Global solution method for decentralised multi‐area SCUC and savings allocation based on MILP value functions

Zheng, Xiaodong; Chen, Haoyong; Xu, Yan; Shen, Feifan; Liang, Zipeng

doi:10.1049/iet-gtd.2020.0438

Cited by 4 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, the impact of power generation swapping value on generation cost evaluated as an important price signal in nonconvex market. 29 Reference 30 examined the impact of generation cost and congestion on electricity prices. Reference 31 considered LMP to be the result of the price behavior of the players on the supply side.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This can increase the jth LSE's LMP share index and amplify its market power compared to other players in the n t h bus. This surge can be calculated from Equation (29).…”

Section: The Market Power Index For Demand Sidementioning

confidence: 99%

“…However, if the generation cost assumed to be constant, the factors that influenced the electricity price setting are of particular importance. In this case, the impact of power generation swapping value on generation cost evaluated as an important price signal in nonconvex market 29 . Reference 30 examined the impact of generation cost and congestion on electricity prices.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Proposing new analytical price‐based market power and coalition indices based on LMP share in double‐sided power market

Saghravanian

Samadi

Hajiabadi

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

One of the strategic actions to gain more profit in the electricity market is to exercising market power as a leverage in exclusive situations. The main goal of this article is to assess load serving entities market power via self-action scramble by price-based indices as an application of the structural decomposition approach.In addition, the possibility of forming a beneficial coalition due to the cross interactions between players can be evaluated using the proposed indices. These coalitions may be occurred between two generation units, two load serving entities, or a generation unit and a load serving entity. The cumulative sharing impacts of one load serving entity on the locational marginal prices of all units owned by a GenCo is also defined as a new index. To achieve this goal, the first step is to extract the structural decomposition coefficients of market components consisting of suppliers, inelastic, and elastic loads, which determine the contribution of all players on the electricity price separately. In the second step, new structural indices to determine self/cross-share index of each player in the electricity price based on the contributing factors obtained from the decomposition process. So, it is possible for market operator to prioritize the potential of exercising market power and forming coalition with a price-based index for both-sides players. As well, it is important for market operators to explore the economic justification of relationships between players to prevent market deviation. The proposed approach is evaluated on the IEEE 24-bus system, and the results are discussed.List of Symbols and Abbreviations: SG, set of all generators; D, set of all demands; L, set of all transmission lines; N G :N G , set of upper and lower bounded generators; N G , set of marginal generation units; N D , set of all fully dispatch elastic loads; N D , set of all partial dispatch elastic loads; L cong , set of all congested lines; n, bus number; a i , intercept of bid function for generator i; b i , slope of bid function for unit i; c j , intercept of offer function for load j; d j , slope of offer function for load j; P max l , upper flow limits of line l; P max g , P min g , upper/lower active power limit of generators; P max e , P min e , upper/lower active power limit of LSEs; P inelastic j , the active power of jth inelastic load; P d , total dispatched active power consist of elastic and inelastic load; P frc , total forecasted active power load; P g i , the active power generated by ith unit; P ej , the active power of jth LSE; α l:i , power transmission distribution factor of line l with respect to node ith generator; α l:j , power transmission distribution factor of line l with respect to node jth load; λ, Lagrange multiplier of the equality constraint; μ max i , μ min i , Lagrange multiplier of maximum/minimum generation limits refer to ith unit; Γ max l , Γ min l , Lagrange multiplier of the upper/lower of line flow limits refer to lth transmission line; ω max n , ω min n , Lagrange multiplier o...

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…This can increase the jth LSE's LMP share index and amplify its market power compared to other players in the n t h bus. This surge can be calculated from Equation (29).…”

Section: The Market Power Index For Demand Sidementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Proposing new analytical price‐based market power and coalition indices based on LMP share in double‐sided power market

Saghravanian

Samadi

Hajiabadi

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…For multi-area DOPF problems with integer variables, relying on a subroutine of refining the convex hulls of the feasible regions of each subproblems, the D-ALR in [32] could converge to the optimal solution under mild conditions, but which may be intractable for large-scale problems. Zheng et al [42] proposed a new global solution method for the decentralised multi-area DOPF problem with integer variables based on the MILP value function of the problem. For multi-area DOPF with integer variables, heuristics or parameters tunings are usually needed to ensure the algorithms converge to a local optimum [43,44].…”

Section: Introductionmentioning

confidence: 99%

Regularised primal–dual interior‐point method for dynamic optimal power flow with block‐angular structures

Zhang

Jian

Yang

2020

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power

et al. 2021

View full text Add to dashboard Cite

Global solution method for decentralised multi‐area SCUC and savings allocation based on MILP value functions

Cited by 4 publications

References 33 publications

Proposing new analytical price‐based market power and coalition indices based on LMP share in double‐sided power market

Proposing new analytical price‐based market power and coalition indices based on LMP share in double‐sided power market

Regularised primal–dual interior‐point method for dynamic optimal power flow with block‐angular structures

Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power

Contact Info

Product

Resources

About