The Experts below are selected from a list of 7722 Experts worldwide ranked by ideXlab platform
Morten Boje Blarke - One of the best experts on this subject based on the ideXlab platform.
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SuperGrid or SmartGrid: Competing strategies for large-scale integration of Intermittent Renewables?
Energy Policy, 2013Co-Authors: Morten Boje Blarke, Bryan M. JenkinsAbstract:This paper defines and compares two strategies for integrating Intermittent Renewables: SuperGrid and SmartGrid. While conventional energy policy suggests that these strategies may be implemented alongside each other, the paper identifies significant technological and socio-economic conflicts of interest between the two.
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thermal battery with co2 compression heat pump techno economic optimization of a high efficiency smart grid option for buildings
Energy and Buildings, 2012Co-Authors: Morten Boje Blarke, Kazuaki Yazawa, Ali Shakouri, Carolina CarmoAbstract:Abstract Increasing penetration levels of wind and solar power in the energy system call for the development of Smart Grid enabling technologies. As an alternative to expensive electro-chemical and mechanical storage options, the thermal energy demand in buildings offers a cost-effective option for intermittency-friendly electricity consumption patterns. Combining hot and cold thermal storages with new high-pressure compressor technology that allows for flexible and simultaneous production of useful heat and cooling, the paper introduces and investigates the high-efficiency thermal battery (TB) concept. In a proof-of-concept case study, the TB replaces an existing electric resistance heater used for hot water production and an electric compressor used for air refrigeration in a central air conditioning system. A mathematical model for least-cost unit dispatch is developed. Heat pump cycle components and thermal storages are designed and optimized. A general methodology is applied that allows for comparing the obtained results with other Smart Grid enabling options. It is found that the TB concept leads to improvements in the intermittency-friendliness of operation Rc (improves from −0.11 to 0.46), lower CO2 emissions (reduced to zero), and lower operational costs (reduced by 72%). The results indicate that TB may be the most cost-effective Smart Grid enabling option for supporting higher penetration levels of Intermittent Renewables in the energy system.
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towards an intermittency friendly energy system comparing electric boilers and heat pumps in distributed cogeneration
Applied Energy, 2012Co-Authors: Morten Boje BlarkeAbstract:Distributed cogeneration has played a key role in the implementation of sustainable energy policies for three decades. However, increasing penetration levels of Intermittent Renewables is challenging that position. The paradigmatic case of West Denmark indicates that distributed operators are capitulating as wind power penetration levels are moving above 25%; some operators are retiring cogeneration units entirely, while other operators are making way for heat-only boilers. This development is jeopardizing the system-wide energy, economic, and environmental benefits that distributed cogeneration still has to offer.
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intermittency friendly and high efficiency cogeneration operational optimisation of cogeneration with compression heat pump flue gas heat recovery and intermediate cold storage
Energy, 2011Co-Authors: Morten Boje Blarke, Erik DotzauerAbstract:This paper develops, implements, and applies a mathematical model for economic unit dispatch for a novel cogeneration concept (CHP-HP-FG-CS (CHP with compression heat pump and cold storage using flue gas heat)) that increases the plant’s operational flexibility. The CHP-HP-FG-CS concept is a high-efficiency and widely applicable option in distributed cogeneration better supporting the co-existence between cogenerators and Intermittent Renewables in the energy system.
Carlo Mari - One of the best experts on this subject based on the ideXlab platform.
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Power system portfolio selection under uncertainty
Energy Systems, 2019Co-Authors: Carlo MariAbstract:We present a general methodology for power system portfolio selection under uncertainty in which fossil fuels and CO $$_2$$ 2 market prices as assumed as the main sources of risk. The planning problem is developed by considering the power system as a whole in its interactions between dispatchable sources and Intermittent Renewables, under load demand and power capacity constraints. The portfolio selection is performed taking into account costs and benefits of the power system from a societal perspective. Efficient frontiers and optimal generation portfolios are derived and discussed. Based on USA data, an empirical analysis is developed to illustrate the main features of this approach.
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Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach
Energies, 2018Co-Authors: Carlo Lucheroni, Carlo MariAbstract:We propose a system level approach to value the impact on costs of the integration of Intermittent renewable generation in a power system, based on expected breakeven cost and breakeven cost risk. To do this, we carefully reconsider the definition of Levelized Cost of Electricity (LCOE) when extended to non-dispatchable generation, by examining extra costs and gains originated by the costly management of random power injections. We are thus lead to define a ‘system LCOE’ as a system dependent LCOE that takes properly into account Intermittent generation. In order to include breakeven cost risk we further extend this deterministic approach to a stochastic setting, by introducing a ‘stochastic system LCOE’. This extension allows us to discuss the optimal integration of Intermittent Renewables from a broad, system level point of view. This paper thus aims to provide power producers and policy makers with a new methodological scheme, still based on the LCOE but which updates this valuation technique to current energy system configurations characterized by a large share of non-dispatchable production. Quantifying and optimizing the impact of Intermittent Renewables integration on power system costs, risk and CO 2 emissions, the proposed methodology can be used as powerful tool of analysis for assessing environmental and energy policies.
Yali Xue - One of the best experts on this subject based on the ideXlab platform.
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superheated steam temperature control based on modified active disturbance rejection control
Control Engineering Practice, 2019Co-Authors: Yali Xue, Li Sun, Liming SunAbstract:Abstract Control of superheated steam temperature (SST) is becoming more and more challenging because of unknown disturbances caused by the frequent and extensive load changes and strict control requirements for the efficiency and safety. This is becoming even severe while the Intermittent Renewables penetration is growing. To this end, the working principle of SST is depicted and the models of SST are identified from the open-loop step response data. Considering the sluggish responses to the disturbances caused by high order dynamics, a modified active disturbance rejection control (ADRC) is proposed to enhance the control performance. Stability analysis of modified ADRC is derived theoretically to perfect the theory of modified ADRC. Then a practical tuning procedure is summarized for modified ADRC that can be readily understood by field engineers even though it involves trial and error tests. A simulation example shows that modified ADRC can improve the performance of tracking and disturbance rejection simultaneously while maintain a good robustness. A modified ADRC based cascade control strategy is proposed for the SST control system and the control performance is initially confirmed by a simulation based on the identified models. A field application in a 300 MW circulating fluidized bed (CFB) power plant demonstrates the advantages of the proposed strategy, which shows the temperature deviation can be significantly reduced in both the small-scale load varying condition and the large-scale load varying condition. The successful application of the proposed SST control system indicates a promising future of modified ADRC in power industry with the increasing demand on integrating more Renewables into the power grid.
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multi objective optimization for advanced superheater steam temperature control in a 300 mw power plant
Applied Energy, 2017Co-Authors: Qingsong Hua, Yali Xue, Jiong She, Kwang Y LeeAbstract:Abstract Control of superheater steam temperature (SST) is critical for the safety and efficiency of the coal-fired power plant. However, the conventional cascaded PI controller is faced with great challenges in regulating the SST within a satisfactory range in the environment of extensive load changes, which is inevitably becoming even worse due to the growing integration of the Intermittent Renewables. To this end, this paper introduces advanced control and multi-objective optimization (MOO) to improve the SST control performance and thus to enable the load being quickly adjusted in a wider range. The inner-loop PI controller parameters are optimized based on the tracking and regulation performance objectives subject to a robustness constraint. The improvement of the outer-loop controller involves two steps, (i) the outer-loop PI controller is upgraded to active disturbance rejection controller (ADRC) in order to eliminate the sluggish response to the external load disturbances; (ii) a mathematical algorithm is developed to depict the stable region for the ADRC parameters, serving as the MOO search space. Comparative simulations show the advantage of the proposed strategy, which is confirmed by a field test in an in-service 300 MW power plant. It shows that the proposed strategy leads to a much smaller temperature deviation in both constant-load and load-varying conditions than the conventional control, making it less sensitive to the external disturbances. Furthermore, the load demand can be shifted more flexibly in a wide range (from 10 MW to 15 MW) while the SST is strictly confined within the allowable range, indicating a promising prospect of the proposed strategy in a power grid with high Renewables penetration.
Zhao Yang Dong - One of the best experts on this subject based on the ideXlab platform.
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optimal air conditioning load control in distribution network with Intermittent Renewables
Journal of Modern Power Systems and Clean Energy, 2017Co-Authors: Dongxiao Wang, Ke Meng, Xiaodan Gao, Colin Coates, Zhao Yang DongAbstract:The coordinated operation of controllable loads, such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, this paper proposes a MILP (mixed integer linear programming) based approach to schedule the interruptible air-conditioning loads. In order to mitigate the uncertainties of the stochastic variables including wind power generation, ambient temperature change, and electricity retail price, the rolling horizon optimization (RHO) strategy is employed to continuously update the real-time information and proceed the control window. Moreover, to ensure the thermal comfort of customers, a novel two-parameter thermal model is introduced to calculate the indoor temperature variation more precisely. Simulations on a five node radial distribution network validate the efficiency of the proposed method.
Kwang Y Lee - One of the best experts on this subject based on the ideXlab platform.
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multi objective optimization for advanced superheater steam temperature control in a 300 mw power plant
Applied Energy, 2017Co-Authors: Qingsong Hua, Yali Xue, Jiong She, Kwang Y LeeAbstract:Abstract Control of superheater steam temperature (SST) is critical for the safety and efficiency of the coal-fired power plant. However, the conventional cascaded PI controller is faced with great challenges in regulating the SST within a satisfactory range in the environment of extensive load changes, which is inevitably becoming even worse due to the growing integration of the Intermittent Renewables. To this end, this paper introduces advanced control and multi-objective optimization (MOO) to improve the SST control performance and thus to enable the load being quickly adjusted in a wider range. The inner-loop PI controller parameters are optimized based on the tracking and regulation performance objectives subject to a robustness constraint. The improvement of the outer-loop controller involves two steps, (i) the outer-loop PI controller is upgraded to active disturbance rejection controller (ADRC) in order to eliminate the sluggish response to the external load disturbances; (ii) a mathematical algorithm is developed to depict the stable region for the ADRC parameters, serving as the MOO search space. Comparative simulations show the advantage of the proposed strategy, which is confirmed by a field test in an in-service 300 MW power plant. It shows that the proposed strategy leads to a much smaller temperature deviation in both constant-load and load-varying conditions than the conventional control, making it less sensitive to the external disturbances. Furthermore, the load demand can be shifted more flexibly in a wide range (from 10 MW to 15 MW) while the SST is strictly confined within the allowable range, indicating a promising prospect of the proposed strategy in a power grid with high Renewables penetration.