Multistage model for distribution expansion planning with distributed generation - Part I: Problem formulation (original) (raw)
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Energy, 2010
This paper presents a dynamic multi-objective model for distribution network expansion, considering the distributed generations as non-wire solutions. The proposed model simultaneously optimizes two objectives namely, total costs and technical constraint satisfaction by finding the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on DG units and/or network reinforcements over the planning period. An efficient heuristic search method is proposed to find non-dominated solutions of the formulated problem and a fuzzy satisfying method is used to choose the final solution. The effectiveness of the proposed model and search method are assessed and demonstrated by various studies on an actual distribution network. d Discount rate τ dl Duration of demand level dl IC dg Investment cost of a DG unit C Investment cost of feeder C tr Investment cost of transformer in substation d Length of feeder in km P dg lim Maximum operating limit of a DG unit ς max Maximum mutation probability ς m Mutation probability in m th cloning process. N b Number of buses in the network N p Number of population N Number of feeders in the network N O Number of objective functions N dl Number of considered demand levels OC dg Operation cost of a DG unit T Planning horizon
Ieee Transactions on Power Delivery, 2008
This paper presents the computer simulation of the Multistage Model for Distribution Expansion Planning with Distributed Generation, as described in Part I. The simulations deal with the planning of an electrical power distribution network in three stages, in five different situations: 1) each of the three stages planned independently; 2) multistage planning; 3) multistage planning with distributed generation; 4) multistage planning with distributed generation and constraints on investment; and 5) multistage planning with distributed generation considering three load levels. The influence of additional constraints is analyzed in terms of the computational effort required to find the optimum solution to the problem.
Optimization model for expansion planning of distribution systems
2004 IEEE/PES Transmission & Distribution Conference & Exposition: Latin America, 2004
~ummnly--This paper presents an optimization model for the problem of expansion planning of distribution electrical energy system: more specifically, for defining the route of feeders. The distribution system is represented by I graph in which the nodes represent demands and sources of energy; the branches represent the possible paths for supply. The model can be used to consider the insertion, removal and/or substitution of power lines of different gauge, with the objective of minimizing network installation and maintenance costs, subject to the limits to capacity of power lines and energy substations, and the maximum and minimum voltage limits specified by the problem. The validity and efficiency of the proposed model are demonstrated by means of two examples of medium-voltage distribution systems. \ Index Terms-power distrlbution; power distribution lines; power distribution planning; power distribution economics.
Dispersed generation impact on distribution network expansion planning
2009
The distribution system is the most extensive part of an electric system and represents the main causes for customer energy interruption. Therefore, the optimal expansion planning of such subsystem including the attractive option of integrating the dispersed generation (DG) can lead to significant economic gains in its installation cost and furthermore minimizing the unserved energy. This paper proposes an integrated model for determining the optimal DG capacity investment and operating cost to serve peak demand as well as the payment reduction toward compensating system losses along the planning period. Thereby, the studied expansion alternatives vary from sizing and sitting of DG generating units or expanding of existing substation and adding new distribution feeders to purchase power from the grid to meet the load demand growth. In the proposed optimization model LINGO software packages is adopted to provide accurate planning decisions. For non-linear constraints both successive linear programming (SLP) and generalized reduced gradient (GRG) algorithms are implemented. Integer models are solved using the branch-and-bound techniques. The different studied alternatives are assessed using present worth analysis to estimate the feasibility of introducing DG in solving the distribution network expansion planning.
International Journal of Electrical Power & Energy Systems, 2015
In this paper, an integrated methodology is proposed for distribution network expansion planning which considers most of the planning alternatives. The planning aims to determine the optimal reinforcement of existing medium voltage lines and high voltage/medium voltage substations, or installation of new ones to meet the load growth in the planning horizon subject to the technical and operational constraints. Also, to take the advantages of new technologies, the renewable and non-renewable distributed generations have been included in the problem as another alternative. The uncertainties related to renewable DGs, load demand, and energy price have been considered in the calculation of cost components. The load duration curve has been utilized for loads such that the results be more precise. The possibility of islanding and load transferring through the reserve feeders have been regarded in the problem to improve the reliability of the network. Also, the required condition for successful and safe operation of island considering all of uncertainty states have been checked out to accurately calculate the reliability. The genetic algorithm is employed to solve this integrated problem. Finally, the proposed method is applied to the 54-bus system and also a real large-scale distribution network, and the results are discussed. The results verify the effectiveness of the presented method.
Overview of Electric Energy Distribution Networks Expansion Planning
IEEE Access
Planning of the electric distribution networks is complex and about upgrading the system to satisfy the demand and constraints with the best economic plan. The planning alternatives include the expansion of substations, installing new distributed generation (DG) facilities, upgrading distribution feeders, etc. In the modern networks, distribution planners must gain the confidence of the reversibility of the investment where renewable energy resources (RERs) inject clean and cost-effective electrical power to respond to the rising demand and satisfy environmental standards. This paper is an exhaustive review on the distribution network expansion planning (DEP) including the modelling of DEP (possible objective functions, problem constraints, different horizon time, and problem variables), optimization model (single/multi-objective), the expansion of distributed energy resources (DERs), problem uncertainties, etc. We discuss the requirements of integrated energy district master planning to avoid conflicts between the goal of independence of district planning on energy, e.g. heat and electricity, and that of dependencies on the local electric utilities regarding instant power balance and stability services. Finally, we describe the primary future R&D trends in the field of distribution network planning. INDEX TERMS Distribution expansion planning, distributed energy resources, multi-objective optimization, decomposition optimization, uncertainty handling.
Integrated and Simultaneous Model of Power Expansion Planning with Distributed Generation
International Review of Electrical Engineering (IREE)
This study proposes a model based on mixed-integer linear programming (MILP) for the integrated expansion planning of generation and transmission systems with the implementation of distributed generation (DG). Most DG planning takes place after generation and transmission planning has been conducted. This model can be used to include DG potential simultaneously with generation and transmission expansion. DG is modelled as a negative load therefore DG is treated as a non-dispatchable unit of power generation. The objective of the model is to minimize overall cost including the investment cost of the generation units, DG units, and transmission lines, and the operating cost of the generation and DG units. The proposed model is staticdeterministic model in the form of MILP. The model was evaluated using the 6-bus Garver's test. To prove the effectiveness of the model, it was evaluated using the IEEE 46 Bus Test. The results show that due to the impact of DG on power system expansion planning ,the overall cost was reduced. The simulation results also show that a different optimal network configuration can be achieved by DG implementation in expansion planning.
Sustainable Energy, Grids and Networks, 2021
Technological progress of distributed generation (DG) units, global approach to reduce the pollution emissions, and creating the opportunity for local investors to participate in the generation expansion investment, are some of the important reasons to involve the DG as an alternative option in the GEP. In this regard, expansion of the DG units compared to the expansion of centralized generation units should be evaluated economically and technically. Therefore, this paper proposes a novel approach for modeling the composite centralized and distributed generation expansion planning problem in the regulated power system. An integrated objective function is presented to involve the most important decision-making factors overall the power system. The purpose is to find the optimal combination of generation expansion created by power plants and DG units to minimize the total costs related to generation expansion, operation, maintenance, fuel, emission, distribution loss and expected energy not supplied, for the decision-making period. The proposed model reveals as a mixed integer nonlinear programming where, genetic algorithm is applied to find the optimal solution which contains the capacity, technology and operation strategy of non-stochastic DG units that will be optimally allocated into some distribution feeders. Results confirm the effectiveness and superiority of the proposed approach.
International Journal of Electrical Power & Energy Systems, 2017
Sub-transmission network, as an intermediate grid between the distribution and transmission systems, receives the electric energy from the transmission network at extra high voltage levels, and delivers it to the distribution network at medium or low voltage levels. The adequate design and operation of sub-transmission system will lead to an efficient design of transmission network from the technical and economic viewpoints on one hand and the adequacy of power delivery to the distribution loads on the other hand. Therefore, the design optimality of these three networks is highly dependent on each other. However, as the simultaneous design of distribution, sub-transmission, and transmission systems is highly complicated, very few researches have tried to model and solve such a difficult problem. In this paper, a new approach has been developed for simultaneous distribution, sub-transmission, and transmission networks expansion planning. The proposed approach has been formulated as an optimization problem where an efficient and improved genetic algorithm (GA) is employed to solve such a complex problem. The utilized GA has been equipped with different modifying operators in order to make sure of its appropriate performance in obtaining useful and optimal solutions for the coordinated planning problem. The conducted approach has been implemented on a real network of Zanjan Regional Electrical Company (ZREC), and the results are compared with those of conventional method, i.e. separate expansion planning of these networks. The simulation results demonstrate the effectiveness of the conducted approach.
A Generalized Multistage Economic Planning Model for Distribution System Containing DG Units
Distributed generation (DG) has gained a lot of attractions in the power sector due to its ability in power loss reduction, increased reliability, low investment cost, and most significantly, to exploit renewable energy resources like wind, photo-voltaic and micro-turbines, which produce power with minimum greenhouse-gas emissions. The installation of DG units into distribution system requires efficient expansion planning technique to minimize the investment and operation cost of the system.. In this paper, a new mixed integer nonlinear model for solving the multistage distribution system network planning problem including DG has been developed. The model is able to deal with different planning scenarios such as buying energy from a nearby electric distribution company through an intertie, upgrading substations, upgrading feeders or investing in DG units. The model takes into account the operational constraints of equipment capacities and voltage limits as well as the dynamic load growth. Finally, the developed mathematical mixed integer model was applied to minimize the planning cost of the studied distribution network including DG units. The implemented mixed integer nonlinear planning model is coded using LINGO V14 optimization software.