Optimal Bidding, Scheduling, and Deployment of Battery Systems in California Day-Ahead Energy Market

Mohsenian‐Rad, Hamed

doi:10.1109/tpwrs.2015.2394355

Cited by 143 publications

(73 citation statements)

References 28 publications

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“…To verify the above statement, first, assume that r φ ij [t] = 1. In that case, from (27) and (30), one can conclude (28), while (31) is not binding. Next, assume that r φ ij [t] = 0.…”

Section: A Nonlinearity In Constraintsmentioning

confidence: 93%

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Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets

Mohsenian‐Rad

2016

IEEE Trans. Power Syst.

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148

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Abstract-In this paper, a new optimization framework is proposed to coordinate the operation of large, price-maker, and geographically dispersed energy storage / battery systems in a nodal transmission-constrained energy market. The energy storage units are assumed to be investor-owned and independentlyoperated, seeking to maximize their total profit. Various design factors are taken into consideration such as the location, size, efficiency, and charge and discharge rates of the energy storage units as well as the joint impact of the energy storage operations on the locational marginal prices. While the formulated optimization problem is originally nonlinear and hard to solve, nonlinearities are tackled both in the objective function and in the constraints and the problem is transformed into a tractable mixed-integer linear program, for which the global optimal solutions are found for the charge and discharge schedules of each energy storage unit. Both deterministic and stochastic design scenarios are addressed. Various case studies are presented. It is observed that transmission line congestion is often, but not always, desirable for the coordinated storage systems. Locational diversity, practice of arbitrage, robust design, self-scheduling versus economic bidding, and the overall power system performance are also investigated.

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“…To verify the above statement, first, assume that r φ ij [t] = 1. In that case, from (27) and (30), one can conclude (28), while (31) is not binding. Next, assume that r φ ij [t] = 0.…”

Section: A Nonlinearity In Constraintsmentioning

confidence: 93%

“…[34, p. 226], solving problem (6) is equivalent to solving the system of nonlinear equations in (7)- (27). Note that, the nonlinearity is due to the complementary slackness constraints in (16)- (23).…”

Section: A Nonlinearity In Constraintsmentioning

confidence: 99%

Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets

Mohsenian‐Rad

2016

IEEE Trans. Power Syst.

Self Cite

148

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“…Although several studies have been conducted in relation to market mechanisms for electricity networks with uncertainty, no market mechanism has so far been proposed for a regional network of prosumers that considers both the uncertainty and strong correlation described above [17], [30]- [32].…”

Section: Correlationmentioning

confidence: 99%

Risk-Limiting Real-Time Pricing for a Regional Prosumers' Electricity Network with Distributed Solar Power Generation

Kawasaki

Takata

Fukui

et al. 2017

SICE Journal of Control, Measurement, and System Integration

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: In this paper, we propose a novel risk-limiting real-time pricing mechanism for a regional electricity network of prosumers with distributed solar power generation. The target system is a regional electricity network that consists of many prosumers, each equipped with a battery and a renewable energy-based generator. In particular, we assume that each prosumer is in possession of a solar power generator, i.e., photovoltaic cells. In the proposed market mechanism, each prosumer sets an asking price and bids for the amount of electricity that he/she sells or buys, In addition, he/she sets an asking price and bids for a parameter to cope with the uncertainty induced by solar power generation in a dayahead market, as well. It is a characteristic of regional electricity networks of prosumers that there is a strong correlation in the solar power generation of each house within a network. A market mechanism for a regional electricity network of prosumers with distributed solar power generation should consider such characteristics. The performance of the proposed mechanism is demonstrated numerically through a simulation experiment. It outperformed a conventional realtime pricing method that does not consider uncertainty, and a method that does not involve trading of the parameter for coping with uncertainty.

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“…A large share of the existing PBUC work assumes perfect foresight of future prices and the storage plant to be small enough to be a price-taker in the considered market (e.g., [18][19][20][21][22][23]). Although quite some studies discuss a relaxation of the perfect price foresight assumption (e.g., [16,[24][25][26][27][28][29][30]), less attention has been given to the relaxation of the price-taking assumption in PBUC arbitrage models. However, either large-scale or multiple small-scale storage plants that are operated cooperatively could benefit from considering the price-effect of (dis)charge actions.…”

Section: Scope and Approachmentioning

confidence: 99%

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

Brijs

Geth

Siddiqui

et al. 2016

Journal of Energy Storage

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Electricity storage plants can be used for many applications, with one of the most studied applications being arbitrage in the day-ahead market. Terms of use: Documents inAlthough the arbitrage value is related to the presence of price spreads, it also depends on the effect of (dis)charge actions on prices, as arbitrage generally reduces price spreads by increasing off-peak prices when charging and decreasing peak prices when discharging. As such, there are two important assumptions in price-based unit commitment arbitrage models: first, whether the storage operator is assumed to have perfect knowledge of future prices, and second, whether they recognize that their (dis)charge actions may affect those prices, i.e., the price-taking or pricemaking assumption. This article proposes a comprehensive formulation of the arbitrage problem including detailed operating constraints, and focuses on relaxing the price-taking assumption by considering real-world price-effect data, published in the form of hourly piecewise linear relationships between quantity and price based on submitted bids, which are referred to as "market resilience functions". These can be used to (1) evaluate the price-taking and price-making assumptions based on simplified price-effects, and to (2) provide an upper limit to the arbitrage value under the assumption that prices and price-effects are known at the decision stage. In addition, a stepwise approximation to the piecewise linear functions is developed to reduce computation time, i.e., from mixed-integer nonconvex quadratic programming to mixed-integer linear programming, while providing lower-and upper bound approximations to the arbitrage value. The developed models are applied to the Belgian day-ahead market for 2014, and show that the price-effect has a strong impact on the operation and arbitrage value of large-scale storage.

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Optimal Bidding, Scheduling, and Deployment of Battery Systems in California Day-Ahead Energy Market

Cited by 143 publications

References 28 publications

Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets

Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets

Risk-Limiting Real-Time Pricing for a Regional Prosumers' Electricity Network with Distributed Solar Power Generation

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

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Optimal Bidding, Scheduling, and Deployment of Battery Systems in California Day-Ahead Energy Market

Cited by 143 publications

References 28 publications

Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets

Coordinated Price-Maker Operation of Large Energy Storage Units in Nodal Energy Markets

Risk-Limiting Real-Time Pricing for a Regional Prosumers&apos; Electricity Network with Distributed Solar Power Generation

Price-based unit commitment electricity storage arbitrage with piecewise linear price-effects

Contact Info

Product

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Risk-Limiting Real-Time Pricing for a Regional Prosumers' Electricity Network with Distributed Solar Power Generation