Designing Enterprise Resources Planning Application for Integrating Main Activities in a Simulator Model of SCM Network Distribution

Collaborative supply chain is a specific topic in supply chain management and studied by industrial engineering students in supply chain management course. Unfortunately, conventional learning media cannot explain the phenomenon of collaborative supply chain to the students. This study aimed to design a dynamic learning media so that inter-company collaboration and information sharing on the activities of Supply Chain entities can be explained effectively to the students. The problem was solved using 3 (three) steps. First, the distribution network was described using mock up. It consists of miniature trucks, miniature network and miniature of the manufacturer-distributor-retailer embedded with tag and reader of RFID. Second, the Enterprise Resources Planning application was developed for supporting business activities. Third, we developed the integrator consists of monitor’s user interface and practice modules. The result of the research - an SCM-Simulator – will be able to improve learning skills of industrial engineering graduates, especially abilities to identify, formulate, and solve the activities of tactical plan & operational routines of Supply Chain entities. However, distribution module designed is for limited scale laboratory study of simple objects. Keywords: Distribution Network, Enterprise Resource Planning, Industrial Engineering Education, SCM Simulator,and Learning Media

Design principles of mobile railway networks

The basic principles of GSM railway network planning are examined. The method of the frequency channels distribution between cells is described. The development of frequency channel reuse scheme is performed. The procedure of an operational planning is proposed. The principles of even radio coverage are considered for cells with mainly free radio propagation and for urban areas

Technoeconomic distribution network planning using smart grid techniques with evolutionary self-healing network states

The transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limited flexibility of traditional approaches to 11 kV network reinforcement threaten to constrain the uptake of low-carbon technologies. This paper investigates the suitability and cost-effectiveness of smart grid techniques along with traditional reinforcements for the 11 kV electricity distribution network, in order to analyse expected investments up to 2050 under different DECC demand scenarios. The evaluation of asset planning is based on an area of study in Milton Keynes (East Midlands, United Kingdom), being composed of six 11 kV primaries. To undertake this, the analysis used a revolutionary new model tool for electricity distribution network planning, called scenario investment model (SIM). Comprehensive comparisons of short- and long-term evolutionary investment planning strategies are presented. The work helps electricity network operators to visualise and design operational planning investments providing bottom-up decision support

An Optimization Model for Single-Warehouse Multi-Agents Distribution Network Problems under Varying of Transportation Facilities: A Case Study

The transportation cost of goods is the highest day-to-day operational cost associated with the food industry sector. A company may be able to reduce logistics cost and simultaneously improve service level by optimizing of distribution network. In reality, a company faces problems considering capacitated transportation facilities and time constraint of delivery. In this paper, we develop a new model of order fulfillment physical distribution to minimize transportation cost under limited of transportation facilities. The first step is defined problem description. After that, we formulate a integer linear programming model for the single-warehouse, multiple-agents considering varying of transportation facilities in multi-period shipment planning. We analyze problems faced by company when should decide policy of distribution due to varying of transportation facilities in volume, type of vehicle, delivery cost, lead time and ownership of facilities. We assumed transportation costs are modeled with a linear term in the objective function. Then, we solve the model with Microsoft Excel Solver 8.0 Version. Finally, we analyze the results with considering amount of transportation facilities, volume usage and total transportation cost. Keywords: physical distribution, shipment planning, integer linear programming, transportation cost, transportation facilities

Security-constrained day-ahead operational planning for flexible hybrid AC/DC distribution networks

A new active network management framework is presented based on a multi-period optimal power flow problem that is bounded by security constraints at the distribution level for upholding the security of supply. This can be achieved through active engagement with flexible demand and distributed generation to prepare for contingency events in day-ahead operational planning. This framework is coupled with a flexible hybrid AC/DC medium voltage (MV) distribution network topology. It contains an integrated multi-terminal medium voltage DC (MVDC) interface for a seamless interaction and integration of the flexible demand and generation on both AC and DC sides of the hybrid network. The active energy management framework when coupled with a flexible hybrid AC/DC topology provides unprecedented degrees of flexibility as well as security of operation under a variety of conditions. To this end, the 75-bus UK generic distribution network has been modified and converted into a hybrid AC/DC network using the integrated MVDC interface. This framework is then deployed to minimise operational costs to the network operator, considering costs of schemes such as distributed generation curtailment and flexible demand shifting, as well as network losses. Results show a significant improvement in operational costs when the network operates as a flexible hybrid when compared to a pure AC or a more conventional AC/DC hybrid

Operational Planning of Active Distribution Grids under Uncertainty

Modern distribution system operators are facing constantly changing operating conditions caused by the increased penetration of intermittent renewable generators and other distributed energy resources. Under these conditions, the distribution system operators are required to operate their networks with increased uncertainty, while ensuring optimal, cost-effective, and secure operation. This paper proposes a centralized scheme for the operational planning of active distribution networks under uncertainty. A multi-period optimal power flow algorithm is used to compute optimal set-points of the controllable distributed energy resources located in the system and ensure its security. Computational tractability of the algorithm and feasibility of the resulting flows are ensured with the use of an iterative power flow method. The system uncertainty, caused by forecasting errors of renewables, is handled through the incorporation of chance constraints, which limit the probability of insecure operation. The resulting operational planning scheme is tested on a low-voltage distribution network model using real forecasting data for the renewable energy sources. We observe that the proposed method prevents insecure operation through efficient use of system controls

EVALUATION OF LOAD FORECAST MODEL PERFORMANCE IN CROATIAN DSO

During the revitalization of the Remote Control Systems of four Distribution System Operators in Croatia: Elektra Zagreb, Elektroslavonija Osijek, Elektroprimorje Rijeka and Elektrodalmacija Split, the load forecasting subsystems were implemented as an integral part of the DMS system. Accurate electricity load forecasting presents an important challenge in managing supply and demand of electricity since it cannot be stored and has to be consumed immediately. Electricity consumption forecasting has an important role in the scheduling, capacity and operational planning of the distribution power system. Load forecasting of certain parts or the whole distribution network helps to improve distribution network planning, operation and control which also increases the safety level of the entire distribution system. Although many forecasting methods were developed, none can be generalized for all load patterns. Accurate results of electricity load models are essential to make important decisions in planning and controlling so it is important to keep models as accurate as possible regarding input variables such as historical loads and meteorological data. This article gives a description of the implemented load forecasting subsystems using an artificial neural network with a feedforward multilayer perceptron and backpropagation as a learning strategy. The emphasis is on the simple and systematic use of input and output data as well as on forecasting scenarios of specific measured points where hourly forecasted results for a week ahead are presented and compared for Croatian Distribution Centers

Active distribution networks planning with integration of demand response

YesThis paper proposes a probabilistic method for active distribution networks planning with integration of demand response. Uncertainties related to solar irradiance, load demand and future load growth are modelled by probability density functions. The method simultaneously minimizes the total operational cost and total energy losses of the lines from the point of view of distribution network operators with integration of demand response over the planning horizon considering active management schemes including coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated probability density functions and the weighting factor method is used to solve the multi-objective optimization problem. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system

Electricity distribution network for low and medium voltages based on evolutionary approach optimization

The optimum planning of distribution systems consists of the optimum placement and size of new substations, feeders, capacitors, distributed generation and other distribution components in order to satisfy the future power demand with minimum investment and operational costs and an acceptable level of reliability. This thesis deals with the optimization of distribution network planning to find the most affordable network design in terms of total power losses minimization and voltage profiles improvement. The planning and operation of distribution networks are driven by several important factors of network designing. The optimum placement and sizing of the capacitor banks into existing distribution networks is one of the major issues. The optimum placement and sizing of the new substations and distribution transformers with adequate feeder connections with minimum length and maximum functionality are vital for power system as well as optimum placement and sizing of the distributed generators into the existing grid. This thesis commonly investigated the impacts of these factors on voltage profile and total power losses of the networks and aims to reduce the capital cost and operational costs of the distribution networks in both LV and MV levels. Optimum capacitor installation has been utilized in terms of reactive power compensation to achieve power loss reduction, voltage regulation, and system capacity release. The Particle Swarm Optimization (PSO) is utilized to find the best possible capacitor placement and size. The OpenDSS engine is utilized to solve the power flow through MATLAB coding interface. To validate the functionality of the proposed method, the IEEE 13 node and IEEE 123 node test systems are implemented. The result shows that the proposed algorithm is more cost effective and has lower power losses compare to the IEEE standard case. In addition, the voltage profile has been improved. Optimum placement of distribution substations and determination of their sizing and feeder routing is another major issue of distribution network planning. This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). The proposed algorithm has been evaluated on the two types of distribution network models which are the distribution network model with 500 customers that includes LV residential and commercial loads as well as MV distribution network, and 164 nodes in MV level. The test network is generated by fractal based distribution network generation model software tool. The results indicate that proposed algorithm has succeeded in finding a reasonable placement and sizing of distributed generation with adequate feeder path. Another sector of power system that is taken into account in this work is Distributed Generators (DGs). In power system, more especially in distribution networks, DGs are able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. This thesis aims to investigate the best solution for an optimal operation of distribution networks by taking into consideration the DG. The PSO method has been used to solve the DG placement and sizing on the IEEE 34 and 123 nodes test systems, respectively. It has been utilized to demonstrate the effectiveness of the PSO method to improve the voltage profile and minimize the cost by mitigating the total losses of the network

Active distribution networks planning with high penetration of wind power

YesIn this paper, a stochastic method for active distribution networks planning within a distribution market environment considering multi-configuration of wind turbines is proposed. Multi-configuration multi-scenario market-based optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand and different operational status of wind turbines (multiple-wind turbine configurations). Scenario-based approach is used to model the abovementioned uncertainties. The method evaluates the impact of multiple-wind turbine configurations and active network management schemes on the amount of wind power that can be injected into the grid, the distribution locational marginal prices throughout the network and on the social welfare. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. It was shown that multi-wind turbine configurations under active network management schemes, including coordinated voltage control and adaptive power factor control, can increase the amount of wind power that can be injected into the grid; therefore, the distribution locational marginal prices reduce throughout the network significantly