Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> To improve system reliability for radial distribution systems with distributed generation (DG) under fault conditions, switch placement schemes are proposed to form self-supported areas after fault isolation. Customer priority is also considered in this problem. The switch placement problem is formulated as a nondifferentiable, multiobjective optimization problem. Graph-based algorithms, which incorporate direct load control, are developed to locate switches. Their results enable DG to support customers continuously in the event of fault. The proposed algorithms can be applied to unbalanced distribution networks with single or multiple distributed generators. Simulation results on a 394-bus distribution system, including priority customers, and single or multiple distributed generators, were also provided. <s> BIB001 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This paper presents a model for use in the problem of multistage planning of energy distribution systems including distributed generation. The expansion model allows alternatives to be considered for increasing the capacity of existing substations, for installing new ones, for using distributed generation, and for the possible change to feeders in terms of addition and removing feeders sections; combining, subdividing, and load transfer between feeders; and replacement of conductors. The objective function to be minimized is the present value of total installation costs (feeders and substations), of operating and maintaining the network, and of distributed generation. The model takes operational constraints on equipment capacities and voltage limits together into account with logical constraints, aimed at reducing the search space. This paper presents: (1) an extension to the linear disjunctive formulation to represent the inclusion, exclusion, and replacement of branches and (2) a generalization of constraints related to the creation of new paths which can be applied in more complex topologies. The resulting mixed integer linear model allows the optimal solution to be found using mathematical programming methods, such as the branch-and-bound algorithm. The validity and efficiency of the model are demonstrated in Part II of this paper. <s> BIB002 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> 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. <s> BIB003 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> In this paper, the remuneration of fixed costs of distribution networks with distributed generation is evaluated by means of an efficient planning strategy that includes the concept of fuzzy robustness of a given solution plan. As a key contribution, it is included the possibility of choice among different conductor sizes in order to assess the deep costs by overcapacity introduced by distributed generation. A single-stage multicriteria nonlinear problem is stated using three different criteria: investment cost in lines and transformers or distributed generators, power losses cost and unserved energy cost. Pareto or efficient plans are identified using the epsiv-Constraint/Weighting method and solved by Benders decomposition algorithm. Uncertainty associated to load demand and power injections of distributed resources are integrated using a fuzzy power flow in order to obtain the robustness indexes of each Pareto solution. The annualized fixed charge rate (AFCR) associated to new and existing distribution lines and transformers or distributed generators is assessed through a with-without analysis permitting to compute the annual avoided charge rate (AACR) in order to send incentives or charges to distributed generation promoters by the avoided or added investment costs on the system. The model is programmed in GAMS mathematical modeling language. The effectiveness of the proposal is demonstrated through a real 201-node distribution network. <s> BIB004 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This study presents an ordinal optimisation (OO) method for specifying the locations and capacities of distributed generation (DG) such that a trade-off between loss minimisation and DG capacity maximisation is achieved. The OO approach consists of three main phases. First, the large search space of potential combinations of DG locations is represented by sampling a relatively small number of alternatives. Second, the objective function value for each of the sampled alternatives is evaluated using a crude but computationally efficient linear programming model. Third, the top-s alternatives from the crude model evaluation are simulated via an exact non-linear programming optimal power flow (OPF) programme to find the best DG locations and capacities. OO theory allows computing the size s of the selected subset such that it contains at least k designs from among the true top-g samples with a pre-specified alignment probability AP. This study discusses problem-specific approaches for sampling, crude model implementation and subset size selection. The approach is validated by comparing with recently published results of a hybrid genetic algorithm OPF applied to a 69-node distribution network operating under Ofgem (UK) financial incentives for distribution network operators. <s> BIB005 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This paper proposes a methodology to achieve integrated planning and projects for secondary distribution circuits. The planning model is formulated as a mixed integer nonlinear programming problem (MINLP). In order to resolve this problem, a tabu search (TS) algorithm is used, with a neighborhood structure developed to explore the physical characteristics of specific geographies included in the planning and expansion of secondary networks, thus obtaining effective solutions as well as low operating costs and investments. The project stage of secondary circuits consists of calculating the mechanical efforts to determine the support structures of the primary and secondary distribution systems and determining the types of structures that should be used in the system according to topological and electrical parameters of the network and, therefore, accurately assessing the costs involved in the construction and/or reform of secondary systems. A constructive heuristic based on information of the electrical and topological conditions between the medium voltage and low voltage systems is used to connect the primary systems and secondary circuits. The results obtained from planning and design simulations of a real secondary system of electric energy distribution are presented. <s> BIB006 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Distributed generation expansion planning (DGEP) has been frequently reported in the literature around the world. In this scope, renewable technologies which are considered as a kind of distributed generations are developing due to their environmental benefits. However, only a few renewable energies have proven to be competitive so far, while their economic viability is also limited to certain regions of the world. In this paper, an encouraging mechanism is proposed in favor of clean technologies in the planning process. This mechanism is defined based on a grant function of emission not polluted which is paid to DG owners to promote renewable and clean technologies. In the planning process, a multi-objective optimization algorithm is applied to produce a Pareto set of optimal planning schemes by taking into account different objective functions (cost and grant functions). The best planning scheme among the Pareto set is chosen based on a composite utility which are obtained through a Monte Carlo simulation of uncertain situations. Distributed generation technologies which are considered in this paper are conventional and renewable technologies, namely photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro turbine (MT), gas turbine (GT), and reciprocal engine (RE). To assess the ability of the proposed method, a typical distribution system is used for expansion planning under two environmental scenarios. <s> BIB007 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Distribution system companies intend to supply electricity to its customers in an economical and reliable manner whereas customers in most distribution system are outspread and connect to distribution system with different type of equipments. These equipment usually have various types and resistance together, that produce highest loss and lowest reliability for distribution systems and customers that are not appreciated in networks. Distributed generations (DGs) are one of the best reliable solutions for these problems if they are allocated appropriately in the distribution system. This paper presents multi-objective function to determine the optimal locations to place DGs in distribution system to minimize power loss of the system and enhance reliability improvement and voltage profile. Time varying load is applied in this optimization to reach pragmatic results meanwhile all of the study and their requirement are based on cost/benefit forms. Finally to solve this multi-objective problem a novel approach based on dynamic programming is used. The proposed methodology is successfully applied to a study case and simulation results are reported to verify the proposed approach. <s> BIB008 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This paper presents a model for solving the multistage planning problem of a distribution network. The objective function to be minimized is the net present value of the investment cost to add, reinforce or replace feeders and substations, losses cost, and operation and maintenance cost. The model considers three levels of load in each node and two investment alternatives for each resource to be added, reinforced or replaced. The nonlinear objective function is approximated by a piecewise linear function, resulting in a mixed integer linear model that is solved using standard mathematical programming. The model allows us to find multiple solutions in addition to the optimal one, helping the decision maker to analyze and choose from a pool of solutions. In addition to the optimization problem, reliability indexes and associated costs are computed for each solution, based on the regulation model used in Brazil. Numerical results and discussion are presented for an illustrative 27-node test network. <s> BIB009 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This paper presents a model for calculating the optimal size of an energy storage system (ESS) in a microgrid considering reliability criterion. A larger ESS requires higher investment costs while reduces the microgrid operating cost. The optimal ESS sizing problem is proposed which minimizes the investment cost of the ESS, as well as expected microgrid operating cost. Utilizing the ESS, generation shortage due to outage of conventional units and intermittency of renewable units is handled; hence microgrid reliability criterion is satisfied. A practical model for ESS is utilized. Mixed-integer programming (MIP) is utilized to formulate the problem. Illustrative examples show the efficiency of the proposed model. <s> BIB010 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Distributed generation (DG) systems are considered an integral part in future distribution system planning. The active and reactive power injections from DG units, typically installed close to the load centers, are seen as a cost-effective solution for distribution system voltage support, energy saving, and reliability improvement. This paper proposes a novel distribution system expansion planning strategy encompassing renewable DG systems with schedulable and intermittent power generation patterns. The reactive capability limits of different renewable DG systems covering wind, solar photovoltaic, and biomass-based generation units are included in the planning model and the system uncertainties such as load demand, wind speed, and solar radiation are also accounted using probabilistic models. The problem of distribution system planning with renewable DG is formulated as constrained mixed integer nonlinear programming, wherein the total cost will be minimized with optimal allocation of various renewable DG systems. A solution algorithm integrating TRIBE particle swarm optimization (TRIBE PSO) and ordinal optimization (OO) is developed to effectively obtain optimal and near-optimal solutions for system planners. TRIBE PSO, OO, and the proposed algorithm are applied to a practical test system and results are compared and presented. <s> BIB011 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> In this work, the planning problem of primary distribution networks is formulated as a multi-objective mixed-integer non-linear programming model (MINLP). The objective functions of this model are the expansion and operation investment costs of primary distribution networks as well as the system's reliability costs in the contingency events. The reliability costs are obtained by means of calculating the non-supplied energy because of the repairing and switching operations in the distribution network carried out to isolate and to redistribute loads in the affected sections by permanent faults. In order to solve the expansion problem of the primary network a Multi-objective Reactive Tabu Search algorithm (MO-RTS) is proposed. The concepts of dominance are used to obtain Pareto's optimal frontier in the MO-RTS. The problem of placement of sectionalising switches (automatic or manual) to restore the distribution network and to reduce non-supplied energy costs when permanent faults occur in the network is solved simultaneously with the network expansion planning problem by means of a dedicated genetic algorithm. For testing, the proposed methodology is used as a primary power distribution system, with 180 points of consumption, where 49 already exist and 131 can be added to the system during the planning process. <s> BIB012 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This paper presents a new method to solve the dynamic sub-transmission substation expansion planning (SSEP) in electric power distribution networks. The method employs a new algorithm based on learning automata for optimization process. The developed algorithm includes different electrical constraints such as voltage drops, thermal limits, power flow and radial flow constraints. Moreover, prevalent cost indices are taken into consideration. The proposed method is used to solve the dynamic SSEP for Birjand city, center of South-Khorasan province of Iran, up to the year 2024. In addition, effects of the dynamic and pseudo-dynamic planning models are investigated at the study region and the obtained results are compared to those of genetic algorithm. Detailed numerical results and comparisons presented in the paper show that the proposed approach leads to proper solutions and can be used as an effective tool for the dynamic sub-transmission substation expansion planning in an actual large scale distribution network. <s> BIB013 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Abstract This paper proposes a long-term planning method to maximize the benefits of network reconfiguration and distributed generation (DG) allocation in distribution networks. The proposed method handles long-term yearly load increase and seeks to define the reinforcements (i.e., line upgrades, network reconfiguration, and DG integration) and when and where they are required to meet the load rise with minimal cost and acceptable quality standards. The objectives considered in this paper are: economic (costs of line upgrades, energy losses, switching operations, and DG capital, operation and maintenance costs) and environmental (emissions from grid and DG units). The proposed method takes into consideration the uncertainty related to renewable DG output power and the load variability. The long-term planning problem is defined as multi-objective nonlinear mixed integer programming. The outcomes of the planning problem are the Pareto front, which represents different optimum operating system points. Finally, the local distribution company (LDC) can choose the system operating point based on its preferences. <s> BIB014 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Power intermittency and maintenance cost are the major challenges in harvesting wind energy. This paper proposes a multicriteria optimization model to design and operate a wind-based distributed generation (DG) system. The goal is to determine the equipment sizing, siting, and maintenance schedules so that the system cost is minimized while the turbine reliability is maximized. System cost comprises initial capital, operations, maintenance, downtime losses, and environmental penalty. The study makes an early attempt to incorporate the maintenance policy of generating units into the planning model. The moment method and the central limit theorem are used to characterize the power intermittency and the load uncertainty. A genetic algorithm is developed to search the nondominant solution set for the equipment siting, sizing, and maintenance intervals. The proposed model is demonstrated on the IEEE 37-node distribution network considering independent and correlated wind speed scenarios. <s> BIB015 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Multistage distribution network expansion because of load growth is a complex problem in distribution planning. The problem includes minimizing cost of objective function subject to technical constraints. The objective function consists of investment, operation and reliability costs. In this paper, HV/MV substations, main and reserve MV feeders, dispatchable DG sources and storage units are considered as possible solutions for multistage distribution expansion planning. A three-load level is used for variable load and some strategies are proposed for DG and storage units operation. A modified PSO algorithm is applied to solve the complex optimization problem. Numerical results of the case studies show the ability of the modification. Moreover, the proposed strategies improve the distribution network from both economical and reliability points of view compared with the other methods. <s> BIB016 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile. <s> BIB017 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Planning distribution systems without considering the operation status of multiple distributed generation (DG) units could result in constraining the network, lowering the utilization of its assets and minimizing the total DG capacity that can be accommodated. In this paper, the impact of multiple DG configurations on the potential of active network management (ANM) schemes is firstly investigated. Secondly, the paper proposes a multi-configuration multi-period optimal power flow (OPF)-based technique (MMOPF) for assessing the maximum DG capacity under ANM schemes considering 1) variability of demand and generation profiles (multi-period scenarios), and 2) different operational status of DG units (multi-configurations). The results show that the availability of DGs at certain locations could critically impact the amount of DG capacity at other locations. If DGs are properly allocated and sized at certain locations up to the optimal limits, even with a “fit-and-forget” approach, the total connected DG capacity can be maximized, with minimum utilization of ANM schemes. However, exceeding these optimal limits may lead to minimizing the total DG penetration in the long term, impacting the system reliability due to the operational status of multiple DG units, and consequently, imposing more investments on ANM schemes to increase the amount of connected DG capacity. <s> BIB018 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before construction of the systems. Therefore, additional distribution facilities are needed to be planned and prepared for the future growth of the electrical demand as well as the increase of network hosting capacity by DG units. This paper presents a multiobjective optimization algorithm for the MDEP (Multi-Stage Distribution Expansion Planning) in the presence of DGs using nonlinear formulations. The objective functions of the MDEP consist of minimization of costs, END (Energy-Not-Distributed), active power losses and voltage stability index based on SCC (Short Circuit Capacity). A MPSO (modified Particle Swarm Optimization) algorithm is developed and used for this multiobjective MDEP optimization. In the proposed MPSO algorithm, a new mutation method is implemented to improve the global searching ability and restrain the premature convergence to local minima. The effectiveness of the proposed method is tested on a typical 33-bus test system and results are presented. <s> BIB019 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This study presents an integrated methodology that considers renewable distributed generation (RDG) and demand responses (DR) as options for planning distribution systems in a transition towards low-carbon sustainability. It is assumed that demand responsiveness is enabled by real-time pricing (RTP), and the problem has been formulated as a dynamic two-stage model. It co-optimizes the allocation of renewables [including wind and solar photovoltaic (PV)], non-renewable DG units (gas turbines) and smart metering (SM) simultaneously with network reinforcement for minimizing the total economic and carbon-emission costs over planning horizons. The behavior compliance to RTP is described through a nodal-based DR model, in which the fading effect attended during the load recovery is highlighted. Besides, uncertainties associated with renewable energy generation and price-responsiveness of customers are also taken into account and represented by multiple probabilistic scenarios. The proposed methodology is implemented by employing an efficient hybrid algorithm and applied to a typical distribution test system. The results demonstrate the effectiveness in improving the efficiency of RDG operations and mitigating CO2 footprint of distribution systems, when compared with the conventional planning paradigms. <s> BIB020 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> This paper proposes a hybrid optimization method for optimal allocation of wind turbines (WTs) that combines a fast and elitist multiobjective genetic algorithm (MO-GA) and the market-based optimal power flow (OPF) to jointly minimize the total energy losses and maximize the net present value associated with the WT investment over a planning horizon. The method is conceived for distributed-generator-owning distribution network operators to find the optimal numbers and sizes of WTs among different potential combinations. MO-GA is used to select, among all the candidate buses, the optimal sites and sizes of WTs. A nondominated sorting GA II procedure is used for finding multiple Pareto-optimal solutions in a multiobjective optimization problem, while market-based OPF is used to simulate an electricity market session. The effectiveness of the method is demonstrated with an 84-bus 11.4-kV radial distribution system. <s> BIB021 </s> Overview of Electric Energy Distribution Networks Expansion Planning <s> C. CONSTRAINTS <s> Abstract The management of distributed energy resources (DER) in power distribution systems and the concept of demand side management (DSM) are becoming increasingly important in recent years, provided that emerging communication technologies contribute to the formation of smart distribution networks of the future. Several methods have been proposed in the literature for the optimal operation of smart distribution networks (OOSDN) with renewables and/or non-renewable DER, DSM and energy storage systems. The main scope of this paper is to review the most significant papers in the area of OOSDN and to introduce a taxonomy of models and optimization methods that are applied to the OOSDN problem. Moreover, the basic schemes for active network management are briefly presented. The article also discusses challenges and areas for future research in the field of OOSDN. <s> BIB022
We typically define DEP as an optimization problem with several constraint variables, including: a) Power balance: this constraint guarantees active and reactive power generation and consumption equity in each time step. b) Voltage level: For stability reasons, voltage deviation must be kept within some boundaries within a voltage profile. Distribution companies (DISCOs) will generally provide the standard voltage profile for the customers BIB013 . c) Power flow: the power flow of the distribution feeders must be within the permissible capacity of the branches where we formulate the constraints with a set of inequality equations. d) Controlling active and reactive output power of DG facilities: A threshold must be set for the active and reactive power generation of the DG units. Since the reactive power of DGs can affect the voltage profile and power losses, for the best allocation of DGs in the network, we must take into account their reactive capabilities in planning studies BIB018 , BIB001 . e) Penetration limit of DGs: the generated power with DGs must also be within a set limit. Typically, the penetration level of DG units is ∼ 30-40 % of the main substation rating BIB014 , BIB001 . f) Substation capacity: the loading of substations must also be within a permissible interval BIB013 . g) Radiality: due to the operational issues, distribution feeders must be operated with a radial configuration. One of the necessary conditions to construct a radial network is the equality between the total number of branches and the number of buses mines one. However, other considerations must be further made to guarantee the connectivity and radiality of the network BIB022 , BIB008 , BIB004 . h) Total investment: the total amount of financial resources is limited for installing new instruments and increasing the existing facilities that will affect the expansion plan of the systems BIB010 . i) Power factor regulation: The amounts of power factors must satisfy the related standards BIB005 , BIB011 , BIB021 . j) Power losses: the power losses of the network are one of the most critical considerations and consist of the losses of the feeders, as well as the transformers BIB006 , BIB019 , BIB020 . k) Logical constraints: these constraints determine how the network must operate, e.g. only one type of equipment can be chosen among all options BIB012 , BIB018 . Fig. 5 shows the normalized number of constraints used in the literature. There are some additional constraints such as Reliability constraint BIB015 ,  , Capacity of energy storage units BIB016 and load shedding BIB002 , BIB003 , BIB009 ,  , electric vehicle charge station constraint BIB017 and DG emission limitation BIB007 . As noticed from Fig. 5 , most papers have studied the voltage drop, load balance, and feeders' loading capacity constraints. At the same time, a limited number focused on other constraints like DGs' reactive capability and the penetration level of DGs. Note that the main aim of the DEP studies is to provide the customers' load. Since some of the references have used the separate load flow to give the customer's load, we do not bring such references under the category of power balance constraint. Power loss is an essential measure in distribution systems and is considered as an objective function in many papers, and that's why power loss has less share in Fig. 5 compared to the other constraints.