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This paper examines the impact of power transmission network topology change on locational marginal price (LMP) in real-time power markets. We consider the case where the false status of circuit breakers (CBs) that bypass topology error processing can generate an incorrect power system network topology, subsequently distorting the results of the state estimation and economic dispatch. The main goal of this paper is to assess the economic impact of this misconfigured network topology on real-time LMP in an entire power system with network congestion. To this end, we start with our prior result, a simple and analytical congestion price equation, which can be applied to any single line congestion scenario. This equation can be extended to better understand the degree to which the LMP at any bus changes due to any line status error. Furthermore, it enables a rigorous analysis of the relationship between the change in LMP at any bus with respect to any line error and various physical/economical grid conditions such as the bidding prices for marginal generators and the locations of the congested/erroneous lines. Numerical examples on the impact analysis of this topology error are illustrated in IEEE 14-bus and 118-bus systems.
A power system network topology provides information for managing and controlling physical and economical grid operations. The topological structure of an entire power network is a key input to solving core power system analysis problems such as state estimation, power flow, contingency analysis, and economic dispatch. Therefore, maintaining the correct topology information is of vital importance for reliable and efficient grid operations. The smart grid of the future will increasingly rely on data from fast sensing units such as phasor measurement units (PMUs) and smart meters in advanced metering infrastructures (AMIs). Therefore, unexpected data corruption will have severe impact on future grid operations. In particular, the corruption of data associated with power system network topology (e.g. the on/off status of circuit breakers (CBs)) could mislead system operators about the real-time topology conditions. As a result, the real-time market price, namely the locational marginal price (LMP), can be distorted because real-time LMP is calculated based on the network topology. This topology error due to data corruption can occur frequently in smart grid operations, which suggests the need for a more rigorous study on the impact of such errors on LMP.
An expansion of intermittent zero-marginal cost generation does not change the fundamentals of efficient electricity market design. Rather, it increases the importance of implementing the design and associated reforms that have been identified from market experience. These include improved scarcity pricing, demand participation, and carbon pricing.
Hence, the requirement was not to find a way to allow the market to discover an efficient dispatch. Rather, the challenge was to provide consistent real-time or spot prices that would support the efficient or economic dispatch coordinated by the system operator. The prices would reflect the locational differences in the marginal value of net generation. Under reasonable simplifying assumptions found in common practice, the solution amounted to determine what became known as locational marginal prices (LMP) . For a given dispatch interval, the LMPs capture the marginal value of incremental generation balancing the marginal cost of load reductions.
Market outcomes would be different. When demand is low relative to capacity, the marginal cost would be zero, so the price would be zero. And when the demand curve shifts to the right, price would have to rise to reduce the quantity demanded to match the available capacity. The associated market-clearing LMP price would be (very) high. But the efficient market design says nothing about the level of real-time prices. The prices would change and would be driven entirely by scarcity pricing, but the market design would be unchanged.
The description of the real-time LMP model often simplifies to marginal-cost pricing, which then collapsed to the treatment of the marginal cost of generators. In part this derives from assuming that demand was fixed. But this descriptive convenience was never exactly correct, nor necessary. For example, when load reached the capacity of a given swath of generation, there would always be an additional price component that would reflect the scarcity of lower cost generation. This would include high load periods when all the available generation capacity was in use. Then scarcity prices would be necessary to balance supply and demand.
Less obvious was the treatment of associated operating reserves. The usual analysis focused on energy and ignored the interactions with the required capacity to be set aside for operating reserves. The efficient market implementations continued this practice by failing to account for the interaction of energy and the marginal values of reserves. The assumption was that this would not be very important, because the interaction would be handled through demand participation. However, demand participation did not develop, and thus, efficient design required a more immediate attention to the roles of operating reserves and scarcity pricing.
Improvements in scarcity pricing have been slow to come, with the leading affirmative example being the operating reserve demand curve (ORDC) adopted in the Texas ERCOT system, starting in 2014 [10, 11]. The essential idea is to recognize the imminent expected marginal value of operating reserves, as derived through an operating reserve demand curve, and incorporate that implied scarcity price as part of the market-clearing price of energy. Full implementation would include co-optimization in the economic dispatch. This reform was overdue, and it will be of even greater importance as part of the adaptation of markets to accommodate intermittent renewable energy.
Efficient calculation of the marginal costs for energy would increase the importance of improving pricing for delivered energy. This would separate fixed from variable costs to support demand participation for loads connected at the distribution. The challenge of reforming existing retail rate designs is an old and well-known problem [28, 29]. The expansion of intermittent renewables does not change the fundamentals, but it does increase the importance of price reform.
This study focuses on one potential benefit of transmission infrastructure\u2014congestion relief. It explores historical grid conditions from 2012 through the first half of 2022, and evaluates the marginal value of transmission in facilitating trade within and across regional boundaries by calculating differences in observed nodal wholesale power prices. The study finds that wholesale power prices exhibit stark geographic differences that, in many cases, are stable over time. Many regional and interregional transmission links have significant potential economic value from reducing congestion and expanding opportunities for trade. In fact, many links have hourly average pricing differences in 2021 that exceeded $15/MWh\u2014equivalent to $130 million per year for a 1000 MW link. The value of transmission is correlated with overall energy prices and varies by region and year. Critically, extreme conditions and high-value periods play an outsized role in the value of transmission, with 50% of transmission\u2019s congestion value coming from only 5% of hours. Transmission planners run the risk of understating the benefits of regional and interregional transmission if extreme conditions and high-value periods are not adequately considered. These periods are natural features of actual market operations. As such, the study highlights the need for planners to more-comprehensively assess the value of transmission under both normal and extreme conditions.
Narimani, M., & Hosseinian, S. H. (2022). Investigation of harmonic effects in locational marginal pricing and development of a framework for LMP calculation. Scientia Iranica, 29(3), 1537-1546. doi: 10.24200/sci.2020.54477.3776
M. Narimani; S. H. Hosseinian. "Investigation of harmonic effects in locational marginal pricing and development of a framework for LMP calculation". Scientia Iranica, 29, 3, 2022, 1537-1546. doi: 10.24200/sci.2020.54477.3776
Narimani, M., Hosseinian, S. H. (2022). 'Investigation of harmonic effects in locational marginal pricing and development of a framework for LMP calculation', Scientia Iranica, 29(3), pp. 1537-1546. doi: 10.24200/sci.2020.54477.3776
Narimani, M., Hosseinian, S. H. Investigation of harmonic effects in locational marginal pricing and development of a framework for LMP calculation. Scientia Iranica, 2022; 29(3): 1537-1546. doi: 10.24200/sci.2020.54477.3776
Distribution LMP formulation based on active and reactive power losses is developed in , and linearized power flow for distribution (LPF-D), loss factors for distribution (LF-D), and linear optimal power flow for distribution (LOPF-D) are processed to compute distribution LMP in a distribution system. In , three-phase distribution LMP computing mechanism is developed to operate the distribution network efficiently by minimizing the losses, improving the voltage profile and preserving the balance between the three phases. In , an extended Kalman Filter based method is proposed to determine the nodal prices at DG buses in the distribution network based on the reduction in active power losses by minimizing the total merchandising surplus (MS). The three methodologies have made important contributions to computing LMPs. However, they have not considered the active distribution system for simultaneous monitoring of loss, emission and reliability. A new methodology is proposed to compute locational marginal price in  based on energy price, loss prices caused by nodal active power and reactive power, congestion price and voltage support price using linearized AC power flow. Power-based distribution locational marginal pricing (PDLMP) to determine the active and reactive power tariffs in distribution systems with high penetration of distributed energy resources is proposed in , where PDLMP for DG owners is computed based on over-voltages, congestion, renewable energy share and distribution system operation cost. 2b1af7f3a8