Scheduling Of Distribution Networks Research Articles

Optimal Operational Scheduling of Distribution Network with Microgrid via Bi-Level Optimization Model with Energy Band

An optimal operation of new distributed energy resources can significantly advance the performance of power systems, including distribution network (DN). However, increased penetration of renewable energy may negatively affect the system performance under certain conditions. From a system operator perspective, the tie-line control strategy may aid in overcoming various problems regarding increased renewable penetration. We propose a bi-level optimization model incorporating an energy band operation scheme to ensure cooperation between DN and microgrid (MG). The bi-level formulation for the cooperation problem consists of the cost minimization of the DN and profit maximization of the MG. The goal of the upper-level is to minimize the operating costs of the DN by accounting for feedback information, including the operating costs of the MG and energy band. The lower-level aims to maximize the MG profit, simultaneously satisfying the reliability and economic targets imposed in the scheduling requirements by the DN system operator. The bi-level optimization model is solved using an advanced method based on the modified non-dominated sorting genetic algorithm II. Based on simulation results using a typical MG and an actual power system, we demonstrate the applicability, effectiveness, and validity of the proposed bi-level optimization model.

Short-Term Line Maintenance Scheduling of Distribution Network With PV Penetration Considering Uncertainties

In this paper, the methodology for short-term line maintenance scheduling in distribution network with PV penetration is proposed, in which the mixed randomness and fuzziness of solar power generation concerning the available cloud amount forecasting, along with other random or fuzzy factors, such as electricity demand and component historical failure rate, are considered. First, based on the obtained historical data from NASA, the empirical mapping from cloud amount to solar irradiance can be established where the uncertainty is represented by combining randomness and fuzziness. Second, the short-term line maintenance scheduling of distribution network with uncertainties is modeled by using random fuzzy chance-constrained programming aiming at minimizing the pessimistic value in terms of economics and reliability subject to the chance constraints. Finally, a hybrid intelligent algorithm with two-layer optimization is implemented to solve the model. Simulation experiments are carried out on the IEEE 33-Bus and IEEE RBTS 2-Bus systems, and the results demonstrate the effectiveness of the proposed short-term line maintenance scheduling solution for distribution network with the mixed uncertainties of randomness and fuzziness.

A Multi-Stage Optimization Approach for Active Distribution Network Scheduling Considering Coordinated Electrical Vehicle Charging Strategy

The increasing integration of renewable resources and electric vehicles (EVs) presents new requirements for the construction of a current distribution network. As an alternative of conventional distribution network, active distribution network (ADN) has gained more interest for its flexibility and interactivity. However, the unpredictable behavior of ADN participants from source-side, network-side, and demand-side brings more challenges on ADN dispatch. Thus, it is urged to design an ADN optimal scheduling approach that can comprehensively regulate the ADN participants’ behavior. In this paper, an ADN performance assessment system is first established to provide a quantitative analysis on ADN’s scheduling in terms of active controllability, active manageability, and active economy, respectively. Then, according to the ADN assessment system, a multi-stage optimal scheduling approach for ADN considering coordinated EV charging strategy is proposed. It is able to not only smooth the fluctuations caused by the integration of intermittent power sources and EVs but also reconfigure the network topology. Therefore, this approach can be applied to day-ahead dispatches to help operators effectively manage the ADN. Simulation results verify the correctness and effectiveness of the proposed approach.

Strategic decision-making of distribution network operator with multi-microgrids considering demand response program

In this paper, the operation scheduling of future distribution network is discussed under assumption of multi-microgrids. The economic operation scheduling of distribution network operator in the presence of autonomous microgrids is formulated as a game problem. Due to participation of multiple players with different objective functions, the multi follower bi-level programming is intended in the energy management scheme. From the distribution network operator's perspective, the decision-making strategy seeks to minimize the operation costs of distribution network operator. Distribution network operator interconnecting with upstream grid and interaction with microgrids, schedules distributed energy resources and loads in economical matter to operate in optimal operation point. On the other hand, microgrid owners fed electrical loads interacting with the other microgrids and distribution network operator implementing demand response program during the scheduling horizon to acquire maximum profit. Therefore, the key focus of this approach is decision-making of distribution network operator which will be affected, not only by the reactions of microgrids, but also by the exchanging power between the microgrids. The paper discusses the theoretical background, architecture and algorithms of the proposed multi follower bi-level programming, and demonstrates the performance of distribution network operator and microgrids by means of simulation on the radial distribution test system.

Emergency rush repair task scheduling of distribution networks in large-scale blackouts

This paper focuses on the emergency rush-repair task scheduling of distribution networks in power grid emergencies. As there are many characteristics in distribution network emergency rush-repair such as large number of rush repair points, diverse but with limited repair resources and urgent repair time, this paper takes constraint conditions, such as a variety of execution modes and repair resources into consideration during the model building process of the emergency rush repair scheduling, and we study emergency repair strategies, such as using the emergency generator vehicle, nearby repair strategy and ordinary repair strategy. In order to obtain the optimal solution and satisfy the constraints of the distribution network repair model, this paper improves the traditional serial schedule generation mechanism to a distribution network repair serial schedule generation mechanism by using improved SA algorithm and hierarchical optimization method to search the optimal solution. Finally, we use the model to an example and analyze it. It is validated that the two schedule generation mechanisms that use nearby repair strategy and ordinary repair strategy are both effective. Both the advantages and disadvantages of two mechanisms, and the feasibility and rationality of the model are analyzed in this paper.

Stochastic adaptive event‐triggered control and network scheduling protocol co‐design for distributed networked systems

In a distributed ‘networked control system’ (NCS), multiple physical systems or agents are connected to their corresponding controllers through a shared packet-switched communication network. For such distributed NCS, periodic sampled controller design is unsuitable to handle packet-switched closed-loop control systems and a novel stochastic optimal adaptive event-sampled controller scheme is proposed in the application layer for each physical system or agent expressed as an uncertain linear dynamic system. Lyapunov stability analysis will be utilised to derive the event trigger condition. In addition, a network scheduling protocol is also required for such NCS. Traditional network scheduling protocols are unsuitable for such NCS since the behaviour of the physical systems is disregarded during the protocol design. Therefore in this study, a novel distributed network scheduling protocol via cross-layer approach is developed to improve the performance of distributed NCS by minimising an overall system cost function which consists of the information collected from both the event-triggered controller for each physical system in the application layer and the distributed scheduling protocol from the network layer. It will be demonstrated that the proposed co-design approach will not only allocate the network resources efficiently but also it will improve the performance of the overall distributed NCS. Simulation results are included to demonstrate the effectiveness of the proposed cross-layer co-design.

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

With the continuous expansion of power distribution grid, the number of distribution equipments has become larger and larger. In order to make sure that all the equipments can operate reliably, a large amount of maintenance tasks should be conducted. Therefore, maintenance scheduling of distribution network is an important content, which has significant influence on reliability and economy of distribution network operation. This paper proposes a new model for maintenance scheduling which considers load loss, grid active power loss and system risk as objective functions. On this basis, Differential Evolution algorithm is adopted to optimize equipment maintenance time and load transfer path. Finally, the general distribution network of 33 nodes is taken for example which shows the maintenance scheduling model’s effectiveness and validity.