136 research outputs found
Towards Net Zero Energy Buildings: building performance optimization, simulation and analysis
The European Union 2020 energy targets seems to be a progressive, however, it still needs to be worked upon. The implementation of Nearly Zero Energy Buildings (nZEBs) as the building target represents one of the biggest challenges to increase energy savings and minimize greenhouse gas emissions. In this paper detached house has been modelled using dynamic simulation tool and the energy efficiency measures, concerning different technologies for envelope systems and technical systems, were set up as parameters in dynamic simulation tool and simulated and analysed. The objective of this paper is to define the heating, cooling, and electricity demand of a residential building in a cold climate region. The façade parameters were optimized for the best possible energy performance, to be used as design guidelines for facades in low and nearly zero energy buildings for architects and engineers. The purpose of the study is to give guidelines of office buildings facade design from the perspective of energy-efficiency and daylighting to architects, engineers, real-estate developers, etc.Peer reviewe
Role of polygeneration in sustainable energy system development : Challenges and opportunities from optimization viewpoints
A sustainable energy system can be treated as a development of the distributed generation concept. It meets energy demands locally from renewable energy or/and high-efficiency polygeneration production technologies, and is characterized by energy and cost efficiency, reliability, and environmental-friendliness.Distributed energy systems typically use renewable energy resources to supply all energy demands, such as heat, cooling, and electric power in an integrated way. However, it seems that too much emphasis is placed on power and associated renewable energy-based power technologies for dealing with sustainability issues in public discussion and the research community. Often, equally important thermal energy (heat and cooling) and polygeneration are ignored. Polygeneration is an energy- efficient technology for generating simultaneously heat and power as well as other energy products in a single integrated process. Energy efficiency contributes significantly to CO2 emission reduction. This paper discusses the role of polygeneration in a distributed energy system and the contributions of polygeneration to the development of sustainable energy systems. The paper also stresses that efficient decision support tools for sustainable polygeneration systems are important to achieve sustainability. First, the joint characteristic of a polygeneration plant that defines the dependency between different energy products is reviewed. Then, typical methods for dealing with polygeneration systems are reviewed. The review attempts to highlight the complexity of polygeneration systems and potential of polygeneration systems to adjust output of different energy products. Next, the challenges of sustainable polygeneration energy systems are discussed. Then some practices for operating polygeneration plants are discussed.Peer reviewe
An efficient algorithm for bi-objective combined heat and power production planning under the emission trading scheme
The growing environmental awareness and the apparent conflicts between economic and environmental objectives turn energy planning problems naturally into multi-objective optimization problems. In the current study, mixed fuel combustion is considered as an option to achieve tradeoff between economic objective (associated with fuel cost) and emission objective (measured in CO2 emission cost according to fuels and emission allowance price) because a fuel with higher emissions is usually cheaper than one with lower emissions. Combined heat and power (CHP) production is an important high-efficiency technology to promote under the emission trading scheme. In CHP production, the production planning of both commodities must be done in coordination. A long-term planning problem decomposes into thousands of hourly subproblems. In this paper, a bi-objective multi-period linear programming CHP planning model is presented first. Then, an efficient specialized merging algorithm for constructing the exact Pareto frontier (PF) of the problem is presented. The algorithm is theoretically and empirically compared against a modified dichotomic search algorithm. The efficiency and effectiveness of the algorithm is justified.Peer reviewe
Role of polygeneration in sustainable energy system development challenges and opportunities from optimization viewpoints
Implementing stochastic multicriteria acceptability analysis
Stochastic multicriteria acceptability analysis (SMAA) is a family of methods for aiding multicriteria group decision making in problems with inaccurate, uncertain, or missing information. These methods are based on exploring the weight space in order to describe the preferences that make each alternative the most preferred one, or that would give a certain rank for a specific alternative. The main results of the analysis are rank acceptability indices, central weight vectors and confidence factors for different alternatives. The rank acceptability indices describe the variety of different preferences resulting in a certain rank for an alternative, the central weight vectors represent the typical preferences favouring each alternative, and the confidence factors measure whether the criteria measurements are sufficiently accurate for making an informed decision.http://www.sciencedirect.com/science/article/B6VCT-4JRM07X-1/1/519bb7e11536f8bb8582526f0b25b76
Fuzzy chance constrained linear programming model for scrap charge optimization in steel production
Optimization of renewable energy for buildings with energy storages and 15-minute power balance
Funding Information: This research has been funded, in part, by the Academy of Finland, project 298317. We thank Granlund Oy, Helen Ltd. and Mr. Tarmo Kor?tko from Tallinn Technical University for providing us data. Funding Information: This research has been funded, in part, by the Academy of Finland , project 298317 . We thank Granlund Oy, Helen Ltd., and Mr. Tarmo Korõtko from Tallinn Technical University for providing us data. Publisher Copyright: © 2021 The AuthorsWhen planning renewable hybrid energy solutions in buildings, it is important to consider both investment and operating costs. This study develops a novel building optimization model based on the coming 15 min power balance settlement. It utilizes multiple energy storages, including hot water tank and flow and lead-acid batteries. We apply the model to plan the retrofitting of an office building in Helsinki and a residential building in Tallinn, with photovoltaics and a ground source heat pump. The model is a large dynamic linear or mixed-integer linear programming model (LP/MILP) for an entire year. The results determine both the optimal dimensioning and the optimal operation of the different production and storage technologies for each building. The optimized configurations caused significant savings in energy costs for both buildings while reducing non-renewable primary energy consumption. Heat storage is highly cost-efficient, but power storages are not. Photovoltaics is cost-efficient in the Helsinki building but slightly unprofitable in the Tallinn building. Power and heat storages do not interact strongly, even in the presence of the ground source heat pump. The heat storage operates in concert with district heating and the ground source heat pump, while power storages operate together with photovoltaics and power trade.Peer reviewe
Explicit demand response potential in electric vehicle charging networks : Event-based simulation based on the multivariate copula procedure
Publisher Copyright: © 2022 The AuthorsThis paper proposes a novel combined event-based simulation model for assessing the explicit demand response potential of electric vehicle (EV) charging networks. The model utilizes different multivariate copulas in generation of realistic artificial charging events that effectively retain the complex dependency structures and parameter distributions of real data important for accurate demand response simulation. A deterministic model is used to estimate the maximal explicit demand response potential of individual charging events based on technical requirements of the frequency containment reserve for disturbance situations (FCR-D) market. The proposed model achieved a mean absolute percentage error (MAPE) of 3.27% when considering averaged daily dispatchable FCR-D potentials, and a MAPE of 4.65% in prediction of dispatchable FCR-D potential with one workweek of data. The results and methodology have been verified and validated with real life data and through comparison with a previous non-copula application for EV FCR profile estimation which it outperformed. The combined event-based simulation model can boost active participation of EVs in power network balancing and is suitable for use in various practical and theoretical applications.Peer reviewe
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