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Strategic bidding of gas-fired units with tanks in coupled electricity and natural gas markets

SUSTAINABLE ENERGY GRIDS & NETWORKS 2023年 34卷

作者： Wu, Chenyu Wu, Zhi Yi, Zhongkai Yang, Lun Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Alibaba DAMO Acad Decis Intelligence Lab Beijing 100020 Peoples R China

With the increasing interdependence between the electricity and natural gas systems in economy and physics, this paper addresses the problem of developing optimal offering strategies in synchronized electricity-gas markets with step-wise energy offer formats. The gas-fired generators act as price makers in electricity markets and interruptible loads in the natural gas markets. The proposed model considers not only the impact of electricity clearing prices on gas bidding behaviors but also the influence of fuel cost variation on developing optimal electricity bidding curves. A price update method is proposed with the help of gas tanks to suppress price fluctuation. A two-stage trading mechanism is designed for gas-fired generators to optimize bids in electricity and gas markets via an iterative method. These bilinear terms in objectives and constraints are tackled by primal-dual equality conditions and binary expansion method. Then, the mathematical program with equilibrium constraints is converted to the mixed-integer linear program. The diagonalization algorithm is nested in the proposed trading mechanism if there are many leaders in the market instead of just one. Case studies validate the proposed methodology in detail. (c) 2023 Elsevier Ltd. All rights reserved.

关键词： Electricity market mathematical problem with equilibrium constraints Natural gas market Offering strategies

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Offering strategy of a price-maker virtual power plant in the day- ahead market

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY DEVELOPMENT-IJRED 2023年第4期12卷 666-+页

作者： Nguyen-Hong, Nhung Quang, Khai Bui Thanh, Long Phan Vo Huynh, Duc Bui Hanoi Univ Sci & Technol Sch Elect & Elect Engn Dept Elect Engn Hanoi Vietnam

With the rapid increase of renewable energy sources (RESs), the virtual power plant model (VPP) has been developed to integrate RESs, energy storage systems (ESSs), and local customers to overcome the RESs' disadvantages. When the VPP's capacity is large enough, it can participate in the electricity market as a price-maker instead of a price-taker to obtain a higher profit. This study proposes a bi-level optimization model to determine the optimal trading strategies of a price-maker VPP in the day-ahead (DA) market. The operation schedule of the components in the VPP is also optimized to achieve the highest profit for the VPP. In the bi-level optimization problem, the upper-level model is maximizing the VPP's profit while the lower-level model is the DA market-clearing problem. The bi-level optimization problem is formulated as a mathematical problem with equilibrium constraints (MPEC), reformulated to a Mixed Integer Linear problem (MILP), then solved by GAMS and CPLEX. This study applies the bi-level optimization model to a test VPP system, including wind plants (WP), solar plants (PV), biogas energy plants (BG), ESSs, and several customers. The maximum power outputs of WP and PV are 100MW and 90MW, respectively. The total installed capacity of BG is 70MW, while the ESS' rated capacity is 100MWh. The local customers have the highest total consumption of 100MW. In addition to the VPP, four GENCOs and three retailers participate in the DA market. The results show that the market-clearing price varies depending on the participants' production/consumption quantity and offering/bidding price. However, based on the optimization model, the VPP can take full advantage of WP and PV available power output, choose the right time to operate BG, then obtain the highest profit. The results also show that with the ESS' rated capacity of 100MWh, the ESS' rated discharging/charging power increased from 10MW to 50MW will increase VPP's profit from 45987$ to 49464$. The obtained res

关键词： Day-ahead market mathematical problem with equilibrium constraints mixed-integer linear programming price-maker renewable energy virtual power plants

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Joint Planning and Operation for Renewable- Storage Under Different Financial Incentives and Market Mechanisms

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IEEE ACCESS 2020年 8卷 13998-14012页

作者： Tian, Kunpeng Sun, Weiqing Han, Dong Yang, Ce Univ Shanghai Sci & Technol Dept Control Sci & Engn Shanghai 200093 Peoples R China Univ Shanghai Sci & Technol Dept Elect Engn Shanghai 200093 Peoples R China

In this paper, a novel joint planning framework is proposed to coordinate the investment and operation of renewable energy sources and energy storage systems (ESS) in energy and ancillary services markets. Based on this framework, coordinated planning and operation model under centralized and deregulated market mechanism is studied, and multiple factors such as siting and sizing of wind turbine and ESS, the efficiency of ESS, transmission lines constraints are considered. For the centralized market mechanism, the coordinated model aiming at maximizing social welfare is established, which is a tractable single-level optimization problem. For the deregulated market mechanism, the coordinated model aiming at maximizing investment profits is established, which is an intractable bi-level optimization problem as the locational marginal price in the objective function. The bi-level optimization problem is reformulated into a mathematical problem with equilibrium constraints by Karush-Kuhn-Tucker conditions. The big-M method and strong dual theory are used to deal with the nonlinearity in constraints and objective functions, and the problem is transformed into a mixed-integer linear programming, which can be solved by commercial software. Furthermore, the impact of production tax credit and investment tax credit financial incentive policies on investment behavior has been studied, and the evaluation indexes of electrical information and economy have been established. The proposed approach has been implemented on the IEEE 6-bus and the IEEE 30-bus test systems, and results justify the efficiency of the model proposed.

关键词： Investment and operation market mechanism mathematical problem with equilibrium constraints Karush-Kuhn-Tucker conditions financial incentive

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Nash equilibria in electricity pool markets with large-scale wind power integration

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ENERGY 2021年 228卷 120642-120642页

作者： Tsimopoulos, Evangelos G. Georgiadis, Michael C. Aristotle Univ Thessaloniki Sch Engn Dept Chem Engn POB 455 Thessaloniki 54124 Greece

This work investigates the interaction between power producers with conventional and wind generation portfolios participating in a network-constrained pool-based market. A stochastic bi-level problem is introduced to model the strategic behavior of each single producer. The upper-level problem maximizes the producers' expected profits and the lower-level problem optimizes the jointly cleared energy and balancing market under economic dispatch. Market participants' offers are modeled using linear stepwise curves, and the stochastic wind power generation is realized through a set of plausible wind scenarios. The bi-level problem is recast into a single-level mathematical problem with equilibrium constraints with primal-dual formulation using the Karush-Kuhn-Tacker first order optimality conditions and the strong duality theorem. The joint solution of all strategic producers' problems constitutes an equilibrium problem with equilibrium constraints. The latter is reduced into an equivalent mixed integer linear program by using disjunctive constraints. Different objective functions are applied to the final program to define the range of market equilibria, and a single-iterate diagonalization process is used to justify those equilibria that are meaningful. The model addresses several cases considering different types of market competition, transmission line congestions, and different levels of wind power penetration and volatility. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Primal-dual formulation Wind uncertainty Energy dispatch Reserve deployments Energy market Nash equilibria mathematical problem with equilibrium constraints

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Virtual storage plant offering strategy in the day-ahead electricity market

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 104卷 401-413页

作者： Pandzic, Kristina Pandzic, Hrvoje Kuzle, Igor Croatian Transmiss Syst Operator HOPS Ltd Zagreb Croatia Univ Zagreb Fac Elect Engn & Comp Dept Energy & Power Syst Zagreb Croatia

Energy storage is gaining an important role in modern power systems with high share of renewable energy sources. Specifically, large-scale battery storage units (BSUs) are an attractive solution due to their modularity, fast response and ongoing cost reduction. This paper aims to formulate, analyze and clarify the role of merchant-owned BSUs in the day-ahead electricity market. It defines virtual storage plant (VSP) as a set of BSUs distributed across the network. A VSP offering model is formulated as a bilevel program in which the upper-level problem represents the VSP profit maximization and operation, while the lower-level problem simulates market clearing and price formation. This mathematical problem with equilibrium constraints (MPEC) is converted into a mixed-integer linear program (MILP). This is afterwards expanded to a game of multiple VSPs formulating an equilibrium problem with equilibrium constraints (EPEC), which is solved using the diagonalization procedure. The proposed model is applied to an updated IEEE RTS-96 system. We evaluate the impact VSPs have on the locational marginal prices and compare the coordinated approach (all BSUs operated under a single VSP), i.e. the MPEC formulation, to the competitive approach (multiple VSPs competing for profit), i.e. the EPEC formulation.

关键词： Virtual storage plant Energy storage Bilevel programming mathematical problem with equilibrium constraints

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

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ENERGIES 2019年第19期12卷 3662-3662页

作者： Hu, Jiakai Jiang, Chuanwen Liu, Yangyang SJTU Minist Educ Key Lab Control Power Transmiss & Convers Shanghai 200240 Peoples R China Nantong Univ Sch Elect Engn Nantong 226000 Peoples R China

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.

关键词： virtual power plant interval optimization mathematical problem with equilibrium constraints

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