Optimal Sizing of PV and BESS for a Smart Household Considering Different Price Mechanisms

Zhou, Lai; Zhang, Yongjun; Lin, Xing; Li, Canbing; Cai, Zexiang; Yang, Ping

doi:10.1109/access.2018.2845900

Cited by 129 publications

(58 citation statements)

References 30 publications

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“…Falling costs of BESS in recent years has encouraged combining PV with it to provide stable power supply. Both linear and nonlinear mixed integer programming (MIP) models have been used to optimize PV and BESS capacity [17][18][19][20][21][22]. Zhao et al [17] co-optimizes BESS and PV for microgrids and households.…”

Section: Literature Surveymentioning

confidence: 99%

“…Their analysis involves maximizing the life of the BESS. Zhou et al [18] also performs this cooptimization using a comprehensive nonlinear MIP (MINLP) model that considers alternative pricing schemes. Results from Zhou et al [18] indicate that economics of PV under a standard tariff policy is not attractive.…”

Section: Literature Surveymentioning

confidence: 99%

“…Zhou et al [18] also performs this cooptimization using a comprehensive nonlinear MIP (MINLP) model that considers alternative pricing schemes. Results from Zhou et al [18] indicate that economics of PV under a standard tariff policy is not attractive. However, it is economic to install a PV-only system under a stepwise power tariff, whereas the PV together with BESS can only be justified under a time-of-use and real-time-pricing tariff.…”

Section: Literature Surveymentioning

confidence: 99%

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Battery Storage for Resilient Homes

Chatterji

Bazilian

2020

IEEE Access

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Small-scale battery energy storage systems (BESS), especially for behind-the-meter applications, are still relatively expensive, but we show that it can be a potent solution to render homes resilient to storm related power outages. We present a stochastic programming model formulation to optimize PV/BESS explicitly accounting for resilience benefits these investments entail, over and above their ability to reduce cost of supply. The stochastic optimization considers uncertainties around storm related grid supply failures as well as variability of solar PV. The model includes an embedded Monte Carlo simulation module that considers storm related outage risks using climate model reanalysis data. It is a least-cost planning framework that optimizes selection of BESS, solar PV, grid supply, and diesel generator, from a homeowner's perspective. We present two case studies with low and high storm risks that demonstrate how different risk exposures can impact on the selection of alternative options to build resilience. Duals, or shadow prices, of demand-supply constraints from the model for both normal days and for storm related contingencies, provide interesting insights into the marginal cost of supply that can inform innovative pricing schemes to promote customer level resilience measures. The case study results reveal significant merits of BESS, in combination with PV, to enhance resilience. We find that in low-risk areas like Bethesda, MD, incremental PV and BESS required for a more resilient system can add $79 (4%) to expected annual electricity costs for a typical household, and a considerably higher $208 (10.6%) in Miami, FL which is at a much greater risk. These options are, however, 27% (in Bethesda) and 20% (in Florida) less expensive than the conventional solution of installing a diesel generator. These results provide insights into the value of BESS as part of a resilient and clean energy solution for households.

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Section: Literature Surveymentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

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Battery Storage for Resilient Homes

Chatterji

Bazilian

2020

IEEE Access

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“…They also have ESSs that considerably boost the efficiency of a power system. An ESS also reduces the total operating cost of a smart grid and saves a big part of the cost of fuel and maintenance [13]. Smart grids could be small-scale or large-scale systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties

2019

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In this paper, based on stochastic optimization methods, a technique for optimal sizing of battery energy storage systems (BESSs) under wind uncertainties is provided. Due to considerably greater penetration of renewable energy sources, BESSs are becoming vital elements in microgrids. Integrating renewable energy sources in a power system together with a BESS enhances the efficiency of the power system by enhancing its accessibility and decreasing its operating and maintenance costs. Furthermore, the microgrid-connected BESS should be optimally sized to provide the required energy and minimize total investment and operation expenses. A constrained optimization problem is solved using an optimization technique to optimize a storage system. This problem of optimization may be deterministic or probabilistic. In case of optimizing the size of a BESS connected to a system containing renewable energy sources, solving a probabilistic optimization problem is more effective because it is not possible to accurately determine the forecast of their output power. In this paper, using the stochastic programming technique to discover the optimum size of a BESS to connect to a grid-connected microgrid comprising wind power generation, a probabilistic optimization problem is solved. A comparison is then produced to demonstrate that solving the problem using stochastic programming provides better outcomes and to demonstrate that the reliability of the microgrid improves after it is connected to a storage system. The simulation findings demonstrate the efficacy of the optimum sizing methodology proposed.

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“…In research [9], a home energy management system including photovoltaic panels and battery energy storage system was investigated. The researchers have examined the following items: i) the effect of the electricity price mechanism using the time-of-use pricing (TOU), the real-time pricing (RTP), and the stepwise power tariff (SPT); ii) the impact of solar panels; and iii) the variability of solar panels in different seasons.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Residential Energy Management System in Smart Building Considering Fuel Cell and Phev’s

Poormoayed¹,

Hakimi²,

Saadatmandi³

et al. 2018

IJESG

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The increased greenhouse gas emissions and the global warming from fossil fuels to produce electrical power generation and transportation, they become the most critical concern of governments to find an alternative source to fossil fuels such as renewable energies like wind and solar; Additionally, transportation is one of the main sources of environmental pollution, to this end, PHEV grid is presented, but the widespread use of PHEV will be creating a significant load on the grid. For this reasons in this paper, a model for the optimal application of green house, was studied in 24 hours. Energy management issue is considered in zero energy buildings with solar hybrid power sources, fuel cell, electrolyzer, hydrogen tank, compressor, reformer, anaerobic reactors and converters as well as plug-in hybrid electric vehicle (PHEV) must be provided, designed and implemented. The green house serves bilateral energy exchange with the upstream distribution network and if the surplus energy provided, can be sold to the network. Daily house trashes use to decline the bioenvironmental contaminations and also heat of house and hot water is supplied using fuel cell heat and if necessary we should purchase gas from network. In order to optimize this house, an objective function is extracted and aggregation Swarm algorithm to minimizing costs was carried out using MATLAB program. Finally, optimal operation is presented for the green house and results have been analyzed.

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Optimal Sizing of PV and BESS for a Smart Household Considering Different Price Mechanisms

Cited by 129 publications

References 30 publications

Battery Storage for Resilient Homes

Battery Storage for Resilient Homes

Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties

Intelligent Residential Energy Management System in Smart Building Considering Fuel Cell and Phev’s

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