Cost Of Distribution Network Research Articles

Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost

Electric vehicles (EV) replacing the internal combustion engine vehicle may be the solution for the particulate matter (PM) 2.5 pollution issue. However, the uncontrolled charging of EVs would challenge the power system operation. Therefore, it is necessary to implement some level of control over the EV charging procedure, especially in the residential network. In this paper, an optimization of EVs charging scheduling considering energy arbitrage and the distribution network cost of an urban village environment is presented. The optimized strategy focuses on decreasing the loss of EV owners’ energy arbitrage benefit, introduced as the penalty cost. Also, peak demand, power loss, and transformer aging are included in the estimation of the cost function for the distribution network. The optimization problem is solved using the genetic algorithm. As a case study, data from the urban village in Udon Thani, Thailand, are utilized to demonstrate the applicability of the proposed method. Simulation results show a reduction in the loss of energy arbitrage benefit, transformer peak load, power loss and the transformer loss of life. Therefore, the application of the optimized EV charging can prolong transformer lifetime benefiting both the EV owner and the distribution system operator.

Research on Optimization of Port Container Inland Collection and Distribution Network

With the advancement of country’s “the Belt and Road” strategy, each port is actively formulating development strategies to help implement the strategy. The port inland collection and distribution network is an important guarantee for the development of the port, and it is a key component to promote the connection between the port and the inland hinterland. It has an important role in expanding the scale of the port and improving the overall competitiveness of the port. Aiming at the current imbalance of the collection and distribution methods and the imperfect collection and distribution networks in most ports, this paper establishes an optimal model of collection and distribution network costs and quantitatively optimizes the collection and distribution network corridors. The Tianjin Port is selected as a case study object. And the MATLAB software is used to solve the analysis. The conclusion is that Tianjin Port could alleviate the pressure of the collection and distribution network by increasing the density of container trains with the hinterland cities, which verified the validity of the model.

An Adaptive Differential Protection and Fast Auto-Closing System for 10 kV Distribution Networks Based on 4G LTE Wireless Communication

With the development of wireless communication technology and computer technology, more and more smart technologies have been applied in electricity distribution networks. This paper presents an adaptive current differential protection and fast auto-closing system for application in 10 kV distribution networks in China Southern Power Grid. The current differential protection can adaptively change its settings according to the topology change of the primary distribution networks, thus the system effectively reduces the operation and maintenance cost of the power distribution network. In order to restore the power supply for the healthy part of the 10 kV networks quickly after a power system fault is cleared, the protection and control system provides wide area control function for automatic fault isolation and automatic switching. The traditional overcurrent protection and control system have no fault location function, it may take several minutes or even hours to manually locate a fault and then restore the power supply. Compared with the protection and control system of the traditional 10 kV distribution networks, the system developed can locate and isolate faults within 900 ms (assuming that the operating time of the load switch is 700 ms), and can quickly restore power supply in less than one second after a power system fault is cleared.

Designing grid tariffs in the presence of distributed generation

In recent years, an increasing number of electricity consumers have decided to become prosumers. Prosumers can introduce both environmental and social benefits, as well as various utility and regulatory challenges. Utilities and regulators need to either update the current compensation systems and tariff structures or to develop new ones to account for the impact imposed on distribution system operators (DSOs) due to a high penetration rate of distributed generators (DGs), including costs related to connecting DG prosumers to the grid. The goal of this paper is to introduce and examine a novel, multi-part tariff structure that accounts for these costs under the net metering mechanism. Our results show that by applying a multi-part tariff for prosumers, which includes a fixed component that reflects recurring grid-connection costs together with a variable component that reflects the net effect on operating cost of distribution networks, it is possible to alleviate the drawbacks of net metering and optimize prosumption.

Coordinating dynamic network reconfiguration with ANM in active distribution network optimisation considering system structure security evaluation

The growing penetration of renewable energy resources in distribution networks demands for more active management tools. As a new controllable resource, dynamic network reconfiguration (DNR) can improve the flexibility of active distribution network, and in turn decreasing the operation cost of the distribution network and mitigating renewable distributed generation (RDG) curtailment. In this study, an optimisation model coordinating DNR with active network management (ANM) strategies is established, and the system structure security is evaluated. Considering the coordination of scheduling resources such as DNR switches, RDG active/reactive outputs, demand response and static var compensator, the model aims to minimise the comprehensive operation cost of distribution network and improve the consumption rate of RDG while satisfying the distribution network operation constraints. The model transformation method based on the second-order cone relaxation and variable substitution linearisation is proposed, and the original no-convex optimisation model is transformed into the mixed-integer second-order cone programming problem. Finally, the extended IEEE 33-node distribution network is utilised to conduct simulation calculation, and the results demonstrate the validity of the proposed model and its transformation method.

Optimal operational scheduling and reconfiguration coordination in smart grids for extreme weather condition

With the increasing in frequency, intensity, and side effects of grid outages caused by weather based events, the importance of resiliency is also increased. This study presents a novel multi-objective optimization problem for improving the resilience of smart grid against natural disasters in the presence of a considerable amount of line outages occurring due to the weather conditions. The proposed model considers the management of distributed energy resources (DERs), energy storages (ESs), and dynamic topology reconfiguration of the distribution network. The main goal is based on a dynamic resilient operational planning using prediction of weather condition. The objectives in the proposed approach are defined as: to minimise operational cost of distribution network from the system operator's viewpoint, to minimise the penalty costs for energy not supplied and side effects of outages, and to maximise benefits of DER-ES owners by using flexible reconfiguration and dynamic operational planning considering weather conditions. A hybrid optimization algorithm based on genetic algorithm and ɛ-constraint method using fuzzy decision maker is employed to choose the best solution from a provided Pareto optimal set. The outcome of the Pareto solution specifies the best scheduling for DERs, ESs and switching of lines during the scheduling horizon.

Study on a Real Time Scheduling Optimization Model for Multi-source Heterogeneous Distribution Network

Real-time scheduling for distributed power consumption can be heterogeneous distribution network problems, in this paper, an optimization model based on real-time scheduling based on the day before the scheduling model, the power supply capacity of the model based on load forecasting to make full use of distributed power and energy storage equipment, reduces in the peak period of the main power supply rely on, and the imperialist competitive algorithm based on the optimization model was solved. Through the simulation test, the power supply capacity of the real-time scheduling model can effectively utilize the distributed power and energy storage devices to reduce the peak power grid based on the running cost of distribution network is reduced by 2.59%.

Operation of networked multi-carrier microgrid considering demand response

PurposeMicrogrids are inclined to use renewable energy resources within the availability limits. In conventional studies, energy interchange among microgrids was not considered because of one-directional power flows. Hence, this paper aims to study the optimal day-ahead energy scheduling of a centralized networked multi-carrier microgrid (NMCMG). The energy scheduling faces new challenges by inclusion of responsive loads, integration of renewable sources (wind and solar) and interaction of multi-carrier microgrids (MCMGs).Design/methodology/approachThe optimization model is formulated as a mixed integer nonlinear programing and is solved using GAMS software. Numerical simulations are performed on a system with three MCMGs, including combined heat and power, photovoltaic arrays, wind turbines and energy storages to fulfill the required electrical and thermal load demands. In the proposed system, the MCMGs are in grid-connected mode to exchange power when required.FindingsThe proposed model is capable of minimizing the system costs by using a novel demand side management model and integrating the multiple-energy infrastructure, as well as handling the energy management of the network. Furthermore, the novel demand side management model gives more accurate optimal results. The operational performance and total cost of the NMCMG in simultaneous operation of multiple carriers has been effectively improved.Originality/valueIntroduction and modeling of the multiple energy demands within the MCMG. A novel time- and incentive-based demand side management, characterized by shifting techniques, is applied to reshape the load curve, as well as for preventing the excessive use of energy in peak hours. This paper analyzes the need to study how inclusion of multiple energy infrastructure integration and responsive load can impact the future distribution network costs.

Economic dispatch of distribution network with inn for electric vehicles and photovoltaic

Inn for electric vehicles (EVs) and photovoltaic (PV) is a typical integration of EVs locally consuming renewable energy sources (RES), with features of EV charging, energy storage, and RES consumption. In the existing research works, scholars focus on the energy storage system (ESS) as a medium to charge EVs and send back the power to the utility grid and alleviating the information asymmetry between EV owners and grid dispatching agencies with lower costs of distribution network. In this study, a mixed operational mode based on inn for EV and PV with a replaceable EV battery is analysed. The fragmented energy transferring can shift the load more effectively, balance fluctuation of RES, of great significance to optimise the operation of distribution network system. In summary, a comprehensive model of power flow in distribution network with inn for EV and PV is proposed. Based on an improved IEEE 33-node case, the effects of fragmented energy management mode are analysed. Numerical results show that replacing the full-charged battery for EV is more effective for peak load time-shifting and improving consuming of RES power based on the interaction among RES, ESS, and the replaceable EV battery.

Intra-Day Dynamic Network Reconfiguration Based on Probability Analysis Considering the Deployment of Remote Control Switches

With the continuous development of renewable distributed generation (DG) in distribution network, the effective integration of DGs to make system operation safe and economic has become a major concern. Dynamic network reconfiguration, which relies on the remote control switches, is being considered as an efficient method to solve the above problem. An optimal model of intra-day dynamic reconfiguration is proposed to maximize the accommodation revenue of DGs and minimize the operation cost of distribution network considering the deployment constraint of remote control switches. Besides the traditional constraints, the number of remote control switches and their action times are considered as the constraints and checked before calculating the reconfiguration model which can improve the efficiency of reconfiguration. In order to solve the dynamic reconfiguration model, time period reduction strategy and decimal coding strategy are developed to improve the coding efficiency, and tree coding is adopted to test the radiation of distribution network. In addition, a probabilistic analysis method is used to deal with the randomness of DGs. Finally, the feasibility and effectiveness of the proposed model are verified by the IEEE33 node system.

Optimal Allocation of Intermittent Distributed Generation under Active Management

In recent years, distributed generation (DG) has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. At present, most distributed generators follow the principle of “installation is forgetting” after they are connected to a distribution network. This principle limits the popularization and benefit of distributed generation to a great extent. In order to solve these problems, this paper presents a two-tier model for optimal allocation of distributed power sources in active distribution networks (ADN). The objective of upper level planning is to minimize the annual comprehensive cost of distribution networks, and the objective of lower level planning is to minimize the active power cut-off of distributed generation through active management mode. Taking into account the time series characteristics of load and distributed power output, the improved K-means clustering method is used to cluster wind power and the photovoltaic output in different scenarios to get the daily curves in typical scenarios, and a bilevel programming model of distributed generation based on multiscenario analysis is established under active management mode. The upper level programming model is solved by Quantum genetic algorithm (QGA), and the lower level programming model is solved by the primal dual interior point method (PDIPM). The rationality of the model and the effectiveness of the algorithm are verified by simulation and analysis of a 33-bus distribution network.

Distribution Network Operation Risk Assessment Considering Various Influencing Factors

The frequent blackout caused by distribution network faults has sparked research on distribution system operation risks. For the continuous increase of operation risk influencing factors in the process of distribution network development, a risk assessment model considering various influencing factors of distribution network is proposed. In the model, a new method is adopted to calculate outage cost of distribution network, which reflects the comprehensive effect of interruption frequency, interruption duration and quantity of outage on the fault cost. The method can calculate outage cost better, and the distribution network risk assessment result is closer to actual situation. Finally, the Monte Carlo method is adopted to conduct the risk assessment of RBTS Bus - 3, and the evaluation results are compared with those of analytical methods to verify the effectiveness of the method.

A tabu search algorithm for distribution network optimization with discrete split deliveries and soft time windows

To save the distribution network costs, the vehicle routing problem with split deliveries by order and soft time windows is studied. In this paper, the flexibility of the distribution system is enhanced via soft time windows, the requirement for non-split deliveries is loosened, and a new form of discrete split deliveries is defined. The new form of split deliveries by order is agreed for splitting. Giving considerations to split deliveries by order, soft time windows and working time constraints, a corresponding multi-objective mathematical model is constructed, and an adaptive tabu search algorithm with dynamic tabu list and multi-neighborhood structure is designed to solve the problem. The effectiveness of the new algorithm is verified by the example testing and comparison.

Modelling and optimization of least-cost water distribution networks with multiple supply sources and users

The proper allocation of water resources is a very important practical problem in the field of water network planning. Optimization models that are expeditious and easy to use for all stakeholders of the sector play an important role for water resource management. The present work resumes and reviews a least-cost optimization model proposed by our group (Maiolo and Pantusa in Water Sci Tech-W Sup. https://doi.org/10.2166/ws.2015.114 , 2016), able to design a water distribution network with multiple supply sources and multiple users. This approach requires of solving an optimization problem based on a nonlinear objective function which is proportional to the cost of the water distribution network. The cost of pre-existing pipelines is considered null. A more realistic scenario, able to consider the maximum flow rate allowed for existing sources-users connections, is considered here. In order to illustrate the usefulness and flexibility of the proposed approach, an application of the model to the real case of the province of Croton, Southern Italy, is presented.

Agent-based tool to reduce the maintenance cost of energy distribution networks

There has been continuous research in the energy distribution sector because of its huge impact on modern societies. Nonetheless, aerial high voltage power lines are still supported by old transmission towers which involve some serious risks. Those risks may be avoided with periodic and expensive reviews. The main objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. More specifically, the work is focused on reducing the number of periodic reviews of transmission towers to avoid step and touch potentials, which are very dangerous for humans. A virtual organization-based multi-agent system is proposed in conjunction with different artificial intelligence methods and algorithms. The developed system is able to propose a sample of transmission towers from a selected set to be reviewed. The system ensures that the whole set will have similar values without needing to review all the transmission towers. As a result of this work, a website application is provided to manage all the review processes and all the transmission towers of Spain. It allows the companies that review the transmission towers to initiate a new review process for a whole line or area, while the system indicates the transmission towers to review. The system is also able to recommend the best place to locate a new transmission tower or the best type of structure to use when a new transmission tower must be used.

Optimization of Energy Loss Cost of Distribution Networks with the Optimal Placement and Sizing of DSTATCOM Using Differential Evolution Algorithm

This paper presents an optimization of energy loss cost (ELC) of distribution networks (DN) with the optimal allocation and sizing of DSTATCOM to maximizing the total net profit (TNP)/cost savings by using the differential evolution algorithm per annum and planning horizon of DSTATCOM installation scheme. In this approach, the optimal reactive power compensation is the main vital role in solving the objective function. The optimal reactive power compensation with the optimal placement and sizing of DSTATCOM and the improvement in voltage profile of the DN are obtained based on certain objectives such as best reduction in network power loss and the total ELC and the maximization of TNP. The modeling on the size of DSTATCOM is used and was incorporated in DN through the forward–backward sweep load flow technique to evaluate the parameters of load flows in DN. Present worth factor is instigated to evaluate the TNP of the DSTATCOM installation scheme. The proposed method is validated on the 30, 33, and 69-bus DN.

Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources

This paper proposes a hierarchical coordination mechanism for coordinating the economic dispatch of transmission system operator (TSO) and distribution system operator (DSO). The challenge of dispatching large-scale distributed energy resources (DERs) is addressed. The coordination problem of dispatching energy and reserve is formulated. Benders decomposition is the underlying mathematical foundation of the proposed hierarchical coordination mechanism. We define the generalized bid function to approximate the dispatch cost of distribution network by a series of affine functions. The generalized bid function is communicated from DSO to TSO. By using convex AC optimal power flow model, the convergence of hierarchical coordination is guaranteed. A grid computing structure in General Algebraic Modeling System (GAMS) to accelerate the computation is proposed. The generalized bid function is simulated for various test cases. We also demonstrate the effect of DERs on the voltage magnitude and phase angle. The numerical results show that the hierarchical coordination using the generalized bid function converges to very close results compared with the results of centralized dispatch. Hierarchical coordination is capable of managing various network congestion scenarios and power loads. The generalized bid function provides a unified format of communication between TSO and DSO.

Cooperation and profit allocation in two-echelon logistics joint distribution network optimization

Collaborative two-echelon logistics joint distribution network can be organized through a negotiation process via logistics service providers or participants existing in the logistics system, which can effectively reduce the crisscross transportation phenomenon and improve the efficiency of the urban freight transportation system. This study establishes a linear optimization model to minimize the total cost of two-echelon logistics joint distribution network. An improved ant colony optimization algorithm integrated with genetic algorithm is presented to serve customer clustering units and resolve the model formulation by assigning logistics facilities. A two-dimensional colony encoding method is adopted to generate the initial ant colonies. Improved ant colony optimization combines the merits of ant colony optimization algorithm and genetic algorithm with both global and local search capabilities. Finally, an improved Shapley value model based on cooperative game theory and a cooperative mechanism strategy are presented to obtain the optimal profit allocation scheme and sequential coalitions respectively in two-echelon logistics joint distribution network. An empirical study in Guiyang City, China, reveals that the improved ant colony optimization algorithm is superior to the other three methods in terms of the total cost. The improved Shapley value model and monotonic path selection strategy are applied to calculate the best sequential coalition selection strategy. The proposed cooperation and profit allocation approaches provide an effective paradigm for logistics companies to share benefit, achieve win–win situations through the horizontal cooperation, and improve the negotiation power for logistics network optimization.

Designing a Reliable Distribution Network with Facility Fortification and Transshipment under Partial and Complete Disruptions

This paper designs a reliability distribution network with limited capacity under partial and complete facility disruptions. To increase the reliability of the distribution network, a new mixed integer linear programing model is developed by considering multiple mitigation strategies including diversification, fortification, and transshipment. The distribution network constitutes of reliable distribution centers are more expensive, always available and not affected by disruption, and unreliable distribution centers. Thus, they might be fortified at any level of reliability. Several numerical examples with sensitivity analyses are conducted to illustrate the usefulness of the proposed model. Results demonstrate that the transshipment strategy is more effective than the other mitigation strategies on distribution network reliability and cost.

The Transmission of the Future: The Impact of Distributed Energy Resources on the Network

Massachusetts Institute of Technology (MIT) study The Future of the Electric Grid, published in December 2011, examined challenges for power systems and concluded with a number of findings and recommendations. study carefully separated recommendations for transmission from those meant for distribution. Transmission analysis focused on the lack of comprehensive planning at interconnected system levels, siting governance shortcomings, new technologies to enhance grid observability and security, and cybersecurity issues. It also stressed the additional flexibility requirements imposed by the growing presence of intermittent wind and solar generation in the generation mix. At the distribution level, in addition to concerns related to privacy and cybersecurity, recommendations focused on the need for a transition to dynamic pricing for end consumers, promotion of innovation in network design and management, data availability and ownership, and tariff reforms to support distribution network cost recovery.