A risk-based simulation and multi-objective optimization framework for the integration of distributed renewable generation and storage

Mena, Rodrigo; Hennebel, Martin; Li, Yan‐Fu; Ruiz, Carlos; Zio, Enrico

doi:10.1016/j.rser.2014.05.046

Cited by 81 publications

(54 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The noticeable numerical techniques addressed in the literature (Table 3) include; ε-constraint method [121,135,161]; second order cone programming [124]; lexicographic method [135]; MCS [122,139,157]; OPF [158]; integer programming [85]; graph theory [85,150]; penalty factor (funchion) method [130,140]; CCP [145,157]; compromise method [153]; ICSP [160]; linear programming (LP) [164] and non-linear programming (NLP) [152,160]. Moreover, goal programming (GOP), exhaustive search, sequential quadratic programming (SQP) and dynamic programming methods have sucessfully employed in conventional DN related planning problems [26].…”

Section: B Numerical Methodsmentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

View full text Add to dashboard Cite

Smart grids (SGs), as an emerging grid modernization concept, is spreading across diverse research areas for revolutionizing power systems. SGs realize new key concepts with intelligent technologies, maximizing achieved objectives and addressing critical issues that are limited in conventional grids. The SG modernization is more noticeable at the distribution grid level. Thus, the transformation of the traditional distribution network (DN) into an intelligent one, is a vital dimension of SG research. Since future DNs are expected to be interconnected in nature and operation, hence traditional planning methods and tools may no longer be applicable. In this paper, the smart distribution network (SDN) concept under the SG paradigm, has presented and reviewed from the planning perspective. Also, developments in the SDN planning process have been surveyed on the basis of SG package (SGP). The package presents a SDN planning foundation via major SG-enabling technologies (SGTF), anticipated functionalities (SGAF), new consumption models (MDC) as potential SDN candidates, associated policies and pilot projects and multi-objective planning (MOP) as a real-world optimization problem. In addition, the need for an aggregated SDN planning model has also been highlighted. The paper discusses recent notable related works, implementation activities, various issues/challenges and potential future research directions; all aiming at SDN planning.

show abstract

Section: B Numerical Methodsmentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

View full text Add to dashboard Cite

show abstract

“…In this section, a power distribution network is analyzed, under the Direct Current (DC) approximation (Purchala et al, 2005), in order to explore and discover possible critical scenarios (Mena et al, 2014). The network, represented in Fig.…”

Section: Conditional Expected Lofmentioning

confidence: 99%

“…the sequential training of the Kriging meta-model and the MCMC-based exploration. Demonstration is given with regards to a representative, critical infrastructure made by a power network of 10 nodes with time-variant demands (Mena et al, 2014). The response of the network is analyzed with respect to different failure scenarios characterized by 20 factors, including the failure times and magnitudes.…”

Section: Introductionmentioning

confidence: 99%

Simulation-based exploration of high-dimensional system models for identifying unexpected events

Turati

Pedroni

Zio

2017

Reliability Engineering & System Safety

Self Cite

View full text Add to dashboard Cite

. Simulation-based exploration of highdimensional system models for identifying unexpected events. Reliability Engineering and System Safety.http://dx.doi.org/10.1016/j.ress.2017.04.004Simulation-based exploration of high-dimensional system models for identifying unexpected events AbstractMathematical numerical models are increasingly employed to simulate system behavior and identify sequences of events or configurations of the system's design and operational parameters that can lead the system to extreme conditions (Critical Region, CR). However, when a numerical model is: i) computationally expensive, ii) high-dimensional, and iii) complex, these tasks become challenging.In this paper, we propose an adaptive framework for efficiently tackling this problem: i) a dimensionality reduction technique is employed for identifying the factors and variables that most affect the system behavior; ii) a meta-model is sequentially trained to replace the computationally expensive model with a computationally cheap one; iii) an adaptive exploration algorithm based on Markov Chain Monte Carlo is introduced for exploring the system state space using the meta-model; iv) clustering and other techniques for the visualization of high dimensional data (e.g., parallel coordinates plot) are employed to summarize the retrieved information.The method is employed to explore a power network model involving 20 inputs. The CRs are properly identified with a limited computational cost, compared to another exploration technique of literature (i.e., Latin Hypercube Sampling).

show abstract

“…According to the literature (see Li & Zio, 2012or Mena et al, 2014) the solar radiation is modeled with a β-distribution. Data were taken from the National Solar Radiation Database Wilcox (2012).…”

Section: Datamentioning

confidence: 99%

Financial Viability of Residential Photovoltaic and Battery Systems in Californias

Lehr¹,

Vrettos²,

Rajagopal³

et al. 2017

JMS

View full text Add to dashboard Cite

Using a battery on a household level has become easier after the launch of Tesla's Powerwall. Storing electricity during daytime's PV overproduction or charging the battery during night with an attractive tariff is the most prominent applications. This paper explores the economic impact of the usage of residential battery storage combined with solar photovoltaics (PV) based on real load data from Northern California, USA. A data-driven, deterministic model to benchmark electricity cost savings for single households is presented and the financial viability of such systems is scrutinized for California. Our results indicate that under current capacity and price points, battery systems have limited financial viability and have a payback period exceeding 20 years in most cases. We deepen our analysis and compare the results of our deterministic model to that of a stochastic model to demonstrate that for an hourly time resolution the deterministic model provides an adequate benchmark for estimating cost (within 3%) savings with a short (1/60th) computation time.

show abstract

A risk-based simulation and multi-objective optimization framework for the integration of distributed renewable generation and storage

Cited by 81 publications

References 64 publications

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Simulation-based exploration of high-dimensional system models for identifying unexpected events

Financial Viability of Residential Photovoltaic and Battery Systems in Californias

Contact Info

Product

Resources

About