Valuation under uncertain energy prices and load demands of micro-CHP plants supplemented by optimally switched thermal energy storage

Díaz, Guzmán; Moreno, Blanca

doi:10.1016/j.apenergy.2016.05.075

Cited by 22 publications

(27 citation statements)

References 35 publications

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“…The ratio between the thermal and electrical requirements of the biorefinery case study is similar to the thermal and electrical power that can be provided by the CHP technology as declared in the technical data sheets of the technology [30]. …”

Section: Possible Energy Recovery Strategiesmentioning

confidence: 73%

Energy Opportunities from Lignocellulosic Biomass for a Biorefinery Case Study

et al. 2016

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This work presents some energy considerations concerning a biorefinery case study that has been carried out by the CRB/CIRIAF of the University of Perugia. The biorefinery is the case study of the BIT3G project, a national funded research project, and it uses the lignocellulosic biomass that is available in the territory as input materials for biochemical purposes, such as cardoon and carthamus. The whole plant is composed of several sections: the cardoon and carthamus seed milling, the oil refinement facilities, and the production section of some high quality biochemicals, i.e., bio-oils and fatty acids. The main goal of the research is to demonstrate energy autonomy of the latter section of the biorefinery, while only recovering energy from the residues resulting from the collection of the biomass. To this aim, this work presents the quantification of the energy requirements to be supplied to the considered biorefinery section, the mass flow, and the energy and chemical characterization of the biomass. Afterwards, some sustainability strategies have been qualitatively investigated in order to identify the best one to be used in this case study; the combined heat and power (CHP) technology. Two scenarios have been defined and presented: the first with 6 MWt thermal input and 1.2 MWe electrical power as an output and the second with 9 MWt thermal input and 1.8 MWe electrical power as an output. The first scenario showed that 11,000 tons of residual biomass could ensure the annual production of about 34,000 MWht, equal to about the 72% of the requirements, and about 9600 MWhe, equal to approximately 60% of the electricity demand. The second scenario showed that 18,000 tons of the residual biomass could ensure the total annual production of about 56,000 MWht, corresponding to more than 100% of the requirements, and about 14,400 MWhe, equal to approximately 90% of the electricity demand. In addition, the CO 2 emissions from the energy valorization section have been quantified and the possibility of re-using the CO 2 flow in order to produce methane is described.

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Section: Possible Energy Recovery Strategiesmentioning

confidence: 73%

Energy Opportunities from Lignocellulosic Biomass for a Biorefinery Case Study

et al. 2016

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“…Previous works have been undertaken on modeling high-level system design for MG to study its profitability and optimal technology selection and sizings [17,15,12,5,18,13,9]. The average long-run operational and real options valuation have been typically considered in [19,18,13] to examine the economy of MG with a diverse combination of CHP, boilers, chillers, electric battery, thermal storage, solar panels, and wind turbines. Though these works lent insights into the modeling of MG, the simplicity of the treatment of the uncertain variables, such as electricity price and renewables, becomes a disadvantage for daily operational planning.…”

Section: Related Workmentioning

confidence: 99%

“…The dispatch of MG is, in essence, a unit commitment (UC) problem, which refers to optimizing generation resources over a short time horizon to satisfy load demand at minimum operational cost while satisfying prevailing constraints [20,17]. Diverse approaches have been pursued based on linear programming (LP) [21], mixed integer linear programming (MILP) [22,10,23], dynamic programming [24,12,13], simulated annealing [3], artificial neural networks [25], particle swarm optimization [18], hybrid methods [26] and evolutionary algorithms [27,5], as well as game theoretic agent-based formulations [7]. Mohamed and Koivo [28] presented a generalized multi-objective optimization for maintenance cost and emission reduction of an MG based on game theory.…”

Section: Related Workmentioning

confidence: 99%

“…A MG can be either connected to other MGs and/or the main grid for energy exchange, or run in island mode as circumstances or economics dictate [3,9,10,11,8]. The efficiency and environmental benefits also arise from the adoption of combined heat and power (CHP) by reusing the generator's waste heat to simultaneously provide electrical and thermal energy [9,12,13]. On the other hand, active demand response (DR), defined as "changes in electric usage implemented directly or indirectly by end-use customers / prosumers from their current consumption / injection patterns in response to certain signals" [6], has been put forward and implemented to lower peak energy usage and utility bills, and, at the same time, bring higher capacity factor and security of distribution grids [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Microgrid to enable optimal distributed energy retail and end-user demand response

et al. 2018

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In the face of unprecedented challenges of upcoming fossil fuel shortage and reliability and security of the grid, there is an upward tendency to adopt distributed, renewable, energy resources, as in microgrids (MGs), and engage flexible electric loads in power system operations to potentially drive a paradigm shift in the energy production and consumption patterns. Prior works on MG dispatch have been leveraging decentralized technologies like combined heat and power (CHP) and heat pumps to promote efficiency and economic gains; however, the flexibility of demands has yet to be fully exploited in cooperation with the grid to offer added benefits and ancillary services. The object of the study is to develop the microgrid optimal dispatch with demand response (MOD-DR), which fills in the gap by coordinating both the demand and supply sides in a renewable-penetrated, storage-augmented, DR-enabled MG to achieve economically viable and system-wide resilient solutions. The key contribution is the formulation of a multi-objective optimization with prevailing constraints and utility tradeoff based on the model of a large-scale MG with flexible loads, which leads to the derivation of strategies that incorporate uncertainty in scheduling. Evaluation using real datasets is conducted to analyze the uncertainty effects and demand response potentials, demonstrating in a campus prototype a 17.5% of peak load reduction and 8.8% cost savings for MOD-DR compared to the non-trivial baseline, which is on par with the Oracle with perfect predictions.

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“…One solution for integrating fluctuating renewable electricity supplies into industrial production is by using small and medium-sized combined heat and power plants (Andersen and Lund, 2007;Lund et al, 2015), together with thermal energy storage systems that reduce the cost of operating of the combined heat and power plants (Díaz and Moreno, 2016).…”

Section: Accepted Manuscriptmentioning

confidence: 99%