the active gas distribution system was tested. Experimental results show that the active gas distribution system decreases the power consumption by 27% and entropy generation by 37% when the proportion of opening time of the middle stage reservoir is 30%. The cryocooler reaches a lower refrigeration temperature with minor decrease of cooling power. Besides, the active gas distribution system may increase the life time for valves.

Distributed generation (DG) brought significant changes to the planning and operation of distribution systems (DS). The presence of DG, allied with advanced technologies of measurement and control related to Smart Grid concepts, converts the DS into active networks, subject to bidirectional power flows. As a consequence, aiming to improve the efficiency and reliability of the power supply, active networks begin to operate more often as closed-loop circuits or even as fully meshed topologies.This context points to the need to update traditional computational methods related to DS analysis to incorporate the consequences of technological advances. At the same time, such updated methods must still consider intrinsic invariable characteristics of the distribution networks, like the low-voltage levels and the low X/R ratio of DS lines.This chapter presents a fast-decoupled power flow (FDPF) formulation combined with the complex per unit (cpu) normalization technique that extends the well-known efficiency of FDPF algorithm to active distribution system analysis. The formulation bases of power flow calculation and cpu technique are fully described. Simulation results with DS under distinct operational conditions are presented to demonstrate the effectiveness and versatility of the cpu-based FDPF approach.

Volt/Var control problem of distribution systems has been extensively investigated in literature. Many control models and algorithms have been proposed to achieve better system quality, security, reliability, efficiency, loadability, and cost effectiveness. Early distribution systems are built based on centralized power generation which is named passive distribution system (PDS), where power flow is unidirectional. Nowadays, the topology of the distribution system allows for bidirectional power flow which is named active distribution system (ADS) due to the presence of active resources, such as distributed generations (DGs). The complexity of controlling each system depends on the topology and size of the network, as well as the control devices used. However, in general there are mainly two main control strategies used to control power networks: centralized and decentralized. This paper provides a review for both control strategies in the distribution system based on Volt/Var control techniques. It introduces the most commonly used techniques and algorithms in the literature for passive and active distribution systems. Moreover, it provides the reader with a comprehensive review on the common optimization techniques and the different objective functions used in terms of loss minimization, voltage deviation, and minimum control variable operation.

A competitive decentralized framework for Volt-VAr optimization of transmission and distribution systems with high penetration of distributed energy resources

This paper proposes a self-healing method for active and smart distribution systems. The method uses a distributed algorithm for Fault Location, Isolation, and Service Restoration (FLISR) to enhance the reliability of active distribution systems. The proposed FLISER method is designed to be implemented in the relays of the circuit breakers (CBs) of distribution lines. The same algorithm is executed for all the CBs and each CB only communicates with the adjacent CBs. Therefore, the proposed method takes advantages of the benefits of distributed methods. To provide a fast service restoration, especially when a zone of the distribution grid is disconnected from the upstream transmission system, the method uses a five-step process to provide the required power for loads of the faulted feeder by use of tie lines and the available capacity of distributed generators (DGs). In comparison with the previous works, in the proposed method the minimum number of CBs are opened. The exchanged data between the network elements can be transferred by use of the IEC61850 protocol and in the form of standard GOOSE messages.

Risk-averse decision under worst-case continuous and discrete uncertainties in transmission system with the support of active distribution systems

This paper proposes a multi-objective benefit function for operation of active distribution systems considering demand response program (DRP) and energy storage system (ESS). In the active distribution system, active network management (ANM) is applied so that the distribution system equipment is controlled in real-time status based on the real-time measurements of system parameters (voltages and currents). The multi-objective optimization problem is solved using ε-constraint method, and a fuzzy satisfying approach has been employed to select the best compromise solution. Two different objective functions are considered as follows: benefit maximization of distribution company (DisCo); benefit maximization of distributed generation owner (DGO). To increase the benefits and efficient implementation of distributed generation (DG), DGO has installed battery as energy storage system (ESS) in parallel with DG unit. Consequently, DGO decides for the battery charging/discharging. DisCo has the ability to exchange energy with the upstream network and DGO. Also, DisCo focuses to study the effect of demand response program (DRP) on total benefit function and consequently its influence on the load profile has been discussed. This model is successfully applied to a 33-bus radial distribution network.

With increasing connection of distributed generations (DGs), the power flow in electric distribution network is no longer unidirectional and the network has become active distribution network. Thus, the connection of DGs in electric distribution networks has created a challenge for distribution network operators due to bidirectional power flow. One of the main technical challenges of an active distribution network is to maintain an acceptable voltage level in the system. This has initiated efforts in using various voltage control strategies to regulate the network voltage profile so that the voltage is maintained at its allowable voltage limits. A number of voltage control methods have been applied to solve voltage control problems associated with the connection of DGs in a distribution system. These voltage control strategies may be classified as decentralized or distributed and centralized or coordinated voltage control. From the literature, a number of coordinated voltage control strategies have been implemented to provide better and faster control to the system. This chapter presents an improved coordinated voltage control method in active electric distribution network by coordinating the three voltage control methods, namely, power factor control, on load tap changer control and generation curtailment control. These voltage control methods are coordinated using fuzzy logic by considering the load bus voltages and DG power as inputs and the voltage control actions as the outputs. The fuzzy logic if-then control rules which are generated to build the fuzzy logic control system are based on the simulations results as well as from the previous works. Results obtained using the fuzzy logic based coordinated voltage control has shown that the voltages are able to be kept within its permissible limits.

Stochastic bi-level coordination of active distribution network and renewable-based microgrid considering eco-friendly Compressed Air Energy Storage system and Intelligent Parking Lot

With the increasing number of distributed power sources connected to the active distribution network, it brings greater uncertainty to the operation of the distribution network, which is intertwined with the uncertainty of the load, and brings challenges to the power flow calculation of the distribution network. To solve this problem, a probabilistic power flow calculation algorithm for active distribution network is proposed. The power flow equation of the active distribution system is linearized by Taylor series. In order to improve the efficiency of power flow calculation, the semi-invariant method and Gram-Charlier expansion are used to deal with random variables in the power flow model. The proposed method is verified on the IEEE-33 system, and the results show that the proposed method can significantly reduce the calculation time while ensuring the calculation accuracy.

Active power dispatch and reactive power optimization problems are usually handled separately in active distribution systems, aiming at minimizing the total generation cost or transmission losses. However, the separate optimization cannot achieve a global optimum scheme in distribution system operations. Moreover, the significant relationship between the active power and reactive power may pose great challenges to distribution system operations due to the uncertain nature of load demands and intermittent renewable energy resources. In this paper, using the branch flow model-based relaxed optimal power flow, we formulate a robust coordinated optimization problem for active and reactive powers as a mixed integer second-order cone (SOC) programming problem. Furthermore, in order to address the uncertainties, a two-stage robust optimization model is proposed to coordinate the on load tap changer ratios, reactive power compensators, and charge–discharge power of energy storage system to find a robust optimal solution. Then the column-and-constraint generation algorithm is applied to solve the proposed robust two-stage optimization model. In the relaxed optimal power flow, a stricter cut is added to speed up the computation process of the SOC relaxation in order to guarantee the exactness for representative cases, such as those with high penetration of distributed energy resources. Numerical results based on the 33-bus and 69-bus systems verify the effectiveness of the proposed method.

Fractional frequency transmission system (FFTS) is utilized to transmit large-scale and remote wind power. By adopting a lower frequency (50/3 Hz), FFTS could reduce the electric distance of transmission lines, thus lowering the transmission loss. In order to analyze the interconnected system of FFTS and main grid, the power flow calculation should be conducted. This paper introduces a new method to calculate the power flow of the interconnected system and analyzes the control strategy of reactive power of FFTS. Firstly, a quasi- steady model of the cycloconverter is elaborated. Secondly, the validity of the model is verified through power flow calculation and PSCAD/EMTDC simulation of a simplified system. Finally, an alternate iteration method for power flow calculation of the interconnected system is proposed. Based on the IEEE-30 system, the power factor control of FFTS is discussed considering various integration buses of wind power.

The power flow calculation on an electric network consists of determining the network's state, power flows and electrical losses on the lines, and total losses on the feeder. In this type of problem, the system's modeling is static, and the network is represented by a set of algebraic equations and inequations. Different solution methods were proposed in the literature to perform power flow calculations. However, for distribution networks, these methods must be able to model, with sufficient details, some unique features of these systems, such as their near radial structure, the unbalanced nature of the loads, and distributed generators' insertion. Besides that, modeling the consumption pattern in distribution systems is more complex, and the line parameters are more difficult to be obtained when compared to the transmission system. Hence, applying traditional methods for power flow calculations in distribution networks may lead to divergent solutions. Within this context, this work proposes a new approach for power flow calculations in distribution systems based on Machine Learning. The proposed models use Artificial Neural Networks (ANNs) to predict the active internal losses of a distribution network and the power flows at the borders with the transmission system. Numerical simulations demonstrate the effective performance of the proposed approach, as well as its computational advantages over benchmark software programs since, once trained, ANNs can approximate power flow calculations extremely fast, as only matrix operations are needed. Moreover, the work presents an application of the ANN methodology proposed: predictions of the flows at the borders with the transmission network were used to generate optimal demand contracts for a real distribution system in Brazil.

In this paper, a power flow calculation method for real bipolar voltage source converter (VSC) based high voltage direct current (HVDC) grid is proposed, which is applicable for the system operating in symmetric mode and asymmetrical mode. An optimization method for the asymmetrical mode is proposed to increase the safety and reliability of the system. The simulation results verify that the power flow calculation method possesses high precision and the optimization method works effectively.

Distributed dynamic state-input estimation for power networks of Microgrids and active distribution systems with unknown inputs