Remuneration of Distribution Networks using a Fuzzy Multicriteria Planning Algorithm (original) (raw)

Long Term Cost Allocation Methodology for Distribution Networks with Distributed Generation

This paper proposes a novel access pricing framework to remunerate investment costs of distribution networks based on Long Term Prices (LTP) taking into account the avoided costs produced by the distributed generation (DG). The proposed methodology uses a fuzzy multicriteria distribution planning algorithm based on simulated annealing metaheuristic in order to obtain effi-cient expansion plans regarding the impact of distributed sources. Avoided investment costs are computed for sev-eral robustness indexes and allocated among consumers and generators by means of a modified roll-in-embedded cost allocation method. The proposed cost allocation ap-proach is simple to implement using efficient plans and does not require high computer performance. The model has been successfully applied and results were discussed from a distribution test system. 1 INTRODUCTION Electricity markets have been established based on the statement of open access and nondiscriminatory use of transmission and dis...

A fuzzy environmental-technical-economic model for distributed generation planning

Energy, 2011

To determine the optimal size, location and also the proper technology of distributed generation (DG) units in distribution systems, a static fuzzy multiobjective model is proposed in this paper. The proposed model can concurrently optimize a number of conflicting and competing objective functions including economic, technical and environmental attributes. The economic function is the profit of a distribution company (DisCo) from selling the DG output power to its customers. The contribution of this model is the consideration of some DG marginal revenues in the economic function. Inclusion of marginal revenues would not only reduce the investment risks of DG technologies, but also would enable the optimal penetration of DG units. The proposed DG planning framework considers various DG technologies such as photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro-turbine (MT), gas turbine (GT) and diesel engine (DE). The system uncertainties (including those for the energy demand, energy price and DG technologies operating and investment costs) are modeled using fuzzy numbers. The numerical case studies have been carried out using the IEEE 37-node distribution test system to demonstrate the performance of the proposed DG planning model.

A Generalized Multistage Economic Planning Model for Distribution System Containing DG Units

Distributed generation (DG) has gained a lot of attractions in the power sector due to its ability in power loss reduction, increased reliability, low investment cost, and most significantly, to exploit renewable energy resources like wind, photo-voltaic and micro-turbines, which produce power with minimum greenhouse-gas emissions. The installation of DG units into distribution system requires efficient expansion planning technique to minimize the investment and operation cost of the system.. In this paper, a new mixed integer nonlinear model for solving the multistage distribution system network planning problem including DG has been developed. The model is able to deal with different planning scenarios such as buying energy from a nearby electric distribution company through an intertie, upgrading substations, upgrading feeders or investing in DG units. The model takes into account the operational constraints of equipment capacities and voltage limits as well as the dynamic load growth. Finally, the developed mathematical mixed integer model was applied to minimize the planning cost of the studied distribution network including DG units. The implemented mixed integer nonlinear planning model is coded using LINGO V14 optimization software.

Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration

Electric Power Systems Research, 2013

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.

Distribution planning with reliability options for distributed generation

Electric Power Systems Research, 2010

The promotion of electricity generation from renewable energy sources (RES) and combined heat and power (CHP) has resulted in increasing penetration levels of distributed generation (DG). However, largescale connection of DG involves profound changes in the operation and planning of electricity distribution networks. Distribution System Operators (DSOs) play a key role since these agents have to provide flexibility to their networks in order to integrate DG. Article 14.7 of EU Electricity Directive states that DSOs should consider DG as an alternative to new network investments. This is a challenging task, particularly under the current regulatory framework where DSOs must be legally and functionally unbundled from other activities in the electricity sector. This paper proposes a market mechanism, referred to as reliability options for distributed generation (RODG), which provides DSOs with an alternative to the investment in new distribution facilities. The mechanism proposed allocates the firm capacity required to DG embedded in the distribution network through a competitive auction. Additionally, RODG make DG partly responsible for reliability and provide DG with incentives for a more efficient operation taking into account the network conditions.

Interaction between Technical and Economic Benefits in Distributed Generation

Electrical and Automation Engineering, 2022

The definition of a restricted power supply area for a distribution network disqualifies this scheme as a distributed product even though it is a very common dg scheme. Power system quality is a key issue for low and medium voltage power companies and consumers, to minimize power network losses; this paper provides guidelines for guaranteed allocation and distribution of distributed generation (DG) in distribution systems for an acceptable reliability level and voltage profile. The optimization process involves the use of genetic algorithms (GA) techniques and is solved by combining systems to estimate system reliability, losses and dg impacts on the voltage profile. The fitness evaluation process leads to the determination of the ga's relationship between investment and operating costs as a benefit of setting numerical units. Estimation based on current flow method for radial networks reconciliation of scattered generator losses with profile of voltage profile.

Comprehensive mixed‐integer linear programming model for distribution system reconfiguration considering DGs

IET Generation, Transmission & Distribution, 2018

Distribution system reconfiguration (DSR) is a critical process that improves the power transfer efficiency and reduces the overall operational cost. There have been various methods for addressing the DSR problems. Recently, DSR problems formulated in mixed-integer linear programming (MILP) has gained popularity as they generally can be solved by the state-ofthe-art commercially accessible linear programming solvers, and is able to solve the system with thousands of unknown variables within a reasonable time. However, in some MILP formulations, the distribution line losses are omitted in the nodal power injections for the sake of simplicity. This compromises the accuracy of the linearised model and contributes to the disparity between the MILP and the true non-linear model. Hence, in this study, new formulations are introduced for embedding the expressions of line losses inside load flow equations so that the deviations between the modelled and exact losses notably reduce. Moreover, other novel formulations have also been presented for simultaneously optimising distributed generation (DG) locations and sizes, while at the same time considering various DG's modes of connection to the distribution grid. The validity and effectiveness of the proposed MILP model is tested on standard IEEE systems and actual distribution network. Nomenclature Indices i/ j, N node (bus), number of nodes (buses) k, D i , D s node (bus), set of downstream nodes connected to node i, set of feeder (substation) nodes s, S segment, set of segments l, L PV , L PQ DG index, set of PV type DGs, set of PQ type DGs Parameters R j, i , X j, i resistance and reactance of branch connecting nodes i and j PD i , QD j active and reactive power demands at node i SB j, i MAX line capacities SG l MIN , SG l MAX DG size limits PS j, i s , QS j, i s parameters known prior to optimisation for determining the maximum active and reactive power flows of the sth segment mp j, i s , mq j, i s slopes of the sth segment for real and reactive power flows pl MAX maximum allowable DG penetration level n g maximum number of DGs that can be connected to any bus V i MIN , V i MAX upper and lower boundaries of voltage magnitude V i SP specified voltage magnitude for PV bus pf l power factor of the lth DG Variables PB j, i , QB j, i active and reactive power flows from bus i to bus j PL j, i , QL j, i active and reactive losses of a branch from node j to node i PG l, i , QG l, i active and reactive power outputs of the lth DG located at ith bus V i voltage magnitude of the bus i V i s square of voltage magnitude of the bus i SW j, i branch status (OPEN/CLOSED) of the line connecting node j to node i XW j, i binary variable which is equal to 1 if i is an upstream (parent) node connected to j LC l binary variable that takes a value of 1 if the lth DG is connected to the ith bus

A General Methodology For Distribution Planning Under Uncertainty, Including Genetic Algorithms And Fuzzy Models In A Multi-Criteria Environment

1995

This paper presents a new comprehensive methodology based on genetic algorithms and fuzzy sets concepts for multistage electric distribution network planning. The model presented is an extension of previous deterministic developed models, taking in account several aspects usually neglected in other approaches like, for example, multiple criteria and a thorough representation of uncertainties. New concepts are developed, such as the tree of fuzzy futures, fuzzy inadequacy and solution robustness. Decisions are taken from a multicriteria approach and under risk analysis policies, namely by minimizing possible future regrets. The merits of the approach are discussed by analyzing its application to a study based on a real case, in a Portuguese utility EN, SA.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation

PloS one, 2016

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. T...

Risk based optimization for strategical planning of electrical distribution systems with dispersed generation

2003 IEEE Bologna Power Tech Conference Proceedings,, 2000

Strategical planning for electrical distribution systems is a difficult multi-objective optimisation problem. The formulation adopted in this paper also includes an overloading risk index, which considers the possibility that the obtained solution may not meet the posed technical constraints. The inherent uncertainty of the considered problem, due to the existence of LV dispersed generation units such as microturbines or photovoltaic generators, is taken into account by means of a Fuzzy formulation of the load density. In presence of Dispersed Generation, the load density in extended sense also includes the DG units contribution. The solution of this Multiobjective Optimisation, MO, problem has been carried out by means of a Non-dominated Sorting Genetic Algorithm-based approach. Distribution systems design using modular strategical planning indeed requires the minimisation/maximisation of many objects depending on mixed-integer variables. In this paper the concept of modularity has been used in the formulation of the strategical planning of electrical distribution systems. Different scenarios for the DG units penetration has been considered and the obtained results show many innovative and rational design solutions with different costs and risk indices.