Multi-objective optimization and comparison framework for the design of Distributed Energy Systems

Καρμέλλος, Μάριος; Mavrotas, George

doi:10.1016/j.enconman.2018.10.083

Cited by 103 publications

(27 citation statements)

References 22 publications

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“…A few words need to be said about the system's energy optimisation aspects. As far as the optimal design of distributed energy systems is concerned, elements such as annual costs or carbon emissions can be considered for drawing comparisons [63]. In addition, it becomes clear that there is plethora of methods and algorithms for the energy systems and their optimisation, but one needs to consider reliability, maintenance, as well as social aspects in optimization for making the system work [64].…”

Section: Economic Growth and Carbon-free Economymentioning

confidence: 99%

Innovative Policies for Energy Efficiency and the Use of Renewables in Households

Strielkowski¹,

Volkova

Pushkareva

et al. 2019

Energies

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Renewable energy sources (RES) are gradually becoming one of the key elements in the process of achieving energy efficiency worldwide. This trend can be observed in many developed Western economies—for example, in the United States, as well as in the United Kingdom. Hence, the role of innovative policies for promoting energy efficiency is becoming crucial in transition to the post-carbon economy. The shift to the carbon-free future make all actors to face forgoing commitments Nevertheless, customers and residential households are the first and the most important players in the pursuit of the energy-efficient future. Without them, carbon-free economy based on RES would never take the shape as envisaged. Our paper focuses on the innovative strategies and policies studying the effect and the scope of RES penetration into the households. We employ and empirical analysis of the effects from using RES in households using an example of the residential households in the northwest region of the United Kingdom (UK) with and without solar photovoltaic (PV) panels and electric vehicles (EV). We analyse the four scenarios that are aimed at analysing the system dynamics and providing differentiation between systems in terms of the varying values of the gross demand, tariffs, metered import, and the total revenue. Our results demonstrate that the solar PV leads to the transfer of costs and wealth regardless of the ownership of PV and EVs. Solar energy generation reduces the share of UK solar PV households per kWh costs of the distribution system which causes the augmenting of the per unit charges as well as to the changes in payments for the electricity that impoverishes less wealthy customer groups. It also becomes clear that with the increase of EV penetration, the existing energy efficiency schemes would have to be revised.

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Section: Economic Growth and Carbon-free Economymentioning

confidence: 99%

Innovative Policies for Energy Efficiency and the Use of Renewables in Households

Strielkowski¹,

Volkova

Pushkareva

et al. 2019

Energies

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“…This situation becomes clear when solar-based RETs are considered, such as photovoltaic panels and solar thermal collectors, because they consume an energy resource that has zero cost and zero emissions. Nevertheless, it is also interesting to analyze the various methods employed in the literature to determine the average CO 2 emission factors: the most common approach is to consider the electricity power mix of a region or a country, 31,[41][42][43][44][45][46] but Casisi et al 47 adopted the region's main thermoelectric plant, Wang et al 29 considered a coal power plant, and Conci et al 48 employed the average between the measured value in 2015 and the forecast value for 2050. Third, several studies disregard the effect of dynamic climatic conditions, such as hourly and seasonal variations in the ambient temperature and solar radiation, on the performance of solar-based RETs. 32 Second, to the best of the authors' knowledge, timebased electricity CO 2 emission factors have never been taken into account in energy systems optimization studies for buildings applications.…”

Section: Introductionmentioning

confidence: 99%

“…Even though it is true that sufficiently accurate data are difficult to obtain, all consulted energy systems optimization studies consider annual average values for the electricity CO 2 emissions, thus completely ignoring the dynamic interaction between the energy system and the electric grid as well as the potential benefits. Nevertheless, it is also interesting to analyze the various methods employed in the literature to determine the average CO 2 emission factors: the most common approach is to consider the electricity power mix of a region or a country, 31,[41][42][43][44][45][46] but Casisi et al 47 adopted the region's main thermoelectric plant, Wang et al 29 considered a coal power plant, and Conci et al 48 employed the average between the measured value in 2015 and the forecast value for 2050. Third, several studies disregard the effect of dynamic climatic conditions, such as hourly and seasonal variations in the ambient temperature and solar radiation, on the performance of solar-based RETs. A temporal and dynamic approach to the operation of solar-based RETs (eg, solar thermal collectors and photovoltaic panels) is needed to enhance the optimization procedure and the benefits that can be derived from their integration in energy systems.…”

Section: Introductionmentioning

confidence: 99%

A multiperiod multiobjective framework for the synthesis of trigeneration systems in tertiary sector buildings

2019

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This paper develops a multiperiod multiobjective optimization procedure to determine the optimal configuration and operational strategy of a trigeneration system assisted with solar-based technologies and thermal energy storage. The optimization model, formulated as mixed integer linear programming problem, incorporates dynamic operating conditions through time-dependent local climatic data, energy resources, energy demands, electricity prices, and electricity CO 2 emission factors. The methodology is applied to a case study of a residential building in Spain. First, the single-objective solutions are obtained, highlighting their fundamental differences regarding the installation of cogeneration (included in the optimal total annual cost solution) and solar-based technologies (included in the optimal total annual CO 2 emissions solution). Then, the Pareto curve is generated, and a decision-making approach is proposed to select the preferred trade-off solutions based on the marginal cost of CO 2 emissions saved. Additionally, sensitivity analyses are performed to investigate the influence of key parameters concerning energy resources prices, investment costs, and rooftop area. The analyses of the trade-off solutions verify the enormous potential for CO 2 emissions reduction, which can reach 32.3% with only 1.1% higher costs by displacing cogeneration in favor of the heat pump and the electric grid. Besides, with a modest cost increase of 7.3%, photovoltaic panels are incorporated, promoting an even greater CO 2 emissions reduction of 45.2%.

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“…References [13] and [14] present a new multistage and stochastic mathematical model, developed to support the decision making process of planning distribution network systems for integrating large-scale clean energy sources. A multi-objective mixed-integer linear programming framework is shown in [15], comparing two main methodologies of designing distributed energy systems using total annual cost and carbon emissions as objective functions. Reference [16] suggests novel cost and emission benefit allocation constraints inspired by cooperative Game theory to ensure that each involved building shares the benefit together.…”

Section: Introductionmentioning

confidence: 99%

Planning of Multi Energy-Type Micro Energy Grid Based on Improved Kriging Model

Liu

Lin

et al. 2019

IEEE Access

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The increasing complexities of multi energy-type micro energy grid (MEG) integrated with distributed renewable energy resources require more effective planning method. This paper presents an improved Kriging model for the planning of MEG to satisfy user's demands in cooling, heating, and electrical energy. First, a generic MEG model containing energy supply devices (combined cooling, heating, and power system, and energy storage systems) and energy supply networks is established. Second, the improved Kriging model combined with the Latin hypercube sampling method is proposed for searching the MEG optimal configuration to minimize the total annual cost. Third, for the sake of completeness and practicality, the sample points are updated by a novel mixed infill-sampling criterion comprised of minimum surrogatemodel point criterion, trust region criterion, and mean square error criterion. The optimal configuration and operation schemes are obtained simultaneously in the case study. Eventually, the numerical results indicate that the proposed method could efficiently solve the optimal planning problem in contradistinction to three other scenarios regarding the Kriging model. INDEX TERMS Micro energy grid, planning, Kriging model, trust region, optimal configuration.

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Multi-objective optimization and comparison framework for the design of Distributed Energy Systems

Cited by 103 publications

References 22 publications

Innovative Policies for Energy Efficiency and the Use of Renewables in Households

Innovative Policies for Energy Efficiency and the Use of Renewables in Households

A multiperiod multiobjective framework for the synthesis of trigeneration systems in tertiary sector buildings

Planning of Multi Energy-Type Micro Energy Grid Based on Improved Kriging Model

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