Optimization of energy production of a CHP plant with heat storage

Abdollahi, Elnaz; Wang, Haichao; Rinne, Samuli; Lahdelma, Risto

doi:10.1109/igesc.2014.7018636

Cited by 26 publications

(14 citation statements)

References 20 publications

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“…A control strategy for the economic optimal operation in a combined heat and power (CHP) system with renewable sources, including wind energy, photovoltaic and heat recovery boiler, is reported in [28]. Similar control strategies with linear programming models are analysed in [29,30] for optimising the operations in CHP systems and evaluating the benefit of using different sized storages.…”

Section: Current Control Approaches In Dhc Systemsmentioning

confidence: 99%

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

et al. 2019

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This paper presents a holistic innovative solution for the transformation of the current district heating and cooling systems to automated more efficient systems. A variety of technological advancements have been developed and integrated to support the effective energy management of future district heating and cooling sector. First, we identify and discuss the main challenges and needs that are in line with the EU objectives and policy expectations. We give an overview of the main parts that our solution consists of, with emphasis on the forecasting tools and an advanced control system that addresses unit commitment and economic load dispatch problems. The proposed control approach employs distributed and scalable optimisation algorithms for optimising the short-term operations of a district heating and cooling plant subject to technical constraints and uncertainties in the energy demand. To test the performance and validate the proposed control system, a district heating plant with multiple energy generation units and real-life heat load data were used. Simulation experiments were also used to evaluate the benefits of using thermal storage units in district heating systems. The results show that the proposed method could achieve significant cost savings when energy storage is employed. The proposed control strategy can be applied for both operating optimally district heating plants with storage and supporting investment planning for new storage units.

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Section: Current Control Approaches In Dhc Systemsmentioning

confidence: 99%

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

et al. 2019

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“…Project lifetime (Year) 7 Interest rate (%) 3.91 Demand growth rate (%) 2.5 Approximation error tolerance (%) 1 The project lifetime is assumed to be seven years, based on the lifespan of the electrical energy storage units [33]. The annual interest rate is considered to be 3.91% [34].…”

Section: Parameter Valuementioning

confidence: 99%

“…In the operation and planning of conventional energy systems, single energy sources are typically considered individually, though these sources have interdependencies [1]. In addition, as a result of economic and environmental concerns, energy systems tend to operate in a decentralized manner.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Energy System Expansion Planning Method Using a Linearized Load-Energy Curve: A Case Study in South Korea

Park

Kim

et al. 2017

Energies

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Multi-energy systems can integrate heat and electrical energy efficiently, using resources such as cogeneration. In order to meet energy demand cost-effectively in a multi-energy system, adopting appropriate energy resources at the right time is of great importance. In this paper, we propose an expansion planning method for a multi-energy system that supplies heat and electrical energy. The proposed approach formulates expansion planning as a mixed integer linear programming (MILP) problem. The objective is to minimize the sum of the annualized cost of the multi-energy system. The candidate resources that constitute the cost of the multi-energy system are fuel-based power generators, heat-only boilers, a combined heat and power (CHP) unit, energy storage resources, and a renewable electrical power source. We use a load-energy curve, instead of a load-duration curve, for constructing the optimization model, which is subsequently linearized using a Douglas-Peucker algorithm. The residual load-energy curve, for utilizing the renewable electrical power source, is also linearized. This study demonstrates the effectiveness of the proposed method through a comparison with a conventional linearization method. In addition, we evaluate the cost and planning schedules of different case studies, according to the configuration of resources in the multi-energy system.

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“…The pressures of the energy crisis and environmental pollution have prompted people to reflect on the existing energy consumption patterns and begin to study the comprehensive utilisation of various forms of energy such as electricity, gas, and heat [1]. In recent years, with the development of cogeneration technology and the deepening of the concept of energy interconnection [2–4], the coupling relationship between multi‐energy systems has gradually attracted attention [1, 5–7]. The coupling between multiple energy sources is reflected in all aspects of production and life [8].…”

Section: Introductionmentioning

confidence: 99%

Energy hub model for energy management in energy internet

Zhang

et al. 2019

J. eng.

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Optimization of energy production of a CHP plant with heat storage

Cited by 26 publications

References 20 publications

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

A Multi-Energy System Expansion Planning Method Using a Linearized Load-Energy Curve: A Case Study in South Korea

Energy hub model for energy management in energy internet

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