جستجوی مقالات مرتبط با کلیدواژه "شبکه توزیع فعال" در نشریات گروه "برق"

To evaluate the reliability of active distribution networks, there is a need to model distributed generation sources, mainly renewable ones. The traditional (common) reliability models are not able to take into account the intermittent and random nature of these energy sources, so the need for a new reliability model is necessary to model the production sources of this type of distribution network. In analytical methods, an analytical model of the network is prepared and the problem is solved mathematically; but with the complexity of the network, solving problems becomes very difficult and practically impossible. Therefore, in terms of the complexity of the structure and the variety of operating modes of active distribution networks, a simulation [Monte Carlo] method has been proposed to evaluate their reliability. In this method, all failure modes of network components are randomly classified and specified. On the other hand, by using the proposed model of reliability of DGs, the nature of randomness of these sources has been accurately considered in the simulation process. The simulation results of a sample active distribution network indicate that, with the introduction of microgrids, the reliability indicators of the network and its loads have improved, but the microgrid has had the greatest impact on the load indicators within the microgrid itself.

In this paper, a three-level framework is proposed to determine the optimal scheduling of a Multi-Area Active Distribution Network in the presence of inter-area Soft Open Points (SOPs). In this framework, the uncertainty of renewable generation and forecasted demand is modeled using information gap decision theory in a risk-averse manner. Coordinated scheduling of Controllable Distributed Generators (CDGs) and SOPs, inter-area energy exchanges and energy trading with upstream network considering the uncertainties are the contribution of the presented method. To improve the computational efficiency and to achieve the optimal solution, the scheduling problem is modeled as a second-order conic programming in which the operational and security constraints of the network, CDG limitations, and operational constraints of SOPs are accurately modeled and the problem is solved by executing CPLEX solver in MATLAB environment. A case study on IEEE 33-bus test system showcases the superiority of the proposed model compared to meta-heuristic algorithms such as particle swarm optimization, genetic algorithm, and gravitational search algorithm.

Existing power grids are inefficient, due to the lack of energy management and the lack of storage, so power plants have to produce more to maintain power quality. But by using network savers, the need to build more power plants is reduced and network stability is improved and many of these inefficiencies will be remedied. By launching this market, consumers are encouraged to optimally manage their consumption, sell power to the grid during peak hours, increase network stability, and compensate grid shortages through the nearest storage network operator due to proximity to the storage. Consumers cause the least transmission line losses. In this paper, using the proposed multi-objective fuzzy multi-objective optimization problem for modeling of energy storage systems (ESS) planning in active distribution networks (ADS) considers the impact of ESS optimization strategy. Finally, the modified IEEE standard 33-bus distribution system will be used to evaluate the feasibility and performance of the proposed model by examining the two hybrid algorithms.

In this paper, an optimal scheduling method for an Active Distribution Network (ADN) in the presence of Soft Open Points (SOPs) is presented. In the proposed method, all types of energy transactions, as well as the reactive power exchange between the ADN and the Upstream Network (UN) and the microgrids, are modeled. Scheduling is formulated in a 24-hour time horizon in which all costs and revenues of the ADN in energy transactions, such as the cost of purchasing power from the UN and the revenue from selling power to it along with the power loss cost, and the DG's fuel cost are modeled. In this method, the exact equations of AC load flow, operational constraints of SOPs and DGs, and energy transaction constraints such as power factor limitation, are modeled in a mixed-integer second-order conic programming model. Therefore, it is expected that the obtained results are the optimal global response that meets the scheduling constraints. To evaluate this claim, the operational scheduling of the modified 33-bus IEEE distribution system connected to two microgrids in different scenarios in the presence of high penetration of renewable sources has been investigated. The simulation results show the efficiency of the proposed framework.

This paper presents a reliability assessment algorithm for radial distribution systems such as microgrids and distributed generation units. The effects of these units and system reconfigurations on distribution system reliability can be evaluated by using the proposed algorithm. The impacts of the location and capacity of the distributed energy resources of microgrids and sectionalizing switches on reliability indices are determined. Moreover, proper location is determined by the classification of load points in distribution system. An approach to identifying the out of the service section after a fault event is presented based on the adjacency matrices. The classification of nodes is obtained by identifying different adjacency matrices based on protective devices. At last, the reliability indices of radial distribution system are calculated.

Distributed Energy Resources (DERs) play a key role in the Active Distribution Networks (ADNs) with environmental concerns. Their small scales and the uncertainty pertaining to intermittent generation of renewable resources are the major challenges of participating in the wholesale electricity markets. Based on the concept of Virtual Power Plant (VPP), the aggregation of heterogeneous DERs is possible and the associated risks of their uncertain generation or consumption can be also hedged. Moreover, the coordination of DERs under the umbrella of VPP yields a surplus profit in comparison with the profits made by uncoordinated DERs. In this paper, the mathematical modeling of each member of the VPP and the way of its involvement in the pool are first presented. Then, the coalition forming of a VPP with a Load Aggregator (LA) and their simultaneous participation in both the day-ahead and real-time markets are analyzed. Finally, the profitability of such bigger coalition in ADN is demonstrated via a comprehensive case study.

Regarding the importance of energy storage in distribution networks and different battery technologies, in this paper the optimal battery planning is presented to compare different technologies without renewable energies in the grid. In long-term planning, the decision variables are the battery type, location, capacity and power rating which should be determined optimally. The objective function includes investment cost and O & M cost of battery as well as the grid operation and reliability cost. The technical constraints should be satisfied in project period as well. On the other hand, every technology has its own technical and economic parameters which change in different conditions. As a result, different parameters of the batteries as well as the behavior of the system are taken into account in a comprehensive study. The simulated annealing algorithm is used for optimization. This study show the Zn-Br and Na-S are the most suitable technologies. The results are generalized to different distribution networks using several sensitivity analyses. Finally, it is specified that employing the batteries is economical in those distribution grids which are connected to the global network and have not renewable distributed energy resources.

In this paper, we propose a new method for solving of optimal operation problem of active distribution networks (ADNs) in energy, spinning reserve service, and reactive power service markets using technical virtual power plant (TVPP) concept. TVPP with considering network and its DER constraints provide active operation of distribution network in order to maximize its profit. A security constraints price-based unit commitment (SCPBUC) model, whose security constraints are related to the supply-demand balancing and to the operation of distribution network, is proposed. In addition to optimal bidding in the markets, the proposed model results show that ADN with using VPP concept can operate its network securely. The presented model is a non-convex nonlinear mixed-integer optimization solved by mixed-integer nonlinear programming (MINLP).