Abstract: This paper proposes an index for nodal market power detection in power market under Locational marginal pricing (LMP). This index is an ex-ante technique to detect the market power. More precisely, this criterion detects the potential of exercising market power regardless of detecting the actual market power. Also it is obvious that pricing and market clearing method affect the potential of exercising market power. Different potential of market power exists in different pricing methods. This index has been analyzed under LMP method which seems to be a desirable environment to exercise market power. In LMP method by load growth, in some determined load levels which is called Critical Load Levels (CLLs), Locational marginal prices have step change. This step change in Locational marginal prices causes step change in revenue and benefit of Gencos. So it is significant to detect the behavior of Gencos in the CLLs. The proposed criterion has been tested on constant system load and CLLs for two test system.

Locational marginal pricing (LMP) is arguably the most effective and commonly employed mechanism to provide the most reliable economic signal to market participants. Meanwhile, nodal prices depend on active power losses and transmission congestion which may be affected by harmonics pollution. In the conventional method, power system and loads are assumed linear and nodal prices are obtained by results of optimal power flow (OPF) at the power frequency. Harmonics lead to skin effect and increasing loss. Further, harmonic flowing in branches in a power network occupies transmission capacity. For providing more accurate signals to market participants and achieving more accurate nodal prices, harmonic effects on LMP are investigated and a framework is developed for LMP calculation in a harmonic polluted power system. In this framework, skin effect, losses, and congestion which can be arisen by harmonic pollution are modelled in optimal power flow (OPF) and are considered in LMP calculation. The proposed concept is implemented with 9-bus and 30-bus test systems while nodal price changes are also indicated.

Distribution Locational marginal pricing (DLMP) is an efficient approach to optimize the pricing of distribution systems. This paper focuses on DLMP to minimize losses within the distribution network. This approach can be strategically manipulated to adjust the profits for distributed generation (DG) owners and the distribution company. Furthermore, the paper employs the information gap decision theory (IGDT) method scenarios to model the uncertainty surrounding electricity market prices. By incorporating the risk-averse (RA) scenario, network operators can discern RA solutions and optimal outcomes derived from the algorithm. On the other hand, the risk-tolerance (RT) scenario helps identify riskier solutions, enabling appropriate decision-making based on whether the solutions are RA or risky in nature. To further enhance the quality of outcomes, this paper combines IGDT scenarios with the cheetah hunter optimization (CHO) algorithm to ensure the obtained results are both optimal and accurate. The proposed method’s performance is evaluated through simulations conducted on a 69-bus IEEE power network using the MATLAB software environment. The results obtained from this approach demonstrate its superior accuracy when compared to previous methodologies.

This paper presents a method to allocate the transmission network costs to users based on nodal pricing approach by regulating the nodal prices from the marginal point to the new point. Transmission nodal pricing based on marginal prices is not able to produce enough revenue to recover the total transmission network costs. However, according to the previous studies in this context, this method recovers only a portion of transmission costs. To solve this problem, in this paper a method is presented in which by considering the direction and amount of injected power in each node the marginal price is regulated to the new price, in such a way as the nodal pricing can recover the total transmission network costs. Also the proposed method is able to control the cost splitting between loads and generators in accordance with the pre-specified ratio. The proposed method is implemented on both IEEE 24-bus and 118-bus test systems and the obtained results are reported.

Expansion planning strategies in power systems have been seriously influenced by disintegration of these systems during the past decade. Transmission Expansion Planning (TEP) is one of the most important parts of expansion planning of power systems. In this paper, a new algorithm for TEP in these environments is presented. The method is based on probabilistic Locational marginal Price (LMP) considering electrical losses, transmission tariffs and transmission congestion costs.Incorporating modeling of reactive power and uncertainty of generation and load are other important features of the proposed algorithm.