An improved differential evolution algorithm-based optimal series compensation voltage control strategy for an active 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.

In order to meet the high permeability and the access of large scale distributed generation, at present and in the future, active distribution network becomes the trend of smart grid research. This paper introduces the influence of distribution network voltage distribution and stability of distributed energy access based on active distribution network; The reactive power and voltage optimization control method of active power distribution network is summarized from the aspects of optimal voltage regulation measure, voltage regulation measure of power network equipment, reactive power optimal dispatch of power system, and so on. Analysis of the current status of the research, and summarized the existing active distribution network with a distributed power pickup distribution network reactive power and voltage control of the existence of some problems and the insufficiency still some problems that must be solved in the study of reactive power and voltage optimization control of active distribution network are pointed out.

The large-scale integration of distributed photovoltaics (PV) can cause reverse power flow due to an imbalance between load and PV generation, altering the voltage profile in traditional distribution networks. The uncertainties in PV output can also cause voltage violations in the distribution network. Conventional methods for assessing static stability in voltage within such systems utilize continuous power flow techniques to calculate the load margin index, which provides a measure of how stable the voltage is in the distribution network. Nevertheless, the frequent load margin calculations in such methods result in significant computational costs, rendering them impractical for networks with distributed generators (DGs). Conventional static voltage stability assessment methods typically use continuation power flow (CPF) to calculate load margins but face significant computational bottlenecks in active distribution networks with distributed generation. For instance, even with improved power flow algorithms, a 33-bus system requires 58 iterations and about 0.3–0.5 seconds per analysis; in large-scale systems with tens of thousands of buses, total evaluation time can exceed 10 minutes. This paper introduces the holomorphic embedding load flow method (HELM), which accommodates different bus types (PI, PQ, PV) in active distribution networks. Building on HELM, a voltage partial sensitivity method is proposed, providing a criterion for evaluating the voltage stability in distribution networks. The sensitivity-based stability criteria using holomorphic embedding functions consider various DG operating conditions without requiring maximum load margin computation. The efficient calculation of these indexes makes the approach ideal for managing voltage in systems that include distribution networks with DGs. Finally, these indexes are used to manage voltage in active distribution networks, and the effectiveness of the method is confirmed through comprehensive numerical examples.

Significant increase of distributed generation (DG) presence and active distribution network (ADN) development cause changes in distribution network’s power quality (PQ), mostly in distorted system voltages and currents. This paper analyses harmonics generation from multiple DG types, such as solar and biogas power plants, and simulates harmonic interactions in ADN in order to identify potential PQ issues. Each harmonic source observed in this paper was modelled according to IEC 61000 with the model parameters provided by power quality measurements in the real system on several DG power plants and passive consumer nodes. A harmonic load flow is performed on a detailed ADN model for different presumed DG expansion scenarios that indicate the complexity of the DG impact on the AND’s PQ. Quantitative and qualitative graphical presentation for cumulative and the most significant ADN nodes is given and the assessment for the potential ADN development based on PQ indices is proposed.

With the decentralization of the electricity market and the plea for a carbon-neutral ecosystem, more and more distributed generation (DG) has been incorporated in the power distribution grid, which is then known as active distribution network (ADN). The addition of DGs causes numerous control and protection confronts to the traditional distribution network. For instance, two-way power flow, small fault current, persistent fluctuation of generation and demand, and uncertainty of renewable energy sources (RESs). These problems are more challenging when the distribution network hosts many converter-coupled DGs. Hence, the traditional protection schemes and relaying methods are inadequate to protect ADNs against short-circuit faults and disturbances. We propose a robust communication-assisted fault protection technique for safely operating ADNs with high penetration of converter-coupled DGs. The proposed technique is realizable by employing digital relays available in the recent market and it aims to protect low-voltage (LV) ADNs. It also includes secondary protection that can be enabled when the communication facility or protection equipment fails to operate. In addition, this study provides the detail configuration of the digital relay that enables the devised protection technique. Several enhancements are derived, as alternative technique for the traditional overcurrent protection approach, to detect small fault current and high-impedance fault (HIF). A number of simulations are performed with the complete model of a real ADN, in Shenyang, China, employing the PSCAD software platform. Various cases, fault types and locations are considered for verifying the efficacy of the devised technique and the enabling digital relay. The obtained simulation findings verify the proposed protection technique is effective and reliable in protecting ADNs against various fault types that can occur at different locations.

A large number of renewable distributed generation (DG) systems connect to the distribution network, affecting the structure of the traditional distribution network and forming an active distribution network (ADN). Although the accelerating grid penetration of DGs brings significant challenges to the distribution network operation, the islanded operation capability of DGs provides a flexible solution to the self‐healing of ADNs from faults. To ensure that ADN can quickly recover and reconfigure in the event of a fault and continue to maintain safe, economical, and reliable operation, this paper proposes a dynamic microgrid formation method for ADNs combined with the dynamic network reconfiguration and intentional islanding operation of DGs. An optimization model is designed to represent the proposed self‐healing method, maximizing the load restoration and minimizing the DG cost, line network loss, and voltage excursion simultaneously. A binary hybrid optimization solver is applied to pursue the optimal self‐healing schedules from the optimization model. The self‐healing method is evaluated on the Institute of Electrical and Electronics Engineers (IEEE) 33‐node system and the IEEE 123‐node system, which indicate its rationality and effectiveness fully verified. By optimizing the on and off states of the normally open switches and the on‐grid and off‐grid operation states of DGs, ADNs not only get healed with minimum load curtailment, but also achieve minimal DG generation cost, network loss, and node voltage deviation. In addition, compared with traditional solvers, the proposed solver has a slightly higher computational time than the corresponding solver.

Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability

With recent development of technology and management in power market and equipment, more and more distributed generation (DG) is embedded in the distribution network. However the approach of connecting DG in most cases is based on a so-called ‘fit and forget’ policy and the capacity of DG is limited rigidly by distribution system operator to avoid the negative effects of high level penetration. New management technologies have been proposed to handle the integration of DGs in the distribution networks. In this review, the micro grid (MG) was treated as the local control method to coordinate DGs within a small area of distribution network. And the active distribution network (AND) was treated as the global control mechanism to actively manage DGs, MGs and other equipment. The operation framework of ADN was firstly introduced. Then based on the static and dynamic models of DGs and MGs, impacts of DGs and MGs on the ADN are surveyed from power quality, stability to the operation. Finally, the conclusion and suggestion is given in this paper.

To investigate the security issues of loop-closing operations in medium–low-voltage distribution networks under the influence of stochastic fluctuations from distributed generators (DGs) and loads, probabilistic power flow is introduced for analyzing loop-closing currents in active distribution networks. A novel method combining Latin Hypercube Sampling (LHS) and the Gram–Charlier (GC) series, termed the LHS-GC method, is proposed to calculate the probability distribution of loop-closing currents. By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. Based on a linearized formulation of loop-closing current equations, the cumulants of loop-closing currents are calculated, ultimately reconstructing the probability distribution function of loop-closing currents in active distribution networks. Subsequently, a security assessment framework for loop-closing operations is established using the probability distribution of loop-closing currents. This framework provides a quantitative evaluation from two dimensions: preliminary loop-closing success rate and the severity of current limit violations, offering data-driven decision support for loop-closing operations. Taking the IEEE 34-node distribution network as an example for feeder loop-closing current assessment, the proposed LHS-GC method achieves results with less than 4% deviation from simulation values in terms of cumulative probability distribution of loop-closing currents and safety assessment metrics. Under a sampling scale of 500 points, the computational time is 0.76 s, demonstrating its efficiency and reliability. These outcomes provide actionable references for decision-making support in loop-closing operations of active distribution networks.

The constraints in the active - reactive power coordinated optimal scheduling of the conventional active distribution network are single - faceted, the scheduling efficiency is low, resulting in an increase in the final network loss ratio. Therefore, a method for designing and analyzing the active - reactive power coordinated optimal scheduling in the active distribution network with consideration of demand response is proposed. In light of the existing scheduling requirements, an analysis of the active - reactive power scheduling requirements is initially conducted, and the adaptive approach is adopted to improve the overall scheduling efficiency and construct the adaptive balance scheduling constraints. Based on this, a demand - response - based active - reactive power coordinated optimal scheduling model for the active distribution network is established, and optimization and iteration are used to achieve optimal scheduling processing. The test results indicate that, in comparison with the contract - coordinated distribution network active - reactive power coordinated optimal scheduling method and the multi - level scale congested distribution network method, the test network loss ratios of the demand - response - based distribution network active - reactive power coordinated optimal scheduling method are kept below 2.5. This demonstrates that the active - reactive power coordination optimization scheduling method for the active distribution network is more practical and reliable, with better practical application effect and high scheduling efficiency, and has practical application value.

In order to improve levels of power loss and local voltage magnitudes of distribution network, the optimization allocation problem of distribution generations (DG) in active distribution network is developed. A multi-objective model consisting of the total construction and operation cost and power loss is built, and the algorithm based on glowworm adaptive step strategy is proposed to obtain some optimize allocation pareto sets of DG in distribution network. Then the best allocation set is selected from the above candidate pareto sets by the interactive fuzzy decision technique. The simulation and analysis of IEEE 33-bus system is carried out. Simulation results show the proposed model and algorithm feasible and effective.

Regulation-based formulas and improved Differential Evolution(DE) algorithm is used to optimize PID parameters. In order to improve the global search ability and the convergence rate of the common DE algorithm, self-adaptive method is introduced to obtain DE parameters. On the other hand, initial population quality of DE algorithm has important influence on convergence of the algorithm. So the regulation-based formulas are used to guide the production of initial population, which is good to improve the convergence rate and realize obtaining of PID parameters completely adaptive without any personal experience. The simulation is developed on steam temperature system of cycle fluidized bed boiler with serious parameter uncertainties and many disturbance and long-time delay. The results show that the improved DE algorithm has higher optimal speed, small amount of calculation and effective optimization of parameters. The proposed method has better control quality and system robustness.

ABSTRACTSoft open point‐based energy storage (SOP‐based ES) can realize the real‐time adjustment of transmission power in space and peak load shaving in time, further promoting the integration of distributed generations (DGs) and decreasing the allocation cost. This article proposed an optimal planning model for coordinated allocation of SOP‐based ES and conventional independent ES systems in PV penetrated Active Distribution Networks (ADN). First, the planning models of SOP‐based ES, battery of ES systems and its lifetime are established. Second, the proposed coordinated allocation model aims to minimize the total planning cost, including power exchange cost, investment cost, operation cost, battery degradation cost and loss cost. In order to solve the uncertainty of PV output and load demand, the stochastic optimization model is established with scenarios reduced by the K‐means clustering technique. Third, the linearization model of the battery degradation cost is derived to transform the optimization model into a mixed integer linear programming (MILP) model. Finally, the presented model is implemented on an IEEE 33‐node distribution system to confirm its effectiveness. The case study results show that the coordinated allocation of SOP and converter‐based ES can effectively reduce the allocation cost of ES and promote the integration of DGs.

Distribution networks typically have unbalanced loads; however, most works on Active Distribution Networks (ADNs) use single-phase representations. This paper proposes a linear alternate current (AC) three-phase optimal power flow (OPF) for a day-ahead operation planning of ADNs and microgrids. The proposed AC linear three-phase optimal power flow model is based on polar coordinate systems and considering some consistent approximations for linearization of power flow equations. The shunts admittances of the network and the mutual impedances between phases of the three-phase lines are considered in the model. In this paper, the proposed linear AC three-phase OPF model is used to define the optimal day-ahead operation planning of active distribution systems and microgrids with three-phase feeders and three-phase distributed generators (DG) and energy storage (ES). Since this model proposes a three-phase representation of the system, it provides more accurate results, making it an effective tool for optimal planning of the ADN operation. The proposed model is illustrated using the IEEE 34-bus test system and results show its effectiveness and excellent performance, presenting an error of less than 4% for the voltage magnitude of the buses and less than 2% for the apparent power flow of the lines, when compared with non-linear models.

Network partition and distributed voltage coordination control strategy of active distribution network system considering photovoltaic uncertainty