Distribution Network Planning Research Articles

Firefly analytical hierarchy algorithm for optimal allocation and sizing of DG in distribution network

<span lang="EN-MY">Distributed generation (DG) can be beneficially allocated in distribution power systems to improve the power system's efficiency. However, specious DG's allocation and sizing may cause more power loss and voltage profile issues for distribution feeders. Therefore, optimization algorithms are vital for future intelligent power distribution network planning. Hence, this study proposes a multi-objective firefly analytical hierarchy algorithm (FAHA) for determining the optimal allocation and sizing of DG. The multi-objective function formulation is improved further by integrating analytical hierarchy process (AHP) with FA to obtain the weight of the coefficient factor (CF). The performance of the proposed approach is verified on the 118-bus radial distribution network with different bus voltage at DG location (VDG) as regulated PV-bus during load flow calculations. The calculated CF and impact of the unregulated voltage at the PV-bus on the objectives function have been analysed. The findings show that the proposed techniques could allocate the DG at the most voltage deviation while minimizing the power loss and improving the radial distribution’s voltage stability index (VSI). The experimental results indicate that the approach is able to improve the overall voltage profile, especially at PQ-buses, minimize the power loss while improving the network's stability index simultaneously.</span>

A feeder link planning method for total supply capability improvement of distribution network

This study proposes a new feeder link planning method for the distribution network, which can improve total supply capability (TSC). Feeder links are the key component of distribution networks. They are of great significance to the TSC of the distribution network. Therefore, it is necessary to reveal the influence rules of feeder links on TSC and then apply the rules in distribution network planning. First, the indices describing the position, scale, and efficiency of feeder links are defined. Second, the influence rules of feeder links on TSC are revealed. 1) When the feeder geometrical distribution is more balanced, the TSC is higher. 2) When the feeder link scale is larger, the TSC is higher. While for both (1) and (2), the TSC will remain unchanged after reaching a certain value. 3) There always exists an optimal construction order of feeder links, which can ensure the TSC is as high as possible in each planning stage. Third, based on the rules, a model and an algorithm of the feeder link planning are proposed. The method can find an optimal construction order of feeder links, which can ensure that the value of TSC is as high as possible in each feeder link planning stage. Finally, the proposed method is verified on an 8-substation-transformer case grid, which has shown that the proposed method has advantages in feeder link efficiency and feeder-distribution balancing, and especially the TSC can be improved in each planning stage than the traditional methods.

Research on comprehensive evaluation method of distribution network based on AHP-entropy weighting method

In the context of smart grid planning and construction, how to tackle the future distribution network, a comprehensive evaluation of smart distribution network planning has become an urgent problem to be solved. To address this issue, this research provides a method for comprehensive evaluation that combines subjective and objective weighing approaches. Firstly, a set of evaluation index system is constructed and quantified based on the characteristics of the future distribution network; after that a comprehensive evaluation model is established and a subjective and objective weighting method combining AHP-entropy weighting method is used to weight the indicators; Finally, the actual data from the distribution network is evaluated and scored. Based on the scoring verification results, the correctness and effectiveness of the method proposed in this paper are verified.

Distribution Network Grid Planning and Automatic Routing Based on Cluster Analysis Algorithm

In order to improve the efficiency of power grid enterprises under the background of new power reform, the author proposes a set of planning ideas and methods for medium-voltage distribution networks based on the optimal division of power supply grids. First, the layout of the main channel in the planning area should be determined to ensure the reservation of land resources. Then, on the basis of clarifying the purpose and principle of grid division, based on the selection of the nearest load backup substation and the load clustering method, the optimal division of the power supply grid should be realized on a global scale. Finally, in each power supply grid, the wiring mode and the primary and secondary construction and renovation standards are selected based on the classification of the supply area, and the main line wiring planning is carried out. For the grid frame in the transition year, in order to avoid repeated reconstruction and facilitate construction, the principle of piece-by-piece construction and reconstruction is proposed. The results show that by the target year, each power supply grid in the planning area will use two substations as power points, the power supply range of the main lines of each grid is limited to this grid, the lines between grids will not be connected, and the line connection rate will reach 100% and all meet the N-1 check. The proposed method follows the basic planning concept of “technically feasible and economically optimal” on the basis of overall planning and transforms the complex global planning of distribution network into local planning within each optimized grid, and it enables different planners to obtain a basically consistent grid optimization scheme, strengthens the scientificity and certainty of planning, and provides a reference for the revision and refinement of relevant guidelines, which has been practically applied.

Research on Data-Driven Distribution Network Planning Method

With the development of the intelligent and interactive power system, the elements of distribution network planning continue to increase. The distribution network connects the transmission system and individuals, directly affects the individual’s power consumption experience, and is a key link in the power system. A reasonable planning scheme can not only improve the power supply capacity and reliability of the distribution network but also fully apply the data of each system in the distribution network to realize the optimal planning of the medium-voltage distribution network driven by data. Firstly, this paper constructs the CIM model and the distribution network topology model and establishes the wiring pattern recognition feature library. The network reconstruction and planning method research was carried out for the target line, and a typical operation scenario of the distribution network was generated. At the same time, based on the time period network loss index, the distribution network reconfiguration optimization model and distribution network expansion planning model are established, and the solution method of the distribution network reconstruction and expansion planning model is expounded. A reconstruction optimization scheme with the best overall network loss performance is in the network operation scenario. The experimental results of the final example show that based on the proposed time period network loss index, the overall operation loss of the distribution network in a period can be calculated more accurately, and the optimized planning scheme is more suitable for the load power consumption characteristics of the region, and the method has certain feasibility.

A Dynamic Evaluation Method for High-Permeability New Energy Distribution Network Planning Considering Multistage Development Trends

With the development of new power systems, high penetration of new energy (HPNE) will become a major feature of power systems in the future. In order to solve the problem that the traditional distribution network planning index makes it difficult to fully consider the impact of new energy access on the distribution network, this paper constructs a distribution network planning evaluation index system considering the characteristics of HPNE, and designs a set of static comprehensive evaluation methods of distribution network planning schemes based on the “over-average penalty” entropy weight method (EWM). At the same time, distribution network planning is a long-term dynamic process, and the static evaluation method makes it difficult to describe the actual situation of the multistage construction process of distribution networks. To this end, a dynamic evaluation method of distribution network planning is proposed, which realizes the comprehensive evaluation of multistage distribution network planning based on dual excitation control lines. Finally, an example of four 10 kV distribution network planning schemes of a power supply bureau are analyzed to prove the effectiveness of the proposed method.

A risk‐averse multiyear framework for resilience improvement planning of active distribution networks against hurricanes

This paper proposes a risk-averse strategy for resilience improvement multiyear planning for distribution networks against hurricanes, considering the uncertainty of load demand and wind power generation. For resilience enhancement, DG placement and line hardening are regarded as planning measures, and DG rescheduling, topology reconfiguration, microgrid forming, and priority-based load curtailment are considered as operational measures. The most conservative scenario is considered for modelling the high-impact/low-probability (HILP) event's impacts. Besides, the information-gap decision theory (IGDT) is utilized to acquire a robust solution protected against the different realization of uncertain variables. As the uncertain loads and wind power generation competitively tend to maximize their robust regions for a particular value of the budget of uncertainty, the ε-constraint method is applied to solve the proposed multi-objective IGDT-based resilience-oriented distribution network planning (RODNP) model. Afterwards, fuzzy decision-making is exploited to find the best solution among Pareto optimal solutions. The proposed risk-averse strategy is implemented on IEEE 33-bus test system, and various case studies are analyzed to demonstrate the proficiency of the approach. The results indicate that the proposed risk-averse strategy can optimally find the hardening schemes to achieve a resilient distribution network in a medium-term planning horizon with a yearly limited monetary budget.

Security constrained optimal placement of renewable energy sources distributed generation for modern grid operations

In modern distribution network planning and operation, optimal distribution generation (DG) placement has become increasingly important. Consequently, extending the optimal DG placement objectives beyond the commonly used deterministic indices to include probabilistic security indices is essential. This paper proposes a decision tree (DT) classification approach for multiple photovoltaic DG (PVDG) units’ placements using specific indices in an unbalanced distribution network. The security indices considered in this paper are the branches’ risk index (RI) and power loss (PL). The optimal branch(es) for PVDG units’ placements are determined through the branches’ RI and PL, and the optimal nodes are determined using the nodal hosting capacity (HC) and zero-point (▪). The proposed technique was tested on the IEEE 33 and 69 node radial distribution networks considering three common PV voltage control modes, namely, constant voltage (CV) mode, reactive power–voltage (QV) mode, and reactive power–power factor (Q–PF) mode. After the optimal placement of the PVDG units under the CV control technique for IEEE 33 and 69 node distribution networks, the worst case of the average probabilistic voltage was improved from 0.798 p.u. and 0.941 p.u. to 0.94 p.u. to 0.975 p.u, respectively. The steady-state power loss was also reduced by 78% and 32.72% for the IEEE 33 and 69 node distribution networks, respectively. The proposed technique was also compared with recent and existing methods in the literature. The proposed technique performs better in terms of power loss reduction and voltage enhancement.

Principal Component Based Sampling for the Continuous Maintenance of Hydraulic Models

The calibration and continuous maintenance of hydraulic models is essential for the optimisation, planning and management of water distribution networks (WDNs). This process requires model fitting against multiple hydraulic states. However, when extended time series of hydraulic data are considered, it is essential to know which hydraulic states to use for model fitting as too many become computationally impractical. This paper presents a novel principal component analysis (PCA) based sampling method, which evaluates the significance of newly observed hydraulic data to be included in the model calibration and maintenance. A framework is presented, which allows for different sized batches of hydraulic data to be utilised. This enables both model calibration on extended time series of data, or model calibration and maintenance with continuous data. An extensive experimental program was conducted to investigate the performance of the proposed framework with different sampling methods compared to other conventional approaches. The results demonstrate that the presented sampling methods can maintain and improve model prediction accuracy both for retrospective and concurrent implementations when used with extended time series data, which capture different hydraulic states. The hydraulic model of the operational WDN used in this study and the acquired hydraulic data are provided as supplementary data to facilitate reproducible research.

Multicriteria method applied to rehabilitation planning in water distribution networks

Multicriteria method applied to rehabilitation planning in water distribution networks

Multicriteria method applied to rehabilitation planning in water distribution networks

Multicriteria method applied to rehabilitation planning in water distribution networks

A Bi-Level Framework for Expansion Planning in Active Power Distribution Networks

This paper presents a new framework for multistage expansion planning in active power distribution networks, in which the distribution system operator (DSO) considers active network management by clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the net present value of the total costs imposed to DSO associated with the investment and maintenance of the network assets as well as the network operation, while the lower level on clearing the local energy market captures the participation of distributed energy resource (DER) owners and demand aggregators to maximize the social welfare. The expansion plans consider the investments in DER owners’ assets as well as variety of network assets in which the profitability of DER owners’ investment is guaranteed. The Karush-Kuhn-Tucker optimality conditions and the strong duality theory are employed through which the model is converted to a mixed integer linear programming optimization problem. The implementation of the suggested model on the 24-bus and 86-bus distribution test systems validates its performance and efficacy in making cost-effective planning decisions.

A novel short-term load forecasting method based on mini-batch stochastic gradient descent regression model

Short-term Load Forecasting (STLF) is the basis of smart distribution network system operation, planning, and dispatching. The traditional linear regression prediction method has the problems of slow prediction speed and low prediction accuracy. In order to solve the problem, an improved regression model based on mini-batch stochastic gradient descent is proposed in this paper. Combined with the big data analysis and processing platform, the collected data is conformed, and the parallel computing model Map-Reduce is used to parallelize mini-batch stochastic gradient descent algorithm for improving the processing ability of mini-batch stochastic gradient descent algorithm in big data load forecasting, and shorten load forecasting time. Meanwhile, in order to clean up the duplicated data and bad data generated by the smart meter and sensor before calculation, an adaptive sorted neighborhood method is proposed to detect the repeatedly recorded data, and the K-means clustering method is used to eliminate the noise data .The experimental results show that the parallelized mini-batch stochastic gradient descent algorithm is much faster than the traditional regression analysis algorithm when the data volume is large. The average absolute percentage error of the load forecasting model for Belgium and a transformer station in Baiyin city of Gansu Province in China is 1.902% and 2.058% respectively, which satisfies the requirements of load forecasting.

Integrated Planning of Cyber-Physical Active Distribution System Considering Multidimensional Uncertainties

The integration of cyber technologies is transforming the power distribution network into a cyber-physical active distribution system (CPADS), and brings more flexibility to its operation. However, various uncertainties from the cyber space and physical space are emerging and coupled with each other, which results in significant challenges for the distribution network planning and operation. Thus, a bilevel integrated planning model accounting for multidimensional uncertainties from both the cyber space and physical space is proposed for the CPADS in this paper. With the goal of minimizing the annual investment and operation costs, the model comprehensively considers the location and selection of active-management elements (e.g., electrical storage systems, capacitor banks, and switches), investment constraints, power flow constraints, and operation constraints for all the active-management elements, etc. Moreover, based on the typical cyber system failure scenario represented by information link failure (ILF), a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N-k</i> uncertainty set considering the failure probability distribution is proposed, while the uncertainties of renewable energy and load demand are characterized by box-like uncertainty sets. Finally, the proposed planning model is recast into a multi-stage robust optimization model which can be divided into a master problem and two-step subproblems (SP-1 and SP-2) to be solved by the column and constraint generation (CCG) algorithm. Case studies and comparative analysis on the PG 69 distribution system are performed to verify the effectiveness of the proposed method.

Hierarchical multi-objective optimal planning model of active distribution network considering distributed generation and demand-side response

Power grid planning is the basis of power system development, the structure of distribution network in China has changed from single source unidirectional network to multi-source multidirectional complex power network, which further increases the uncertainty and complexity of distribution network operation and planning. From the perspective of distributed energy grid connection, this paper constructs a hierarchical optimization model of distribution network planning under active management mode. The relationship among balanced network loss, line investment, power purchase cost, carbon emission cost and policy subsidies are comprehensively considered. To improve the convergence and effectiveness of the algorithm, NSGA-TS hybrid algorithm is applied for example analysis, which has better global search and local search ability. From the calculation and analysis results of an example, it can be seen that the model is effective in practical analysis, and expands the analysis idea of distribution network planning.

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.

Location of transformers during the extension of an electricity distribution network

The electricity network of a country is in continuous development, including the distribution transformers that provide power within a city. Efficient electricity networks depend on the good implementation of the principles of network planning and development. Moreover, technology development and the increasing standard of living are creating greater electricity demand. Besides, housing developments alter the need for electricity in an urban area and will require changes to control load density, adjustment of the voltage on distribution lines, installation of new lines and substations, and restructuring of existing ones. This study develops new mathematical and geometric methods that can be applied to all Low Voltage distribution networks to investigate load distribution, the effects of change and, provide a tool for distribution network planning. The analysis included the electrical power values to the new transformer, the shortest distribution routes between the transformers, and the costs, and provided optimum locations for new transformers. In this way, distribution network planning has been approached with a new method.

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.

Analysis and research on the sensitivity of current protection based on the planning and design of distribution networks

Analysis and research on the sensitivity of current protection based on the planning and design of distribution networks

Joint expansion planning of distribution network with uncertainty of demand load and renewable energy

Rational planning plays a key role in developing and improving operation security and stability of distribution networks (DNs). This paper proposes a novel method to solve the expansion of transmission lines (TLs) and the allocation of distributed generators (DGs) considering the uncertainty of load demand and renewable energy. The spanning-tree is a theoretical method specifically tailored to guarantee the radiality operation of distribution networks. Also, to guarantee the stability and reliability of the network, the probability function is used to describe the stochastic nature of load behavior and renewable sources fluctuation. Thus, the most proper installation location and time for TL and DG assets can be identified by modeling the joint expansion planning. The objective of the proposed model is minimizing the present value of the total social costs, including the cost of investment, purchasing energy, and environmental benefits. This mixed-integer nonlinear problem (MINLP) optimization model is solved based on GAMS environment. The effectiveness and scalability of this model is validated and illustrated based on the IEEE RTS-24 system.