An optimisation algorithm for distributed energy resources management in micro-scale energy hubs

Roldán-Blay, Carlos; Escrivá-Escrivá, Guillermo; Roldán-Porta, Carlos; Álvarez-Bel, Carlos

doi:10.1016/j.energy.2017.05.038

Cited by 46 publications

(19 citation statements)

References 20 publications

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“…Likewise, it is observed that the installed power PV peak must be increased to values between 6 and 8 kW in order to obtain a LOLP around 2%. Comparing to the initial deterministic design (PV peak = 4 kW and Q b = 35 kWh are shown as circled points in Figures 12 and 13), this means that it is more convenient to increase PV peak and slightly reduce Q b (to a value of [25][26][27][28][29][30]. This type of design is the only one that can guarantee continuity in the supply, based on statistical values.…”

Section: Discussionmentioning

confidence: 99%

“…Another factor that influences the applicability of simulation results is the temporal resolution of the PV generation and load demand. At least an hourly resolution is required to reflect the power balance between PV generation and energy demand [30][31][32]. Some authors [1] propose smaller temporal resolutions (10-min sampled data) in order to evaluate energy flows between PV units, batteries, and loads.…”

Section: Introductionmentioning

confidence: 99%

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Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

et al. 2020

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In rural areas or in isolated communities in developing countries it is increasingly common to install micro-renewable sources, such as photovoltaic (PV) systems, by residential consumers without access to the utility distribution network. The reliability of the supply provided by these stand-alone generators is a key issue when designing the PV system. The proper system sizing for a minimum level of reliability avoids unacceptable continuity of supply (undersized system) and unnecessary costs (oversized system). This paper presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level. The proposed method is based on the application of a sequential random Monte Carlo simulation to the system model. Uncertainties of solar radiation, energy demand, and component failures are simultaneously considered. The results of the case study facilitate the sizing of the main energy elements (solar panels and battery) depending on the required level of reliability, taking into account the uncertainties that affect this type of facility. The analysis carried out demonstrates that deterministic designs of SAPV systems based on average demand and radiation values or the average number of consecutive cloudy days can lead to inadequate levels of continuity of supply.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

et al. 2020

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“…The EV aggregator will be only in charge of managing the EVs charge while the SO will be in charge of the operation of renewable generation. It could be also considered that the EV aggregator will be in interaction with residential customers' aggregators, which will manage energy hubs as buildings [46]. The EV aggregator will have to define a daily EV electricity cost curve when a new day starts, based on the forecasts.…”

Section: Methodsmentioning

confidence: 99%

Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation

2018

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Inhabited islands depend primarily on fossil fuels for electricity generation and they also present frequently a vehicle fleet, which result in a significant environmental problem. To address this, several governments are investing in the integration of Renewable Energy Sources (RESs) and Electric Vehicles (EVs), but the combined integration of them creates challenges to the operation of these isolated grid systems. Thus, the aim of this paper is to propose an Electric Vehicle charging strategy considering high penetration of RES. The methodology proposes taxing CO2 emissions based on high pricing when the electricity is mostly generated by fossil fuels, and low pricing when there is a RES power excess. The Smart charging methodology for EV optimizes the total costs. Nine scenarios with different installed capacity of solar and wind power generation are evaluated and compared to cases of uncoordinated charging. The methodology was simulated in the Galapagos Islands, which is an archipelago of Ecuador, and recognized by the United Nations Educational, Scientific and Cultural Organization (UNESCO) as both aWorld Heritage site and a biosphere reserve. Simulations results demonstrate that the EV aggregator could reduce costs: 7.9% for a case of 5 MW installed capacity (wind and PV each), and 7% for a case of 10 MW installed (wind and PV each). Moreover, the use of excess of RES power for EV charging will considerably reduce CO2 emissions

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“…This case study focuses on verifying the effectiveness of the proposed DDC algorithm by comparing it to the centralized algorithm [30]. The power and heat load demands for each power and heat load are initialized at 150 kW and 140 kW, respectively.…”

Section: Comparison With Centralized Algorithmmentioning

confidence: 99%

Double-Consensus Based Distributed Optimal Energy Management for Multiple Energy Hubs

Zhou

et al. 2018

Applied Sciences

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This paper presents a novel distributed double-consensus algorithm to solve the optimal energy management problem for multiple energy hubs interconnected with each other. The objective is achieved by establishing two interactive and paralleled consensus procedures modified by their corresponding feedback terms. Meanwhile, a novel projection operation method is proposed to map the infeasible values into the feasible operating region. The proposed algorithm can effectively handle the coupled variables problem existing in the objective function and constraint limits. Moreover, the optimality and convergence analysis are performed strictly under strong connectivity conditions only. Simulations performed on standard test cases are provided to illustrate the effectiveness of the proposed distributed algorithm.

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An optimisation algorithm for distributed energy resources management in micro-scale energy hubs

Cited by 46 publications

References 20 publications

Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability

Electric Vehicle Charging Strategy for Isolated Systems with High Penetration of Renewable Generation

Double-Consensus Based Distributed Optimal Energy Management for Multiple Energy Hubs

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