An optimum bidding strategy of CVPP by interval optimization

Hu, Jiakai; Liu, Yangyang; Jiang, Chuanwen

doi:10.1002/tee.22721

Cited by 4 publications

(6 citation statements)

References 23 publications

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“…In the DA stage, most researchers treat the DA market price as uncertain parameters. In other words, VPPs are assumed to be price takers due to the small capacity [6,[14][15][16][17]. Nevertheless, VPP has the potential to achieve higher profit by exercising market power, as VPP aggregates more DERs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this work, VPP is investigated, which integrates more DERs. In contrast with another interval optimization-based VPP research [17], VPP in this paper is the price maker, and network constraints are considered.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The mathematical proving process is based on fuzzy methodology. A more detailed introduction can be found in our previous work [17,32]. Research [30] first introduced this method in a study of coordinated dispatching of wind power and hydro power.…”

Section: Uncertainty Characterizaion By Interval Optimizationmentioning

confidence: 99%

“…Research [30] first introduced this method in a study of coordinated dispatching of wind power and hydro power. Research [17] investigated the price taker VPP's medium-term bidding strategy, representing UR and market price in interval numbers.…”

Section: Uncertainty Characterizaion By Interval Optimizationmentioning

confidence: 99%

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Short-Term Bidding Strategy for a Price-Maker Virtual Power Plant Based on Interval Optimization

Jiang

Liu

2019

Energies

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A virtual power plant is proposed to aggregate various distributed renewable resources with controllable resources to overcome the uncertainty and volatility of the renewables so as to improve market involvement. As the virtual power plant capacity becomes remarkable, it behaves as a strategic price maker rather than price taker in the market for higher profit. In this work, a two-stage bi-level bidding and scheduling model is proposed to study the virtual power plant strategic behaviors as a price maker. A mathematical problem with an equilibrium constraints-based method is applied to solve the problem by transforming the two level problem into a single level multi-integer linear problem. Considering the deficiency of computational burden and implausible assumptions of conventional stochastic optimization, we introduce interval numbers to represent the predicted output of uncertainty resources in a real-time stage. The pessimism degree-based method is utilized to order the preferences of profit intervals and tradeoff between expected profit and uncertainty. An imbalance cost mitigation mechanism is proposed in this pessimism degree-based interval optimization manner. Results show that the bidding price directly affects the cleared day ahead of the locational marginal price for higher profit. Interior conventional generators, energy storage and interruptible loads are comprehensively optimized to cover potential power shortage or profit from market. Moreover, controllable resources can decrease or even wipe out the uncertainty through the imbalance cost mitigation mechanism when the negative deviation charge is high. Finally, a sensitivity analysis reveals the effect of interval parameter setting upon optimization results. Moreover, a virtual power plant operator with a higher pessimism degree pursues higher profit with higher uncertainty.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Uncertainty Characterizaion By Interval Optimizationmentioning

confidence: 99%

Section: Uncertainty Characterizaion By Interval Optimizationmentioning

confidence: 99%

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Short-Term Bidding Strategy for a Price-Maker Virtual Power Plant Based on Interval Optimization

Jiang

Liu

2019

Energies

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“…Reference [5] proposed an economic rescheduling strategy using a medium of imbalanced price to reduce deviation losses and increase total profits in a VPP. Reference [6] indicated that the efficient operation of a microgrid connecting to the main grid was able to improve market involvement. Nevertheless, most existing researches only involve the power energy management in the electrical power system.…”

Section: Introductionmentioning

confidence: 99%

Dual Interval Optimization Based Trading Strategy for ESCO in Day-ahead Market with Bilateral Contracts

Tan

Wang

Jiang

2020

Journal of Modern Power Systems and Clean Energy

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Being capable of aggregating multiple energy resources, the energy service company (ESCO) has been regarded as a promising alternative for improving power system flexibility and facilitating the consumption of renewable resources in the electricity market. Considering the uncertain variables in day-ahead (DA) market trading, an ESCO can hardly determine their accurate probability distribution functions. Traditional interval optimization methods are used to process these uncertain variables without specific probability distribution functions. However, the lower and upper bounds of the intervals may change due to extreme weather conditions and other emergent events. Hence, a dual interval optimization based trading strategy (DIOTS) for ESCO in a DA market with bilateral contracts (BCs) is proposed. First, we transfer the dual interval optimization model into a simple model consisting of several interval optimization models. Then, a pessimistic preference ordering method is applied to solve the derived model. Case studies illustrating an actual test system corroborate the validity and the robustness of the proposed model, and also reveal that ECSO is critical in improving power system flexibility and facilitating the ability of absorbing renewable resources.

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