Distribution Network Planning Research Articles

Intelligent decision-making of distribution network planning scheme with distributed wind power generations

This paper first analyzes the impact of the volatility of distributed power generation (DG) output on distribution network planning. This impact mainly includes three aspects: system equivalent load forecasting, distribution network planning decision, and stable operation of the system. To reduce the impact of this instability, this paper takes the wind power system as an example, and establishes the corresponding relationship model of the output state-year output scenario. Secondly, combined with the life cycle theory and multi-scene partitioning, a comprehensive decision-making objective function of the distribution network planning scheme for a single area considering investment operation costs, additional backup costs, energy-saving, and environmental protection benefits, and system reliability costs were established. Because of the many parameter calculations and selection judgments involved in the decision model, an intelligent decision framework based on Dempster-Shafer evidence theory and Multi-agent system (DS-MAS) is proposed after the decision target is established, that is, which can automatically select the fitting selection analysis parameters according to different conditions. Finally, the effectiveness of the model is verified by a practical example.

Optimal Planning of a Distribution Network in Egypt

Distribution networks planning is a very complex task as it involves the consideration of various important issues. A model for optimal planning of a distribution network is presented in detail, using Distributed Generation (DG). This paper presented a detailed analysis of the West Delta Network (WDN) as a part of the Egyptian distribution network with a 30% increase in system loading. An Oscillatory Particle Swarm Optimization (OPSO) technique was used to find the optimal locations and sizes of one DG or multiple DGs for achieving the objectives of minimizing total active power losses and system voltage regulation as a single-and-multi-objective optimization problem in a distribution network. Several penetration scenarios have done to evaluate concentrated (at one location) and distributed DGs (at different locations). The results are presented in a comparative form and thoroughly discussed. The obtained results will help in system operation with DG integration and identifying the critical penetration levels for the studied system.

A novel approach to increase the share of renewable purchase obligation for planning of distribution network including grid scale energy storage

Abstract In recent times, producing electricity with lower carbon emissions has resulted in strong clean energy incorporation into the distribution network. The technical development of weather-driven renewable distributed generation units, the global approach to reducing pollution emissions, and the potential for independent power producers to engage in distribution network planning (DNP) based on the participation in the increasing share of renewable purchasing obligation (RPO) are some of the essential reasons for including renewable-based distributed generation (RBDG) as an expansion investment. The Grid-Scale Energy Storage System (GSESS) is proposed as a promising solution in the literature to boost the energy storage accompanied by RBDG and also to increase power generation. In this respect, the technological, economic, and environmental evaluation of the expansion of RBDG concerning the RPO is formulated in the objective function. Therefore, a novel approach to modeling the composite DNP problem in the regulated power system is proposed in this paper. The goal is to increase the allocation of PVDG, WTDG, and GSESS in DNP to improve the quicker retirement of the fossil fuel-based power plant to increase total profits for the distribution network operator (DNO), and improve the voltage deviation, reduce carbon emissions over a defined planning period. The increment in RPO and decrement in the power purchase agreement will help DNO to fulfill round-the-clock supply for all classes of consumers. A recently developed new metaheuristic transient search optimization (TSO) based on electrical storage elements’ stimulation behavior is implemented to find the optimal solution for multi-objective function. The balance between the exploration and exploitation capability makes the TSO suitable for the proposed power flow problem with PVDG, WTDG, and GSESS. For this research, the IEEE-33 and IEEE-69 low and medium bus distribution networks are considered under a defined load growth for planning duration with the distinct load demand models’ aggregation. The findings of the results after comparing with well-known optimization techniques DE and PSO confirm the feasibility of the method suggested.

PERENCANAAN SISTEM DISTRIBUSI AIR BERSIH DAN PENGOLAHAN AIR BUANGAN PADA PEMBANGUNAN TOWER A APARTEMEN TAMANSARI EMERALD SURABAYA

Plumbing installation planning is one of the most important things in building constructions. The planning of clean water distribution network in the Tamansari Emerald Surabaya Apartment building is designed to serve the clean water needs of residents and customers. Plans are made in accordance with standards and regulations regarding the provision of clean water in the apartment. The Tamansari Emerald Surabaya Apartment is a building with 48 floors consisting of 1 basement floor, 1 commercial floor, 13 parking floors, and 33 residential floors. Clean water needs are calculated based on the number of residents and room types with a total building water requirement of 312. m³ / day. The diameter of vertical clean water pipe used is 4 inches,meanwhile the diameter for distribution pipes range of ¾ inch to 1 ½ inch. The clean water distribution system uses a ground water tank and roof tank, which those volumes are 120 m3 using 2 units tanks of 60 m3 and 20.8 m³using FRP-tank.

Bi-level planning for distribution network including distributed generations and electric vehicle charging stations to meet the requirements of internet of things construction

With the development of power internet of things technology, the application of internet of vehicles technology in the field of electric vehicles (EVs) is constantly maturing and improving. In line with the concept of building an environment-friendly society, distributed generations (DGs) and EVs are being built and put into use in large numbers. In this context, in order to improve the accuracy of distribution network planning, this paper proposes a distribution network planning method based on big data technology. The upper layer aims to minimize the present value of the comprehensive cost of the distribution network, and the lower layer aims to minimize the construction, operation, and maintenance costs of electric vehicle charging stations (EVCSs) and DGs. Under the constraint of relevant constraints, the optimal grid structure of the distribution network including DGs and EVCSs is obtained. The effectiveness of the proposed method is demonstrated using a 54-bus distribution system.

Regional active distribution network planning study based on robust optimization

With the increasing installed capacity of new energy generation, the randomness and volatility of new energy generation has seriously affected the stable operation of the grid. And the traditional generation side dispatching method can no longer meet the demand of the grid to maintain stable operation, which greatly affects the consumption of new energy. In order to improve the rate of new energy consumption and economic efficiency, this paper proposed a regional active distribution network economic evaluation index that takes construction costs, operating costs, and new energy subsidies into account. What is more, the paper summarized the physical constraints of each equipment in the regional active distribution network. Combining the economic evaluation index and the physical constraints, the paper raised a regional active distribution network planning and scheduling model based on robust optimization. Finally, the regional active distribution network planning model based on robust optimization is validated in terms of the new energy consumption rate and the economic benefits by optimizing the examples of load-based regional active distribution network.

Joint active and reactive for allocation of renewable energy and energy storage under uncertain coupling

Growing energy storage systems for intermittent renewable energy to maintain the power balance has expanded the investment cost in distribution network planning. Existing works on the energy storage system and intermittent renewable energy allocation, however, do not adequately consider the joint operation of active and reactive power under uncertain coupling, leading to a lack of economic efficiency in the investment decision. Regarding this, a techno-economic framework is urgently needed to take the responsibility of accommodating intermittent renewable energy. To do so, a joint active and reactive operation strategy is developed to fully harness the potential flexibility existed in intermittent renewable energy and energy storage system, and to determine their optimal allocation under uncertain coupling. In the proposed strategy, the state of energy is simulated via the Fourier-Legendre series to capture the charging/discharging characteristic of the energy storage system. The expected reserve and expected curtailment to address the risk caused by uncertainties are respectively modeled by a joint probability-based value of loss load and value of power curtailment. To tackle the net load fluctuation imposed by intermittent renewable energy, a price-based active and reactive integrated demand response is established. Case studies prove the feasibility and effectiveness of the proposed model in reducing annual cost, flattening net load curve as well as improving voltage quality for stochastic distribution network planning.

Microgrid‐based resilient distribution network planning for a new town

Nowadays, the deployment of micro-grids (MGs) is one of the important trends in modern distribution network planning. Implementing this strategy aims to improve the ability of the distribution network to withstand extreme weather conditions and supplying critical loads. While the literature has focused chiefly on operating distribution systems and partitioning them into MGs, in this work, the idea of planning a new low voltage (LV) radial distribution system based on multi MGs for a greenfield is proposed. The main contribution is providing a framework to plan a resilient LV distribution system step by step for a new town without any operating grid. In the planning process, some MGs are formed and their service area and technical specifications like the number of MGs and their sizes are determined by a multi-objective optimization algorithm considering hardening and resiliency issues. The planning is done in a way that all predefined critical loads will be supplied. To consider the effects of extreme weather conditions, failure rates of poles and conductors due to thunderstorms are considered as a function of wind speed, and their appropriate models are used. The provided method is implemented in a test case with three major scenarios. Accordingly, planning in normal conditions considering hardening options and resilient network planning cases are evaluated. Simulation results and resiliency metrics are compared in detail.

Reliability Based Power Distribution Network Planning Using Fuzzy Logic

This paper presents a fuzzy system for reliability-based power distribution network planning. The proposed Mamdani type fuzzy inference system with subsequent application of the Bellman-Zadeh decision-making method is used to evaluate the reliability of the power line feeders as criteria for power system planning. Unplanned outages of system components, the Energy Not Supplied (ENS) and age of the power lines are used as input variables of the system and are fuzzified using triangular fuzzy functions. The proposed model was tested on a model of a realistic distribution network in order to prove its relevance and applicability. Results demonstrated that this model could make a contribution in this field as it can be used in practical planning situations for project priority ranking.

Automatic routing of medium voltage distribution network based on load complementary characteristics and power supply unit division

In view of the problems of large network scale and low equipment utilization efficiency caused by the lack of consideration of load complementary characteristics in the current distribution network planning, a new practical automatic routing method of medium voltage distribution network considering load complementary characteristics and power supply unit division is proposed. Firstly, based on the existing conclusions of load clustering and gridding planning, the concepts of feeder block and power supply unit of medium voltage distribution network are redefined, and the framework of medium voltage distribution network planning considering the power supply unit division is proposed. Secondly, the evaluation indexes of feeder block division and power supply unit division considering the load complementary characteristics are proposed, and a centerline swing distance weighted clustering algorithm is proposed, which is used to realize the feeder block division. Thirdly, considering the annual comprehensive cost of line planning and the outage loss cost based on reliability index, the medium voltage distribution network planning model is established based on the power supply unit division. The automatic routing method is proposed based on ant colony algorithm, which is used to realize the combinatorial solution of the trunk line and branch line. Finally, an example is given to verify the scientificity and practicability of the model and method proposed in this paper.

Concepts, Structure and Developments of High-Reliability Cyber-Physical Fusion Based Coordinated Planning for Distribution System

Coordinated control is imperative for the distribution network with the integration of wind power, photovoltaic system, and energy storage system. Meanwhile, the advanced automation terminal, intelligent control technology, and information communication technologies have greatly promoted the informatization of distribution networks which also increase the correlation between the physical system (primary system) and the cyber system (secondary system). Hence, it is critical to comprehensively coordinate the planning of the cyber-physical system for building a highly reliable power grid. This work summarizes a series of challenges brought by the highly coupled cyber-physical system, such as the primary and secondary collaborated planning models and solution algorithms. Then, the reliability assessment theories of cyber-physical systems and their application in distribution network planning models are introduced. Finally, three development directions of distribution network planning in the future are proposed, considering primary and secondary system coordinated planning.

Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties

Power systems have incorporated many new technologies in recent years and the introduction of energy storage systems and demand response provides additional challenges for their operation and expansion planning. Current distribution networks are complex active networks where many technologies are included, which must be considered and properly represented in expansion planning models. Thus, this paper proposes a robust model to solve the coordinated operation and expansion planning of active distribution networks with multiple microgrids, distributed energy resources (DERs), demand response, and N-1 generation contingency. The objective is to determine the best expansion planning proposals and the optimal daily operation (24-hour representation) for the DERs under the worst realization of uncertainties, using a contingency-constrained approach. Besides, the load is represented by non-controllable, controllable, and deferrable portions. The model is formulated as a tri-level problem that is solved using a two-stage robust optimization approach. The proposed method is illustrated using a modified version of the IEEE 123-bus test system. The results show that the coordinated operation and expansion planning decreases the total cost of the problem and provides more consistent results for demand response and DERs coordination. Simulations show a reduction of 13.8% in the total cost if the daily operation and demand response are represented, and the inclusion of contingencies provides a reduction of 70% in the EENS (expected energy not served) reliability index for the case study.

Holistic approach to resilient electrical energy distribution network planning

This paper proposes a two-objective linearized resilient architecture (LRA) model for distribution networks to achieve a strictly resilient network during natural disasters like earthquakes and floods. To obtain this goal, the proposed LRA framework is based on the planning of the energy storage system (ESS), hardening and tie lines, and backup distributed generation (DG). Therefore, the proposed model minimizes the sum of planning and expected operation costs in the first objective function, and the total load shedding and repair costs originates from earthquakes and floods in the second objective function. Also, it constraints to the network planning model, linearized equations of the system operation, and system reconfiguration formulation. Moreover, stochastic programming models the uncertain availability of the network equipment during the natural disaster condition, the load and electricity price. In the next step, the ε-constraint-based Pareto optimization is used to achieve an equivalent single-objective LRA model and obtain the best compromise solution. Finally, the proposed strategy is applied to a standard test distribution network. Numerical simulation confirms the capability of the proposed method in obtaining a resilient distribution network during natural disasters.

A novel algorithm based on the combination of AC-OPF and GA for the optimal sizing and location of DERs into distribution networks

This article proposes an algorithm to obtain an optimal local solution for the network planning process related to the optimal integration of different renewable energy sources (RES) and different Battery Energy Storage Systems (BESS) into a distribution network (DN). The algorithm provides strategic information related to investment and operation costs regarding the type of technology, location, and sizing. The mathematical formulation is based on an AC optimal power flow (OPF) to ensure the network’s minimal stability conditions. Besides, through the use of linearization and a modified version of a genetic algorithm (GA), the algorithm proposed breaks the 24 h wall, used until now in the literature, and extend it to 8760 h, which represents a much more realistic scenario to define the storage and power generation capacity of a DN in a planning context. The algorithm has been tested in a modified version of the IEEE 33-bus considering two cases of study: an off-grid case and grid-connected case, to measure the CapEx and OpEx variability, achieving to show that a grid-connected system reduces the installed capacity of DG and BESS in 37.4% and the CapEx 22.8%. • A novel algorithm is presented for the optimal simultaneous integration of DG and BESS into DN in terms of capacity and location. • A feasible solution for 8760 h as a time horizon, which breaks the 24-hours wall of related literature. • A much more realistic sizing for DG and BESS for distribution network planning is obtained. • The impact of an Off-grid and Grid-connected system on the planning process in terms of CapEx/OpEx.

Service Restoring Reconfiguration for Distribution Networks Considering Uncertainty in Available Information

The recent growth in the penetration of photovoltaic generation systems (PVs) has brought new difficulties in the operating and planning of electric power distribution networks. This is because operators of the distribution networks normally cannot monitor or control the output of the PVs, which introduces additional uncertainty into the available information that operations must rely on. This paper focuses on the service restoration of the distribution networks, and the authors propose a problem framework and its solution method that finds the optimal restoration configuration under extensive PV installation. The service restoration problems have been formulated as combinatorial optimization problems. They do, however, require accurate information on load sections, which is impractical in distribution networks with extensively installed PVs. A combined framework of robust optimization and two-stage stochastic programming adopted in the proposed problem formulation enables us to deal with the PV-originated uncertainty using readily available information only. In addition, this problem framework can be treated by a traditional solution method with slight extensions. The validity of the authors’ proposal is verified through numerical simulations on a real-scale distribution network model and a discussion of their results.

Research on Charge and Discharge Strategy of Electric Vehicles Based on New Distribution Network Planning

Based on the planning and distribution of new distribution network, the charging and discharging strategies of existing electric vehicles are studied. According to the number and distribution of existing charging piles, as well as the charging quantity of electric vehicles in each region, the travel law of electric vehicles is analyzed by using the travel chain theory and Monte Carlo algorithm; then, according to the user travel rules and the charging pile capacity of each area, each area is rated, and a hierarchical V2G distribution network is designed. Then, the power supply behavior of electric vehicles in V2G distribution network is analyzed, and the main power supply time period of electric vehicles in the improved V2G distribution network is obtained by using Monte Carlo algorithm; finally, the effectiveness of the proposed scheme is verified by an example, and the power supply situation of electric vehicles is classified.

Optimization Decision Method based on Nonlinear Analytic Hierarchy Process for Active Distribution Network Planning

Aiming at the investment environment of the distribution network, this paper deeply analyses the investment conditions of the distribution network, introduces the analytic hierarchy process and modern investment theory, establishes the analytic hierarchy of the investment conditions in the distribution network project, and proposes an optimization decision-making method of investment plan in distribution network. This paper also establishes two new concepts: condition score and correlation score, uses the improving analytic hierarchy process to calculate the weights, proposes a priority ranking method for distribution network projects, and gives detailed process. to formulate distribution network investment plans. The application of the proposed method to optimize the distribution network planning scheme shows that the optimization investment scheme given has better investment benefits under the condition of the power supply reliability requirements of the distribution network and investment capital constraints.

Construction and Application of Dual Q Programming Model for Medium Voltage Distribution Network

With the rapid development of China’s economy, people’s demand for electricity is increasing. In order to ensure the reliability of power supply, a dual Q programming model of distribution network is proposed. In this paper, the overview of “double Q theory” and key technologies are described, and the problems and optimization of medium voltage distribution network planning are discussed for readers’ reference.

Day-Ahead Hourly Operation Planning of Distribution Networks with Photovoltaic Generation Integrated by Smart Inverters via Mixed-Integer Volt/Var Optimization Problems.

A penetração da geração fotovoltaica distribuída nas redes de distribuição tornou-se uma realidade; entretanto, ainda impõe desafios a serem superados, como o funcionamento dessas redes com desvios mínimos nos perfis de magnitude de tensão. Assim, este trabalho propõe o planejamento diário da operação horária de redes de distribuição visando minimizar o desvio nos perfis de magnitude de tensão por meio de ajustes de tap ótimos de transformadores em subestações, ajustes ótimos de bancos de capacitores chaveados remotamente ao longo dos alimentadores primários e injeções de potência ativa e reativa da geração fotovoltaica distribuída por inversores inteligentes. Em tal problema, as variáveis de controle discretas associadas aos taps de transformadores e susceptâncias equivalentes de bancos de capacitores chaveados remotamente são tratadas por função penalidade senoidal que modificam o problema de programação não linear inteira mista original em um problema de programação não linear com apenas variáveis de decisão contínuas. Os resultados obtidos para redes de distribuição com 69 e 135 nós mostram que o modelo OVV proposto e sua metodologia de resolução são eficientes na redução do desvio nos perfis de magnitude de tensão e, ao mesmo tempo, na redução da demanda geral de potência reativa da rede de distribuição.

Integrated Transmission and Distribution System Expansion Planning Under Uncertainty

The increased deployment of distributed generation calls for the coordination and interaction between the transmission and distribution levels. This requirement is particularly relevant for planning purposes when renewable-based generation is involved. Unfortunately, in current industry practice, transmission and distribution network planners solve their problems independent of each other, thereby leading to suboptimal solutions. Within this context, this paper addresses the integrated expansion planning problem of transmission and distribution systems where investments in network and generation assets are jointly considered. Several alternatives are available for the installation of lines as well as conventional and renewable-based generators at both system levels. Thus, the optimal expansion plan identifies the best alternative for the candidate assets under the uncertainty associated with demand and renewable-based power production. The proposed model is an instance of stochastic programming wherein uncertainty is characterized through a set of scenarios that explicitly capture the correlation between the uncertain parameters. The resulting stochastic program is driven by the minimization of the expected total cost, which comprises the costs related to investment decisions and system operation. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program for which finite convergence to optimality is guaranteed. Numerical results show the effective performance of the proposed approach.