DISTRIBUTION LOCATIONAL MARGINAL PRICE-OPTIMAL DG-PLACEMENT-SIZING-MODIFIED ANTLION OPTIMIZER
DESIGN DETAILS The transition from Distribution Network Operators (DNOs) to Distribution System Operators (DSOs) represents a significant evolution in the operation and management of modern power systems. Determining the true value of electricity at the distribution level has become increasingly vital, where decentralized energy pricing demands systematic and analytical evaluation. Traditional passive distribution networks are transforming into active distribution systems comprising proactive market participants, where both energy suppliers and consumers dynamically influence market behavior. Consequently, an efficient coordinating entity is essential to conduct market operations, regulate competitive interactions, and establish market clearing and settlement prices. In this work, the optimal placement and sizing of Distributed Generation (DG) units in radial distribution networks are investigated within the Distribution Locational Marginal Price (DLMP) framework, optimized using the Modified-Antlion Optimizer (MALO). The proposed methodology aims to mitigate the operational uncertainties associated with Renewable Energy Sources (RESs) while enhancing network efficiency, reliability, and economic performance. The IEEE 33-bus distribution system serves as the test network for simulation and validation. Bus 1 is designated as the reference bus, where the connected generator submits a flat bid of $20/MWh. This bus represents the low-voltage side (12.66 kV) of a transmission substation, ensuring that the Locational Marginal Price (LMP) established by the Transmission System Operator (TSO) remains relatively unaffected by distribution-level variations. The voltage magnitude across all buses is maintained within the range of 0.95 to 1.01 p.u. Additionally, two microgrids, located at buses 18 and 33, are integrated to simulate double auction market conditions, facilitating the evaluation of DG allocation under competitive market environments. The developed MATLAB-based simulation model demonstrates the effectiveness of the MALO-DLMP approach in reducing real power losses and improving voltage stability, thereby validating its suitability for modern competitive distribution systems. OBJECTIVE FUNCTION Locational Marginal Prices (LMPs) are the Lagrange coefficients corresponding to active power equations at any bus. LMP assigns a valid and precise signal of electricity price to market participants at any node of the power network. Indeed, these values imply the worth of generating an additional megawatt hour (MWh). Distribution Locational Marginal Price (DLMP) is comprised of three components as follows: DLMP_i=λ+λ_(L,i)+λ_(C,i) Energy term: Represents the marginal cost of producing one more MWh. λis the component of marginal energy cost at the reference bus. Loss term: Demonstrates the marginal cost of active power loss in distribution systems. Congestion term: Implies the marginal cost of congestion occurring in distribution networks. REFERENCES Reference Paper-1: Application of Distribution Locational Marginal Price in optimal simultaneous distributed generation placement and sizing in electricity distribution networks Author’s Name: Saeed Nematshahi and Habib Rajabi Mashhadi Source: Wiley Year: 2019 Request source code for academic purpose, fill REQUEST FORM below, http://www.verilogcourseteam.com/requ... If you need Matlab p-code(encrypted files) to check the results, contact us by email to [email protected] You may also contact +91 7904568456 by WhatsApp Chat, for paid services. We are also available on Telegram and Signal. Visit Website: http://www.verilogcourseteam.com/ Visit Our Social Media Like our Facebook Page: / verilogcourseteam Subscribe: / @verilogteam Subscribe: / verilogcourseteammatlabproject Subscribe: / verilogcourseteam