Risk-Constrained Coordination of Cascaded Hydro Units With Variable Wind Power Generation

Abreu, Lisias; Khodayar, Mohammad E.; Shahidehpour, M.; Wu, Lei

doi:10.1109/tste.2012.2186322

Cited by 81 publications

(49 citation statements)

References 22 publications

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“…The imbalance charge is imposed on the WGenCO to balance energy in the power system due to deviation of the RTM [4,6,7]. The WGenCO's payoff in this method is as follows:…”

Section: A Conventional Systemsmentioning

confidence: 99%

“…The authors in [4] and [7] proposed a scheduling strategy for the coordination of wind and storage units without any flexibility for the WGenCO to adapt when the storage units fail.…”

Section: B Wgenco With the Energy Storage Systemmentioning

confidence: 99%

“…Conventional Systems The objective function (9) is to maximize the revenue from selling the day-ahead wind energy minus the cost of energy imbalance [4,6,7]. The intra-hour based wind power deviation between real-time and day-ahead schedules is in (10), and generation limits are given in (11)- (12).…”

Section: Mathematical Model Formulationmentioning

confidence: 99%

“…Both wind generation uncertainty, and energy price fluctuations are contributing factors to the decrease of the competitiveness of wind generating companies (WGenCOs) in the energy market [4]. In addition, the current market structure does not usually allow WGenCOs to serve loads directly and there is no coordination between them and distribution companies serving customer loads [5].…”

Section: Introductionmentioning

confidence: 99%

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Energy Exchange Between Electric Vehicle Load and Wind Generating Utilities

Tavakoli

Negnevitsky

Nguyen³

et al. 2016

IEEE Trans. Power Syst.

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This paper proposes a novel approach to energy exchange between electric vehicle (EV) load and wind generation utilities participating in the day-ahead energy, balancing, and regulation markets. An optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. A new strategy model is based on optimizing decision making of a wind generating company (WGenCO) in selecting the best option among the use of the balancing or regulation services, the use of the energy storage system (ESS) and the use of all of them to compensate wind power deviation. Energy imbalance is discussed using conventional systems, ESS, and EV-Wind coordination; results are compared and analyzed. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MILP). Uncertainties associated with wind forecasting, energy price, and behavior of EV owners based on their driving patterns, are considered in the proposed stochastic method and validated through several case studies. Abstract-This paper proposes a novel approach to energy exchange between electric vehicle (EV) load and wind generation utilities participating in the day-ahead energy, balancing, and regulation markets. An optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. A new strategy model is based on optimizing decision making of a wind generating company (WGenCO) in selecting the best option among the use of the balancing or regulation services, the use of the energy storage system (ESS) and the use of all of them to compensate wind power deviation. Energy imbalance is discussed using conventional systems, ESS, and EV-Wind coordination; results are compared and analyzed. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MILP). Uncertainties associated with wind forecasting, energy price, and behavior of EV owners based on their driving patterns, are considered in the proposed stochastic method and validated through several case studies.Index Terms-Electricity market, energy exchange, electric vehicles, energy storage, stochastic optimization. NOMENCLATURE Indices

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“…The imbalance charge is imposed on the WGenCO to balance energy in the power system due to deviation of the RTM [4,6,7]. The WGenCO's payoff in this method is as follows:…”

Section: A Conventional Systemsmentioning

confidence: 99%

“…The authors in [4] and [7] proposed a scheduling strategy for the coordination of wind and storage units without any flexibility for the WGenCO to adapt when the storage units fail.…”

Section: B Wgenco With the Energy Storage Systemmentioning

confidence: 99%

Section: Mathematical Model Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Energy Exchange Between Electric Vehicle Load and Wind Generating Utilities

Tavakoli

Negnevitsky

Nguyen³

et al. 2016

IEEE Trans. Power Syst.

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“…Based on the credibility theory, the traditional deterministic system constraint is transformed into fuzzy chance constraints, and dynamic economic dispatch model following that is established, which includes several fuzzy parameters at the multi-time scale. In the paper [4], the stochastic programming is used to reflect the probability of wind power. The unit commitment problem is described as a two-stage stochastic programming model with chance constraints, so a mixed sampling average approximation algorithm is carried out to solve it.…”

Section: Introductionmentioning

confidence: 99%

Multi-time Scale Joint Scheduling Method Considering the Grid of Renewable Energy

Zhijun

Wang

Cao

et al. 2018

IOP Conf. Ser.: Earth Environ. Sci.

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Abstract. Renewable new energy power generation prediction error like wind and light, brings difficulties to dispatch the power system. In this paper, a multi-time scale robust scheduling method is set to solve this problem. It reduces the impact of clean energy prediction bias to the power grid by using multi-time scale (day-ahead, intraday, real time) and coordinating the dispatching power output of various power supplies such as hydropower, thermal power, wind power, gas power and. The method adopts the robust scheduling method to ensure the robustness of the scheduling scheme. By calculating the cost of the abandon wind and the load, it transforms the robustness into the risk cost and optimizes the optimal uncertainty set for the smallest integrative costs. The validity of the method is verified by simulation. IntroductionWind power, photovoltaic, small hydropower and other renewable energy output power is susceptible to climate, altitude, topography, temperature and other natural factors, so has randomness and volatility. Currently under the condition of satisfying the safe operation, renewable energy adopts full internet access to stabilize its output fluctuations by thermal power, larger hydropower and other conventional power. However, the adjustment capacity of conventional power is limited. When the deviation between the output of renewable energy and forecast value is large, system active power is imbalance and trend is overload. And there will be abandon wind, abandon light, abandon water etc. In the field of operation control, it has been a point that how to improve renewable energy consumptive through the multi-time scale joint dispatch of renewable energy [1].In the paper [2], based on the difference in corresponding adjustment ability of power grid and wind power error at different time scales, a multi-time scale coordinated flexible load response scheduling model of "multi-level coordination, step-by-step refinement" is set to divide the whole process into dayahead plan (24h), intraday 4h rolling plan and real-time 15min plan and automatic power generation control. In the paper [3], wind power and load prediction value are expressed by fuzzy parameters. Based on the credibility theory, the traditional deterministic system constraint is transformed into fuzzy chance constraints, and dynamic economic dispatch model following that is established, which includes several fuzzy parameters at the multi-time scale. In the paper [4], the stochastic programming is used to reflect the probability of wind power. The unit commitment problem is described as a two-stage stochastic

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Multi‐objective optimization of integrated gas–electricity energy system based on improved multi‐object cuckoo algorithm

Yang

2021

Energy Science & Engineering

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With the depletion of sources of primary energy across the world, the prospect of a global energy crisis in the near future has raised considerable concern. Among the many sources of clean energy, wind energy is considered to be the most effective means of sustainable and environmentally friendly energy. Traditional systems of energy based on oil and natural gas still operate in a discrete manner, and the promise offered by the mutual coordination between energy systems to draw complementary benefits has not yet been fully exploited. This has prompted all energy sectors to examine the optimal integration of interconnected gas–electricity energy systems. In this context, this study proposes a multi‐objective collaborative operational optimization model of P2G for an interconnected, integrated gas–electricity energy system in case of uncertain wind power. Based on the effect of carbon capture by using P2G, the effect of coupling gas and electricity, and the cost of low‐capacity reserves, the authors use conditional risk values to design four targets of optimization—the operating cost of the system, rate of consumption of the natural gas system, total carbon emissions and capacity stand‐by cost—according to the power system, natural gas system, thermal energy system, and their elements of coupling from multiple perspectives to clarify the constraints on the model. Moreover, to reduce the likelihood of the optimal solution falling into the local optimum, the improved cuckoo algorithm is used to optimize the multi‐objective scheduling model. The authors used a 10‐node power system and a six‐node natural gas system as examples for simulation to verify the proposed model. The results of empirical analysis show the following: (a) Once the P2G equipment had been connected, it reduced the total operating cost and improved the consumption of wind power of the natural gas system regardless of whether backup services were provided. (b) The P2G equipment could be combined with gas‐fired CHP units to “cut peaks and fill valleys” in the electrical load of the power system. These results verify the effectiveness of the proposed multi‐objective optimal dispatch model of an interconnected gas–electricity energy system.

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Risk-Constrained Coordination of Cascaded Hydro Units With Variable Wind Power Generation

Cited by 81 publications

References 22 publications

Energy Exchange Between Electric Vehicle Load and Wind Generating Utilities

Energy Exchange Between Electric Vehicle Load and Wind Generating Utilities

Multi-time Scale Joint Scheduling Method Considering the Grid of Renewable Energy

Multi‐objective optimization of integrated gas–electricity energy system based on improved multi‐object cuckoo algorithm

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