Multistage Generation and Network Expansion Planning in Distribution Systems Considering Uncertainty and Reliability

Muñoz-Delgado, Gregorio; Contreras, Javier; Arroyo, José M.

doi:10.1109/tpwrs.2015.2503604

Cited by 173 publications

(96 citation statements)

References 28 publications

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“…Authors in [23], [25] and [26] provide a solution for the multistage expansion planning problem considering renewable generation and correlation. Authors in [24] enhance the previous approach including topological changes. [25], [26] …”

Section: Literature Review and Contributionsmentioning

confidence: 99%

“…The annual pattern is repeated for every block considered in the formulation, being therefore the probability of each scenario in every stage constant. The approach proposed in the present formulation enhances [23] and [24] in order to adequately integrate time-dependent resources in the expansion planning. The modelling of uncertainty in a distribution system for each single load block is based on the load, wind and solar irradiation curves.…”

Section: Uncertainty Modelingmentioning

confidence: 99%

“…The proposed formulation is based on the work in [17]. However, when DR is integrated in the expansion planning model, the minimization of costs partially disregard the benefits consumers receive from the modification of their electricity consumption [24]. The objective function (1) has been modified to maximize the net social welfare or benefit (NSB) of the system and represents the present value of the total payment of the consumers minus the present value of the total cost, which consists of five terms: (2) investment, (3) maintenance, (4) production, (5) unserved energy and (6) storage.…”

Section: Problem Formulationmentioning

confidence: 99%

See 2 more Smart Citations

Joint Distribution Network and Renewable Energy Expansion Planning Considering Demand Response and Energy Storage—Part I: Stochastic Programming Model

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Quevedo

Muñoz-Delgado

et al. 2018

IEEE Trans. Smart Grid

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194

107

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The first part of this two-paper series describes the incorporation of Demand Response (DR) and Energy Storage Systems (ESS) in the joint distribution and generation expansion planning for isolated systems. The role of DR and ESS has recently attracted an increasing interest in power systems. However, previous models have not been completely adapted in order to treat DR and ESS on an equal footing. The model presented includes DR and ESS in the planning of insular distribution systems. Hence, this paper presents a novel model to decide the joint expansion planning of Distributed Generation (DG) and the distribution network considering the impact of ESS and price-dependent DR programs. The problem is formulated as a stochastic-programming-based model driven by the maximization of the net social benefit. The associated deterministic equivalent is formulated as a mixed-integer linear program suitable for commercially available software. The outcomes of the model are the location and size of new generation and storage units and the distribution assets to be installed, reinforced or replaced. In the second companion paper, an insular case study (La Graciosa, Canary Islands, Spain) is provided illustrating the effects of DR and ESS on social welfare.

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Section: Literature Review and Contributionsmentioning

confidence: 99%

Section: Uncertainty Modelingmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Joint Distribution Network and Renewable Energy Expansion Planning Considering Demand Response and Energy Storage—Part I: Stochastic Programming Model

Asensio

Quevedo

Muñoz-Delgado

et al. 2018

IEEE Trans. Smart Grid

Self Cite

194

107

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“…In the quest for improving economic efficiency and promoting sustainable development, electric power industries have experienced major changes in the regulatory structure over the last few decades [1][2][3][4][5][6][7]. Regarding the generation expansion planning (GEP) and operation decisions by generation companies (GENCOs), the issue of profitability is critical in terms of strategies offered to the market (short-term) and the generation capacity expansion (long-term) [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO2 Emissions

et al. 2019

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According to the European Union Emissions Trading Scheme, energy system planners are encouraged to consider the effects of greenhouse gases such as CO 2 in their short-term and long-term planning. A decrease in the carbon emissions produced by the power plant will result in a tax decrease. In view of this, the Dynamic carbon-constrained Equilibrium programming equilibrium constraints (DCC-EPEC) Framework is suggested to explore the effects of distinct market models on generation development planning (GEP) on electricity markets over a multi-period horizon. The investment incentives included in our model are the firm contract and capacity payment. The investment issue, which is regarded as a set of dominant producers in the oligopolistic market, is developed as an EPEC optimization problem to reduce carbon emissions. In the suggested DCC-EPEC model, the sum of the carbon emission tax and true social welfare are assumed as the objective function. Investment decisions and the strategic behavior of producers are included at the first level so as to maximize the overall profit of the investor over the scheduling period. The second-level issue is market-clearing, which is resolved by an independent system operator (ISO) to maximize social welfare. A real power network, as a case study, is provided to assess the suggested carbon-constrained EPEC framework. Simulations indicate that firm contracts and capacity payments can initiate the capacity expansion of different technologies to improve the long-term stability of the electricity market.

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“…Reference [31] established stochastic wind speed and load model, incorporating the model in the proposed multi-configuration multi-scenario market-based optimal power flow, to achieve satisfied active distribution networks planning solution. Based on a large amount of historical data analysis, stochastic output is abstracted into multiple scenarios with their probability of occurrence, and then substituted it into multi-objective planning model [32,33]. Reference [34] put forward a dynamic fuzzy interactive approach for expansion planning in a long term period.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Credible Capacity for Intermittent Distributed Energy Resources in Active Distribution Network

et al. 2017

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Abstract:The irregularity and randomness of distributed energy sources' (DERs) output power characteristic usually brings difficulties for grid analysis. In order to reliably and deterministically evaluate intermittent distributed generation's active power output, a credible capacity index for active distribution network (ADN) is proposed. According to the definition, it is a certain interval that the stochastic active power output of DERs may fall in with larger probability in all kinds of possible dynamic and time varying operation scenarios. Based on the description and analysis on the time varying scenarios, multiple scenarios considered dynamic power flow method for and are proposed. The method to calculate and evaluate credible capacity based on dynamic power flow (DPF) result is illustrated. A study case of an active distribution network with DERs integrated and containing 32 nodes is selected; multiple operation scenarios with various fractal dimension are established and used. Results of calculated credible capacity based on several groups of scenarios have been analyzed, giving the variance analysis of groups of credible capacity values. A deterministic value with the maximum occurrence probability representing credible capacity is given. Based on the same network case, an application of credible capacity to grid extension planning is given, which contributes to expenditure and cost reduction. The effectiveness and significance of the proposed credible capacity and solution method have been demonstrated and verified.

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Multistage Generation and Network Expansion Planning in Distribution Systems Considering Uncertainty and Reliability

Cited by 173 publications

References 28 publications

Joint Distribution Network and Renewable Energy Expansion Planning Considering Demand Response and Energy Storage—Part I: Stochastic Programming Model

Joint Distribution Network and Renewable Energy Expansion Planning Considering Demand Response and Energy Storage—Part I: Stochastic Programming Model

Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO2 Emissions

Assessment of Credible Capacity for Intermittent Distributed Energy Resources in Active Distribution Network

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