Multi-objective planning of Distributed Energy Resources with probabilistic constraints (original) (raw)
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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.
Renewable Energy, 2016
With the increasing share of renewable energy sources (RES) in demand supply, the distribution network operators (DNOs) are facing with new challenges. In one hand, it is desirable to increase the ability of the network in absorbing more renewable power generation units (or increasing the hosting capacity (HC)). On the other hand, power injection to the distribution network by renewable resources may increase the active power losses (if not properly allocated) which reduces the efficiency of the network. Thus, the DNO should make a balance between these two incommensurate objective functions. The Demand Response (DR) in context of smart grids can be used by DNO to facilitate this action. This paper provides an approach in which a multi-objective and multi-period NLP optimization model is formulated where the DR is utilized as an effective tool to increase HC and decrease the energy losses simultaneously. In order to quantify the benefits of the proposed method, it is applied on a 69-bus distribution network. The numerical results substantiate that the proposed approach gives optimal locations and capacity of RES, as well as minimum energy losses by load shifting capability provided via DR programs.
Sustainability
Renewable energy-based distributed generators are widely embedded into distribution systems for several economical, technical, and environmental tasks. The main concern related to the renewable-based distributed generators, especially photovoltaic and wind turbine generators, is the continuous variations in their output powers due to variations in solar irradiance and wind speed, which leads to uncertainties in the power system. Therefore, the uncertainties of these resources should be considered for feasible planning. The main innovation of this paper is that it proposes an efficient stochastic framework for the optimal planning of distribution systems with optimal inclusion of renewable-based distributed generators, considering the uncertainties of load demands and the output powers of the distributed generators. The proposed stochastic framework depends upon the scenario-based method for modeling the uncertainties in distribution systems. In this framework, a multi-objective func...
A General Analysis of the Distributed Generation Impact on Electrical Energy Planning
2018 53rd International Universities Power Engineering Conference (UPEC), 2018
This study analyzes the perspective of the increasing participation of distributed generation (DG) in power systems, and its impact on electrical energy planning. To evaluate the effects of DG, this study presents the results of simulations involving a distribution network where some of the consumers, randomly chosen, are small producers of electrical energy, denominated prosumers. Some scenarios are analyzed, in which the prosumers adopt different levels of photovoltaic and/or wind DG, and in each one the annual reductions of the substation energy consumption and energy losses in lines and transformers are measured. Besides these benefits, the voltage violations in each scenario, caused by the DG, are also computed. The network model is based on the IEEE 8500-Node Test Feeder, and the simulations are performed using the open-source Open Distribution System Simulator (OpenDSS).
2019
This paper presents an approach for assessing the benefit of island operation of variable distributed generation (DG) in improving reliability in radial distribution networks. The proposed approach employs the risk-based procedure to obtain the best network automation scenario in the presence of variability of loads and variability and uncertainty of distribution generation. The automation scenario defines the number, type and location of automation devices to be allocated in the network to enable optimal creation of islands and thus to minimize the expected reliability cost. This cost consists of the cost of interruptions to customers and the cost of automation devices. By varying the level of variability and uncertainty of DG production different automation scenarios and corresponding reliability costs are obtained using the risk procedure. Based on these results the value of island operation of DGs in improving reliability in radial distribution networks is assessed.
10.38IJISRT24JUN1130, 2024
The distribution system has been paying more and more attention to distributed generation (DGUs) since a few years ago. The main causes of (DGUs) in distribution systems are increased electric demand, a deregulated energy market, and a congested transmission network. These factors ultimately lead to a decline in system performance. There's also an increasing push to cut greenhouse gas emissions. Proper placement and dimensioning are crucial for efficient utilization of DGUs. The system's current performance will be deteriorated and losses would increase due to improper DGUs location and size. However, optimal placement will reduce power loss, increase voltage stability, and maintain a consistent voltage profile in the distribution system. This paper reviews DGUs, the technical developments in DGUs, and several optimisation methods for the optimal placement problem. and size.