Coordination of combined heat and power-thermal-wind-photovoltaic units in economic load dispatch using chance-constrained and jointly distributed random variables methods

Azizipanah‐Abarghooee, Rasoul; Niknam, Taher; Bina, Mohammad Amin; Zare, Mohsen

doi:10.1016/j.energy.2014.10.024

Cited by 68 publications

(20 citation statements)

References 51 publications

(63 reference statements)

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“…For chance-constrained optimization, the constraints are formulated in probabilistic terms and thus decision-makers can know the likelihood of meeting the constraints [43]. In [44], Niknam et al proposed chance constrained programming to handle multi-objective economic load dispatch using a jointly distributed random variables method. For the two-stage stochastic programming method, the effects of decisions after uncertain variables are realized can be well represented.…”

Section: Methods For Handling Uncertaintiesmentioning

confidence: 99%

A comprehensive review of Energy Internet: basic concept, operation and planning methods, and research prospects

Cao

Tan

et al. 2017

J. Mod. Power Syst. Clean Energy

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With the intensifying energy crisis and environmental pollution, the Energy Internet and corresponding patterns of energy use have been attracting more and more attention. In this paper, the basic concept and characteristics of the Energy Internet are summarized, and its basic structural framework is analyzed in detail. On this basis, couplings between the electric power system and other systems such as the cooling and heating system, the natural gas system, and the traffic system are analyzed, and the operation and planning of integrated energy systems in both deterministic and uncertain environments are comprehensively reviewed. Finally, the research prospects and main technical challenges of the Energy Internet are discussed.

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Section: Methods For Handling Uncertaintiesmentioning

confidence: 99%

A comprehensive review of Energy Internet: basic concept, operation and planning methods, and research prospects

Cao

Tan

et al. 2017

J. Mod. Power Syst. Clean Energy

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show abstract

“…The time periods for operating these elastic loads can be determined by the time-of-use tariff, PV generation, a capacity contract, cost of the fuel of the micro-turbine generator and other operational constraints. The uncertainty of PV power output was addressed by many papers [21][22][23][24][25][26][27][28][29][30][31][32]. In this paper, the uncertainty of PV power is modeled using stochastic distributions.…”

Section: Introductionmentioning

confidence: 99%

Novel Genetic Algorithm-Based Energy Management in a Factory Power System Considering Uncertain Photovoltaic Energies

Hong

2017

Applied Sciences

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Abstract:The demand response and accommodation of different renewable energy resources are essential factors in a modern smart microgrid. This paper investigates the energy management related to the short-term (24 h) unit commitment and demand response in a factory power system with uncertain photovoltaic power generation. Elastic loads may be activated subject to their operation constraints in a manner determined by the electricity prices while inelastic loads are inflexibly fixed in each hour. The generation of power from photovoltaic arrays is modeled as a Gaussian distribution owing to its uncertainty. This problem is formulated as a stochastic mixed-integer optimization problem and solved using two levels of algorithms: the master level determines the optimal states of the units (e.g., micro-turbine generators) and elastic loads; and the slave level concerns optimal real power scheduling and power purchase/sale from/to the utility, subject to system operating constraints. This paper proposes two novel encoding schemes used in genetic algorithms on the master level; the point estimate method, incorporating the interior point algorithm, is used on the slave level. Various scenarios in a 30-bus factory power system are studied to reveal the applicability of the proposed method.

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“…For example, by using the strong complementary nature of wind energy and solar energy in time and region, wind power plants and solar power plants can form a hybrid power system that contributes to reducing the fluctuation of power output [5,6]. In addition, a wind-thermal hybrid system can ensure the stability of the system through relying on peak modulation and frequency modulation from thermal power plants [7]. At present, Xinjiang has started demonstration work of wind-solar-thermal combined generation and the transmitted renewable energy has reached one billion kWh [8].…”

Section: Introductionmentioning

confidence: 99%

Game-Based Generation Scheduling Optimization for Power Plants Considering Long-Distance Consumption of Wind-Solar-Thermal Hybrid Systems

Yuan

Sun

et al. 2017

Energies

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Abstract:With the increasing penetration of renewable energy in power systems, fluctuation of renewable energy power plants has great influence on stability of the system, and renewable power curtailment is also becoming more and more serious due to the insufficient consumptive ability of local power grid. In order to maximize the utilization of renewable energy, this paper focuses on the generation scheduling optimization for a wind-solar-thermal hybrid system considering that the produced energy will be transmitted over a long distance to satisfy the demands of the receiving end system through ultra-high voltage (UHV) transmission lines. Accordingly, a bilevel optimization based on a non-cooperative game method is proposed to maximize the profit of power plants in the hybrid system. Users in the receiving end system are at the lower level of the bilevel programming, and power plants in the transmitting end system are at the upper level. Competitive behavior among power plants is formulated as a non-cooperative game and the profit of power plant is scheduled by adjusting generation and bidding strategies in both day-ahead markets and intraday markets. In addition, generation cost, wheeling cost, and carbon emissions are all considered in the non-cooperative game model. Moreover, a distributed algorithm is presented to obtain the generalized Nash equilibrium solution, which realizes the optimization in terms of maximizing profit. Finally, several simulations are implemented and analyzed to verify the effectiveness of the proposed optimization method.

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Coordination of combined heat and power-thermal-wind-photovoltaic units in economic load dispatch using chance-constrained and jointly distributed random variables methods

Cited by 68 publications

References 51 publications

A comprehensive review of Energy Internet: basic concept, operation and planning methods, and research prospects

A comprehensive review of Energy Internet: basic concept, operation and planning methods, and research prospects

Novel Genetic Algorithm-Based Energy Management in a Factory Power System Considering Uncertain Photovoltaic Energies

Game-Based Generation Scheduling Optimization for Power Plants Considering Long-Distance Consumption of Wind-Solar-Thermal Hybrid Systems

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