Dynamic Expansion Planning Research Articles

Developing an Integration of Smart-Inverter-Based Hosting-Capacity Enhancement in Dynamic Expansion Planning of PV-Penetrated LV Distribution Networks

With the penetration of distributed energy resources (DERs), new network challenges arise that limit the hosting capacity of the network, which consequently makes the current expansion-planning models inadequate. Smart inverters as a promising tool can be utilized to enhance the hosting capacity. Therefore, in response to technical, economic, and environmental challenges, as well as government support for renewable resources, especially domestic solar resources located at the point of consumption, this paper is an endeavor to propose a smart-inverter-based low-voltage (LV) distribution expansion-planning model. The proposed model is capable of dynamic planning, where multiple periods are considered over the planning horizon. In this model, a distribution company (DISCO), as the owner of the network, intends to minimize the planning and operational costs. Optimal loading of transformers is considered, which is utilized to operate the transformers efficiently. Here, to model the problem, a mixed-integer nonlinear programming (MINLP) model is utilized. Using the GAMS software, the decision variables of the problem, such as the site and size of the installation of distribution transformers, and their service areas specified by the LV lines over the planning years, and the reactive power generation/absorption of the smart inverters over the years, seasons, and hours are determined. To tackle the operational challenges such as voltage control in the points of common coupling (PCC) and the limitations in the hosting capacity of the network for the maximized penetration level of PV cells, a smart-inverter model with voltage control capability in PCC points is integrated into the expansion-planning problem. Then, a two-stage procedure is proposed to integrate the reactive power exchange capability of smart inverters in the distribution expansion planning. Based on the simulations of a residential district with PV penetration, results show that by a 14.7% share of PV energy generation, the loss cost of LV feeders is reduced by 28.3%. Also, it is observed that by optimally making use of the reactive power absorption capability of the smart inverters, the hosting capacity of the network is increased by 50%.

Dynamic expansion planning in active distribution grid integrated with seasonally transferred battery swapping station and solar energy

This paper addresses a novel multi-stage dynamic distribution network expansion planning (DNEP) taking into account the electric vehicle (EV) charging station based on the battery swapping model. The battery swapping station (BSS) is transferred seasonally and integrated to different buses in various seasons in order to defer the investment on the new lines. The BSS is as well integrated with rooftop solar panels. The uncertainties of loads and renewable energies are taken into account and handled by stochastic programming. The charging scheduling is optimized for all the batteries inside the BSS. A comparative study is presented for 3 cases including expansion planning without BSS, planning with a fixed location of BSS, and the proposed method (i.e., planning with seasonally transferred BSS). The numerical simulations demonstrate that the proposed model transfers the BSS every six months, where, it is installed on bus 25 in seasons 1 and 2, and on bus 17 in seasons 3 and 4. The congested lines such as lines 2 to 19, 16 to 17, and 6 to 7 are expanded by installing new lines in years 2, 4, and 5, respectively. The BSS sends power to the external grid in on-peak loading times such as hours 12 to 15 and 18 to 21. The proposed model reduces the planning cost by 5% compared to the expansion planning with a fixed location for BSS.

Multi-objective Dynamic Expansion Planning of Active Meshed Distribution Network: Sizing, Siting, and Timing of Hub and Voltage Regulators

Distribution network expansion planning is a technique for managing the system effectively in the face of future challenges. This work investigates the design of a mesh distribution network to allocate substations, DGs, voltage regulators, feeder routing, switch placement, and the integration of multiple energy carrier systems. Dynamic modeling for multi-objective system expansion planning is proposed in this study to identify the optimal plan and operational strategy. The uncertainties related to DGs, electricity, heat load, and their prices are considered in the planning process. A 54-Bus distribution network is applied to evaluate the methodology and discuss the results.

Resiliency-oriented dynamic expansion planning of MG-based distribution networks

High-Impact Low-Probability (HILP) events are the ever-increasing threats against distribution networks (DNs). Boosting DN resilience can be achieved by such measures as redundancy increment by substation allocation, feeder routing from less affected area, design of reconfigurable multi-MicroGrid based (MGs) DN and deployment of different distributed generation sources (DGs). This paper proposes an approach for designing resilient DNs by posing the problem as a dynamic modeling of bi-level resilient DN expansion planning (RDEP) program. In the upper level of the RDEP, distribution company (DisCo) identifies the optimal eco-reliable planning and operation of different assets, while in the lower level, DisCo determines the optimal operation point of the expanded DN against the specified HILP. The uncertainties of renewable energy resources, electric load and its market price and ZIP modeling, well incorporate into the problem. To evaluate the effectiveness of RDEP, computer simulation is done on a large scale 138-bus DN and the results are discussed.

Risk-based dynamic expansion planning of distribution network’s reliability and power quality

ABSTRACT Today’s advanced society with high level of digitalisation suffers from power outages even if it takes just a few minutes. Also, higher voltage drop causes higher power losses and also damages home appliances. In a competitive environment, higher power losses and lower reliability are converted to economic losses. So, Distribution Companies (DisCos) try to provide reliable power supply with higher power quality, of course, in lowest possible costs to their consumers. In this regard, simultaneous switch placement and capacitor allocation can be eco-technically efficient. Due to the limited budget of DisCo, the investments must be applied in different years and in accordance with the level of accepted risk by DisCo. So, this paper is aimed to optimise both the reliability-oriented risk-based – and power quality – objective functions; by finding the timing and sitting of both capacitors and switches, sizing of installed capacitors and determining the kind of installed switches (Recloser and sectionliser), using MOPSO. Also, the uncertainties of load demand and electricity price, voltage-sensitive loads and load priority in power supply are applied to the planning problem. To evaluate the effectiveness of the suggested method, the computer simulation is done on a 33-Bus IEEE distribution network and the results are discussed.

Dynamic generation and transmission expansion planning in the power market-based on a multiobjective framework

Summary Expansion planning is one of the most important issues in the power system studies because of its significant effect on the operation and maintenance in the future. This paper presents a new model for dynamic expansion planning in the power market in which simultaneous expansion of generation and transmission is addressed based on a multiobjective framework. The costs of investment, congestion, and loss of load are considered in the problem formulation as three objectives. The impacts of transmission line losses and different investment scenarios on the planning objectives are also investigated. For us to overcome the difficulties of solving this nonconvex and mixed integer optimization problem, nondominated sorting genetic algorithm-II followed by the fuzzy satisfying method is used to obtain the final optimal solution. The methodology yields a set of solutions so that final plan can be selected according to different planning policies. The proposed method has been applied to the IEEE 24-bus, Iranian northeastern 400-kV power grid and Iranian 400-kV simplified network to justify the performance of the proposed method. Different cases are analyzed, and the obtained results approve the applicability of the proposed approach in real power systems.

Risk based multi‐objective dynamic expansion planning of sub‐transmission network in order to have eco‐reliability, environmental friendly network with higher power quality

This study suggests a method based on stochastic multi-objective modelling for optimally timing, siting and sizing of sub-transmission substationsand medium voltage feeders, distributed generations and capacitors, simultaneously, in order to take more pros of recent developed technologies. Regards to comprehensive impact of uncertainties including: intermittent nature of renewable energy sources, load forecasting and market price errors, some strategies must be devised in order to well incorporate them into the problem. The mentioned problem is modelled by dynamic programming which NSGA-2 is chosen for optimisation purposes and then fuzzy set theory is applied to find the best compromise solution. The proposed scheme aims to minimise substations expansion and installation cost, medium voltage feeders installation and replacement cost, DG units installation and operation cost, capacitors installation cost, cost of purchased energy from the transmission network, active and reactive power losses cost, and connection cost of sub-transmission substations to the upstream network. Besides, risk based modelling of energy not-supplied as an efficient reliability index is incorporated to cost function in order to improve the reliability of the network. Also voltage deviation and voltage stability as the criterion of power quality in distribution networks and emission reduction are treated as independent objective functions.

Multistage Generation and Network Expansion Planning in Distribution Systems Considering Uncertainty and Reliability

This paper describes the incorporation of uncertainty and reliability in the dynamic expansion planning of distribution network assets and distributed generation. Several alternatives for the installation of feeders, transformers, and distributed generation are considered. Thus, the optimal expansion plan identifies the best alternative, location, and installation time for the candidate assets under the uncertainty related to demand and renewable energy sources. To that end, an iterative algorithm is devised to yield a pool of high-quality candidate solutions in terms of total investment and operational costs. Each candidate solution results from a stochastic-programming-based model driven by the minimization of the expected investment and operational costs. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program for which finite convergence to optimality is guaranteed and efficient off-the-shelf software is available. Standard metrics are subsequently applied to each candidate solution to characterize its reliability so that valuable information is provided to the distribution system planner. Numerical results illustrate the effective performance of the proposed approach.

Timing, Siting, and Sizing of Sub-transmission Substations and Distributed Generation Units Along Planning Horizon

Development of distributed generation has provided new opportunities in power system planning. In this article, distributed generation units are considered as an alternative for supplying the load of a sub-transmission system, and a new mathematical framework is presented for expansion planning of an optimal sub-transmission substation and allocation of distributed generation units as well as defining the associated service area. The proposed method focuses on dynamic expansion planning and operation of distributed generation units and substations in a way with lowest cost. Dynamic expansion planning of a sub-transmission system is inherently a mixed-integer non-linear programming problem due to the prevalent electrical and expansion constraints, cost indices in the objective function, and decision variables. This non-linear problem is simplified to a linear problem by the proposed method. The cost function of the developed method consists of investment, construction, and installation costs of sub-transmission substations as well as connection costs of substations to the upper network, new medium-voltage feeders, and distributed generation units. The costs of purchased energy from the upper network and distributed generation units forecasted as nodal prices are added to the objective function. Moreover, prevalent constraints are considered. The proposed approach is applied to a realistic case study.

Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach

This paper presents a dynamic (i.e., time-based) model for distribution system expansion planning (DSEP) considering distributed generation. The proposed model optimizes both investment and operation costs of distribution system. It determines the optimal location and size of distributed generators as well as the reinforcement strategy for primary (i.e., medium voltage) distribution feeders along a specified planning horizon. Besides, the dynamic feature of this model enables it to determine the time of each investment. The investment costs consist of installation cost of distributed generators and reinforcement cost of primary distribution feeders. Similarly, the operation costs comprise the cost of energy losses, operation and maintenance cost of the equipment and cost of power purchased from upstream grid (i.e., sub-transmission or transmission grid). The introduced model is solved using a combination of two efficient heuristic methods of Modified Integer-coded Harmony Search (MIHS) to find the optimal expansion scheme and Enhanced Gravitational Search Algorithm (EGSA) to optimize the operation costs. Furthermore, the suggested solution approach also incorporates an efficient mechanism for coding the candidate solutions in MIHS algorithm. The effectiveness of the proposed method and coding mechanism is extensively demonstrated by testing on two radial distribution systems and comparing the obtained results with the results of several other solution techniques.

Dynamic expansion planning of sub-transmission substations and defining the associated service area

In this paper, a new methodology is presented for dynamic expansion planning of sub-transmission substations (DEPSS). The proposed method deals with the expansion schemes of the facilities which should be installed and/or reinforced in order to make the sub-transmission system capable of supplying the forecasted demand at the lowest cost while all technical constraints are satisfied. DEPSS is inherently a mixed integer nonlinear programming (MINLP) problem due to the prevalent electrical and expansion constraints, cost indices in objective function and decision variables. This nonlinear problem is simplified to a linear problem without any neglecting by the proposed method. The location, capacity and construction time of substations and MV feeders, as well as the optimal service area of substations are determined through a dynamic approach for the planning years. Meanwhile, the optimal operation capacities of substations are determined at each load level in every planning year. The effectiveness of the proposed optimization method is discussed in the first case study which is related to just placement and defining the associated service area. Also, the proposed dynamic method is tested on a realistic case study and compared with the static and multistage approaches.

A new evolutionary solution method for dynamic expansion planning of DG-integrated primary distribution networks

Reconstruction in the power system and appearing of new technologies for generation capacity of electrical energy has led to significant innovation in Distribution Network Expansion Planning (DNEP). Distributed Generation (DG) includes the application of small/medium generation units located in power distribution networks and/or near the load centers. Appropriate utilization of DG can affect the various technical and operational indices of the distribution network such as the feeder loading, energy losses and voltage profile. In addition, application of DG in proper size is an essential tool to achieve the DG maximum potential benefits. In this paper, a time-based (dynamic) model for DNEP is proposed to determine the optimal size, location and installation year of DG in distribution system. Also, in this model, the Optimal Power Flow (OPF) is exerted to determine the optimal generation of DGs for every potential solution in order to minimize the investment and operation costs following the load growth in a specified planning period. Besides, the reinforcement requirements of existing distribution feeders are considered, simultaneously. The proposed optimization problem is solved by the combination of evolutionary methods of a new Binary Enhanced Particle Swarm Optimization (BEPSO) and Modified Differential Evolution (MDE) to find the optimal expansion strategy and solve OPF, respectively. The proposed planning approach is applied to two typical primary distribution networks and compared with several other methods. These comparisons illustrate the effectiveness of the proposed DNEP approach.

A continuous linear optimization model for the exact solution of travelling-salesman-problems in connexion with expansion planning of ring networks

This work describes a subproblem in connexion with a newly developed optimization model for dynamic expansion planning of ring networks serving for electric power distribution in urban supply areas. This subproblem is the exact solution of a Travelling-salesman-problem by a continuous linear optimization model. A short survey over the complete planning model is given too. The model is created by a problem specific, flexibly applicable matrix generator and solved by a powerful commercial standard programming package. The symmetric Travelling-salesman-problems under consideration are characterized as follows: The set of potential ways is determined by the public streets of a city and the nodes to be connected are distributed uniformly over the supply area. The new optimization model allows the exact solution of problems up to about 60 nodes. The practical application is demonstrated by two examples.