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Decision Area of Distributed Generation Investment as Deferral Option in Industrial Distribution System Using Real Option Valuation
Abstract
Distribution system planning (DSP) aims to ensure, that the electricity distribution can satisfy the demand in an optimum way. It has to provide the necessary economical, reliable, and secure electricity to consumer. Network solutions of DSP are the solutions that need adding and/or replacing some network asset. Traditional response is a large investment that creates large capacity. Therefore there may be unused capacity for period years. Thus, there is excess system capacity after the investment is made. In other hand, the alternative responses frequently install distributed generation in very small size. Original plan can be deferred by installing distributed generation. Investment using distributed generation is an option to defer the larger investment in distribution planning. Utility can use this option to face the uncertainty in demand projection. This paper proposes model for determining decision area of distributed generation investment as deferral option in industrial distribution system planning. It uses real option valuation to define the boundary by using the critical value. This study depicts the decision area by ‘discount rate’-‘electricity price on transmission’ and ‘discount rate’-‘delaying time’ boundary. © 2016, School of Electrical Engineering and Informatics. All rights reserved.
... The deferral option concatenated to the underlying asset modeled the implementation of the project, aiming to improve profitability by postponing the investment until, according to [93], the emergence of favorable market conditions. Essential in conducting uncertain scenarios, this option provides high quality in management decisions [94,95]. ...
Background: The commonly used methods for the financial evaluation of plantation forest investment projects do not incorporate uncertainties and ignore the value related to flexibility. The real options analysis makes it possible to capture these values in investment projects, increasing their value and return. Despite this, studies involving real options in forest investment projects are scarce, specifically those related to Pinus spp. Therefore, this study aimed to: (a) analyze whether the real options analysis adds value to investment projects of Pinus elliottii Engelm. plantations; and (b) make the real options analysis more accessible to forest managers and potentially increase its use in the investment projects of Pinus spp. plantations. Methods: We evaluated two investment projects in P. elliottii plantations in southern Brazil, which differed in the way of obtaining the land for planting: with lease or purchase of land on a planning horizon of 21 years. In the real options analysis, we used deferral, expansion, and abandonment. Results: Individually, the deferral, expansion, and abandonment options add value to investment projects in Pinus elliottii plantations. The option to expand the forested area is one that adds the most value to the investment project with land lease. In the investment project with land purchase, it is abandonment. Conclusions: Investment projects in Pinus elliotti plantations that contemplate the land purchase analyzed through the real options analysis present higher financial returns than those that consider land lease, inverting the result provided by the traditional analysis.
... Coordination of protection device has been done in presence of DG in [41]. Optimal reconfiguration has been presented considering the DG in [42]. Authors in [43], have introduced an optimization method to allocated DGs in distribution system. ...
Optimal placement of Distributed Generation (DG) in the distribution network is a significant solution to resolve the power loss issue. Selection of the optimal locations and sizes of the DG is a practical problem and challenging job to achieve the minimum loss. In this work, the optimal location and appropriate size of the DGs have been found out to minimize the total active power loss of the distribution system with less penetration level of the DG considering of 24 hours duration. A modified search algorithm has been proposed in this paper which is capable to obtain the best solutions. Moreover, several reputed soft computing techniques have been applied to solve the problem and validate the optimal results. Technical aspects like energy losses have been minimized instead of power loss and practical factors like hourly basis solar output, wind generation and load variation have been considered to make this work more realistic. The solution techniques have been tested on the IEEE 33, IEEE 69 and 118 radial distribution test bus systems and results have been compared with recent literature. The quality of the results establishes the efficiency of the proposed modified algorithm to solve the optimal location and sizing problem with the effect of PV and wind power variation along with the variable load.
Technological advances in signal processing, electronics, embedded systems and neuroscience have allowed the design of devices that help physicians to better assess the evolution of neurological diseases. In this context, we are interested in the development of an intelligent system for the quantification of Parkinson’s disease (PD). In order to achieve this, the system contains two parts: a wireless sensor network and an embedded system. The wireless sensor network is used to measure motor defects of the patient; it is constituted of several nodes which communicate among themselves. These nodes are intelligent sensors; they contains accelerometers, EMG and blood pressure sensors to detect any malfunction of the patient’s motor activities. As regards to the embedded system, it allows analyzing the patient’s voice signal in order to extract a descriptor that characterizes PD. The network detects the patient’s posture and measures his or her tremors. The voice analysis system measures the degradation of the patient’s condition. The embedded system combines the three decisions using the Chair–Varshney rule. The data fusion between the sensor network and the embedded system, will quantify the disease to facilitate the diagnostic for the physician, while providing the ability to effectively assess the evolution of the patient’s health.
Efficient and well-timed investment in distributed generation (DG) in distribution networks in the electricity market environment presents a big challenge for distribution companies. In this study, a real option valuation framework is proposed to determine the optimal investment strategies for DG including the investment location, size, and timing. Within the proposed framework, the profit from investing in DG is modelled, where the benefits include the operation cost savings and capacity update deferral benefit compared with a no-DG-investment scenario over the study period. Future power demands and electricity prices are modelled as stochastic variables. The candidate DG investment plans are considered as multiple mutually exclusive options, and the corresponding managerial flexibility for seizing opportunities and mitigating risk of loss upon an unfavourable unfolding of future uncertainties is assessed with real option analysis using the extended least square Monte Carlo method. The distribution of future investment strategies and optimal initial investment threshold levels under various scenarios are analysed in a case study to demonstrate the characteristics of the proposed framework and methodology.
This paper presents a multi-population hybrid algorithm to solve the switches placement problem in distribution networks considering remote and manual switches. A genetic algorithm in conjunction with local search procedure is used. In the procedure, reliability index, remote–manual controlled switch and investment costs are considered. The problem is formulated as a multi-objective optimization problem to be solved trough of weighted sum method. This method obtains the optimal solution considering a priori articulation of preferences established by the decision maker in terms of an aggregating function which combines individual objective values into a single utility value. A 282-bus test system is presented, and the results are compared to the solution given by other techniques. The results confirm the efficiency of the proposed method which makes it promising to solve complex problems of switches placement in distribution feeders.
MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.
IntroductionTypes of Relay ConstructionOvercurrent ProtectionReclosers, Sectionalizers, and FusesDirectional ProtectionDifferential ProtectionThermal ProtectionOvervoltage Protection
Basic Objectives
Earthing Electric EquipmentSystem EarthingMV Earthing SystemsEarthing Systems in LV Distribution Networks
The distribution system is the final link between bulk power system and consumer end. A distinctive load flow solution method is used for analysis of the load flow of radial and weakly meshed network based on Kirchhoff’s Current Law (KCL) and KVL. This method has excellent convergence characteristics for both radial as well as weakly meshed structure and is based on bus injection to branch current and branch-current to bus-voltage matrix. The main contribution of the paper is: (i) an analysis has been carried out for a weekly mesh network considering number of loops addition and its impact on the losses, kW and kVAr requirements from a system, and voltage profile, (ii) different load models, realistic ZIP load model and load growth impact on losses, voltage profile, kVA and kVAr requirements, (iii) impact of addition of loops on losses, voltage profile, kVA and kVAr requirements from substation, and (iv) comparison of system performance with radial distribution system. Voltage stability is a major concern in planning and operation of power systems. This paper also includes identifying the closeness critical bus which is the most sensitive to the voltage collapse in radial distribution networks. Node having minimum value of voltage stability index is the most sensitive node. Voltage stability index values are computed for meshed network with number of loops added in the system. The results have been obtained for IEEE 33 and 69 bus test system. The results have also been obtained for radial distribution system for comparison.
Deregulation in the power system industry and invention of new technologies for producing electrical energy have led to innovations in distribution system planning (DSP). Distributed generation (DG) is one of the most attractive technologies that brings different kinds of advantages to a wide range of entities, engaged in power systems. In this paper, a new model for considering DGs in the DSP problem is presented. In this model, an optimal power flow (OPF) is proposed to minimize capital costs for network upgrading, operation and maintenance costs, and the cost of losses for handling the load growth for the planning horizon. The term “dynamic” is used to refer to the planning over a specific period so that dynamic distribution system planning is, in fact, proposed. Besides, a modified genetic algorithm is used to find the optimal topology solution. The effectiveness of this method is demonstrated through examination on a radial distribution network.
This second part of a two-part paper presents the implementation and simulations of a risk-based optimization approach for distribution expansion planning with distributed generation (DG), as described in Part I. The proposed approach is first applied to a test system in order to test convergence of the optimization algorithm and then comparing its numerical results with the ones from the exhaustive method. Later, the expansion planning of a typical Latin American distribution network is assessed and analyzed. For this, two expansion optimizations are performed: one, taking into account traditional expansion alternatives (without DG) and, the other, considering DG as flexible expansion options. Finally, the computational effort is analyzed. Results show that the greatest contribution of DG lies in the flexibility it gives to expansion planning, mainly by deferring network reinforcements.
Investment in distributed generation (DG) is an attractive distribution planning option for adding flexibility to an expansion plan, mainly by deferring network reinforcements. In this first part of a two-part paper, a risk-based optimization approach is proposed to model a multistage distribution expansion planning problem that takes DG into account as a flexible option to temporarily defer large network investments. Five features of the installation of DG related to location, size, type, operation and timing are all optimized. The evolutionary particle swarm optimization (EPSO) method is applied to solve this mixed integer nonlinear problem. A return-per-risk index is proposed to assess expansion investments. This index achieves an efficient synergy between the expected return and the risk of investments by performing Monte Carlo simulations. In turn, the flexibility of network investment deferral is assessed through a real option valuation. Finally, in order to quantify the investment deferral benefit, the expected return from a traditional expansion plan (without DG) is compared to the return obtained from a flexible expansion plan (with DG). In the companion paper, the proposed approach is tested on a typical Latin American distribution network; implementation aspects and analysis of numerical results are presented.
The rise in installation/reinforcement and maintenance costs of power distribution systems enforces the planner to adopt an optimal strategy during system planning. The planning should be uch that the designed system should economically and reliably take care of spatial and temporal load growth, and service area expansion in the planning horizon. Mathematically, this planning is a multivariable multi-objective optimization problem. During the past decade or so, several planning algorithms have been developed. The purpose of this survey is to present a comprehensive review of all the developments in the planning technology, which includes all the reported optimization models and solution strategies. This state-of-the art survey is systematically organized to serve as a stepping stone for future researchers as well as a planning guide for the engineers. The various planning models are grouped in a three-level classification structure starting with two broad categories, i.e., planning without and with reliability considerations. The tree grows further with subdivisions. The last level of this classification tree consists of different planning models and solution strategies. Comprehensive discussions on each planning model are presented.
Distributed Generation: An Alternative to Electric Utility Investments in System Capacity
- T E Hoff
- H J Wenger
- B K Farmer
T. E. Hoff, H. J. Wenger, and B. K. Farmer, "Distributed Generation: An Alternative to
Electric Utility Investments in System Capacity,".
Indonesia 1976 and his DiplIng degrees in Electrical Power Engineering from Institut National Polytechnique de Toulouse, France in 1977, 1978 and 1981 respectively. He is currently working as lecturer in The School of Electrical Engineering and Informatics ITB
- Dea Ing
Yusra Sabri received his Sarjana (Bachelor) degree in Electrical Engineering
from Institut Teknologi Bandung (ITB), Indonesia 1976 and his Dipl.Ing,
DEA and DR.Ing degrees in Electrical Power Engineering from Institut
National Polytechnique de Toulouse, France in 1977, 1978 and 1981
respectively. He is currently working as lecturer in The School of Electrical
Engineering and Informatics ITB. His research interests are in Power and
Distribution System Planning.
On the Quantification of the Network Capacity Deferral Value of Distributed Generation
- H A Gil
- G Joss
H. A. Gil and G. Joss, "On the Quantification of the Network Capacity Deferral Value of
Distributed Generation," IEEE Transactions on Power System, vol. 21, no. 4, pp. 1592-1599, November 2006.
Real Option in Practice
- M A Brach
M. A. Brach, Real Option in Practice. Hoboken, New Jersey: John Wiley & Sons, Inc.,
2003.
Recent Advances on Power Distribution System Planning : a state of the art Survey
- N S A D S Gangguly
N. S. a. D. S.Gangguly, "Recent Advances on Power Distribution System Planning : a
state of the art Survey," Energy Syst, pp. 165-193, 2013.