MILP model for reliability assessment of active distribution networks with microgrids

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.

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.

With the development of the economy and the improvement of people’s living standards, energy has become an increasingly indispensable substance. The large-scale development and utilization of fossil energy has caused problems of energy crisis and environmental pollution. In order to solve these two problems, it is necessary to develop and utilize renewable energy sources, and access distributed power sources in the distribution network to form an active distribution network. The active distribution network contains a large number of distributed power sources, energy storage units and reactive power compensation equipment. Although it provides more convenience for voltage and reactive power regulation of the distribution network, the intermittent and volatility of renewable energy sources will also be Its voltage has a big impact. In order to solve the voltage dip and overvoltage problem of active distribution network, a new active distribution network voltage control strategy is proposed by using model prediction control technology. Inaccurate system modeling is reduced by establishing active distribution bus voltages, distributed power supplies, and energy storage device prediction models. With the minimum adjustment cost as the control target, the second-order cone relaxation method is used to optimize the action behavior of each control device. Finally, the IEEE33 node simulation example is built on the matlab simulation platform. The results show that the proposed voltage control strategy has good control effect and robustness.

Active distribution network is an effective solution to realize the optimizing operation of integrating large-scale distributed energy into distribution network. The intermittency of distributed energy makes the traditional PI control dissatisfying the requirement on the active distribution network control, this paper proposed a method based on model predictive control to apply to the coordination control of active distribution network according to the multi-layer coordination control characteristics of the active distribution network. And uses the dynamic matrix control algorithm to simulate the regional autonomous control in active distribution network with Matlab/Simulink, the simulation results show the effectiveness of the model predictive control method.

Detection and isolation of faulty line in an active distribution network using intelligent numerical relay

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.

With increased uncertainties and depressed security margins of distribution networks, the risk of violating load or voltage constraints has increased. The usual risk-prevention method is to set an appropriate optimal schedule of active distribution networks to reserve enough margin without incurring extra operating costs. In this study, an optimal scheduling method for an active distribution network is proposed that allows for a low level of violation risk to minimize operating costs while maintaining good system security. Overload violation risk cost is a financial cost due to the cost of countermeasures needed to avoid overload violation. In this study, the N-0 security regions of overload are set as the constraint that provides the definition and calculation of the bidirectional violation distance of overloading for active distribution networks based on the N-0 security region. The relationship between the violation distance of overloading and the countermeasures against overload violation have been established based on the power flow equations, enabling the calculation of the countermeasures cost. The assessment model for the overload violation risk cost is derived from the cost of countermeasures and probability distributions of nodal power. The point estimation algorithm is introduced to simplify the calculation. The calculation of risk cost is fixed through the conditional value-at-risk. On this basis, a novel optimization scheduling model of active distribution networks that considers risk cost is constructed. Examples of the optimal schedule are designed and the validity of the proposed method is verified.

In this paper, a multi-level control strategy for transmission congestion is proposed based on the active reconfiguration and islanding capability from active distribution network. The multi-level control strategy includes an active reconfiguration scheme pursuing the minimum tie line power between the transmission and distribution network, an active islanding scheme based on the multi-source characteristic of active distribution network and a demand response scheme. Case studies are carried out on a typical IEEE 30-bus system with a three-feeder active distribution network to verify the effectiveness of the proposed multi-level control strategy. Simulation results show that the strategy can contribute to congestion relief of transmission network to some extent, and guarantee the reliability index of the distribution network at the same time, which has a good engineering application prospect.

Background: Due to the influence of illumination resources, the output of photovoltaic power generation exhibits intermittency, randomness, and volatility. The large-scale integration of photovoltaic power into the distribution network can cause fluctuations in bus voltage and line flow and, in severe cases, may lead to system voltage and flow limits being exceeded, increasing the risk of system operation. Methods: In response to this, this study proposes an active distribution network flow optimization method based on energy storage regulation. This method takes the total system operation cost, which includes elements such as the cost of photovoltaic power generation, network loss cost, energy storage regulation cost, and curtailment cost, as the optimization objective. It uses the bus voltage, line flow, and transformer load of the active distribution network as the constraint for accommodating space. Additionally, it considers the charging and discharging regulation capacity and sensitivity index of distributed energy storage. Based on this, a flow optimization model for the active distribution network is established, which is driven by the joint cost and sensitivity of the minimum total adjustment amount and the minimum number of control nodes. The model is solved using the path-tracking method. Results: In this paper, the improved IEEE39-bus system is used as an example for analysis, verifying the correctness and effectiveness of the proposed method. Conclusion: Research shows that this method can fully consider the technical and cost factors of high-proportion distributed photovoltaic grid integration. By optimizing the power flow of the distribution network through coordinated control of distributed energy storage, the proposed method achieves the minimum control adjustment amount while minimizing the number of nodes involved in the adjustment. This ensures the safe, reliable, and economical operation of the system.

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 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.

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.

The access of distributed generation has grant influences on the power distribution system network structure and as a consequence, changes its failure risk. This article presents a power failure risk evaluation model of power distribution network, which including two aspects of device level and feeder level. In the first place, the risk of the power distribution network containing distributed generation will be evaluated from two aspects, device failure possibility and device failure severity. Basing on varies devices' evaluation, through the comprehensive evaluation method to quantify the feeder's risk of failure. When the risk exceeds the threshold value, the system would start its safety precaution. Numerical example results show that, the evaluation method that this article established can realize the risk evaluation and early warning of the power distribution network containing distributed generation, the results have guiding significance for construction retrofitting, and hastens the optimal operation for active power distribution network.

Aiming at the problem that the global optimization results of distribution network can not satisfy the needs of multiple parties, a cooperative development strategy of active distribution network and integrated energy system which based on autonomous state space is proposed. Firstly, the satisfactory solution group of the optimal operation of the distribution network is calculated, and, the interaction power between the distribution network and the integrated energy system is taken as the base point of the autonomous state space, and the shortest radius of the transient security region under the base point range is calculated, thereby determining the autonomous state space of the interaction between the integrated energy system and the active distribution network. Secondly, optimize the integrated energy system in the autonomous state space to determine the output and cost of dispatching equipment in the integrated energy system. The calculation example shows that the collaborative optimization strategy proposed in this paper can give consideration to the interests of active distribution network safety optimization operation and integrated energy system operator cost optimization at the stage of power market reform not yet fully mature.

With the increasing penetration of renewable energy, traditional distribution network operation state assessment methods based on typical operating conditions are no longer applicable. It is urgent to conduct risk assessment research on the dynamic coupling characteristics of voltage, power flow, and distributed generation output after photovoltaic integration into active distribution networks. This paper first analyzes the spatiotemporal variation characteristics of power flow distribution and voltage fluctuations in active distribution networks, and proposes evaluation indicators for power flow and voltage over limit risks. Secondly, feature quantities related to the over limit risk assessment indicators are selected, and a distribution network over limit risk assessment method based on TCN-Transformer neural network architecture is proposed. Finally, based on the improved IEEE 33 node distribution network model, an active distribution network simulation model is built in Matlab(2023b), and a simulation dataset is constructed for multiple operating scenarios. On this basis, a comparative analysis of risk assessment examples for power flow and voltage exceeding limits is conducted, and the results verify the effectiveness and superiority of the proposed method.