Electronic multilateral trade of electricity

This paper presents a technical approach for electronic multilateral trade of electricity in competitive power industries. The trade involves strategic sharing of data among agents in an attempt to provide the opportunity to intelligently discover competitive behavior of peer suppliers. A trading logic is implemented as a specialized software module within the agent. The logic mimics intelligence of the human strategic trade. A time-bounded trade protocol has been introduced as a trading basis among rivalry trade agents in the market. The protocol limits the trade rounds in order to bind the trading process to specific deadlines. The protocol is coded as part of the automated trade server. The results of a generic 3-bus test system show that the electronic multilateral trade logic presented in this paper better distributes market sales, lowers prices and consequently provides higher social welfare compared to the standard Cournot economic model that may be used by the human decision-maker for market trading. Based on a set of test cases with different load profiles, it is noted that the electronic multilateral trade drives the market price closer to the marginal cost of generation supply and far away from the estimated Cournot price.     

Hydrothermal scheduling by augmented Lagrangian: consideration oftransmission constraints and pumped-storage units

This paper presents an augmented Lagrangian (AL) approach to scheduling a generation mix of thermal and hydro resources. AL presents a remedy to duality gap encountered with the ordinary Lagrangian for nonconvex problems. It shapes the Lagrangian function as a hyperparaboloid associating penalty in the direction of the coupling constraints. This work accounts further for the transmission constraints. We use a hydrothermal resource model with pumped-storage units. An IEEE 24-bus test system is used for AL performance illustration. Computational models are all coded in C. The results of the test case show that the AL approach can provide better scheduling results as it can detect optimal on/off schedules of units over a planning horizon at a minimal cost with no constraint violation. It requires no iteration with economic dispatch algorithms. The approach proves accurate and practical for systems with generation diversity and limited transmission capacity     

Security-constrained optimal generation scheduling for GENCOs

This paper presents an approach for maximizing a GENCO's profit in a constrained power market. The proposed approach considers the Interior Point Method (IPM) and Benders decomposition for solving the security-constrained optimal generation scheduling (SC-GS) problem. The master problem represents the economic dispatch problem for a GENCO which intends to optimize its profit. The formulation of the master problem does not bear any transmission network constraints. The subproblem will be used by the same GENCO to check the viability of its proposed bidding strategy in the presence of transmission network constraints. In this case if the subproblem does not yield a certain level of financial return for the GENCO or if the subproblem results in an infeasible solution of the GENCO's proposed bidding strategy, the GENCO will modify its proposed solution according to the Benders cuts that stem out of the subproblem. The study shows a more flexible scheduling paradigm for a GENCO in a competitive arena. The proposed approach proves practical for modeling the impact of transmission congestion on a GENCO's expected profit in a competitive environment.     

Supply curve bidding of electricity in constrained power networks

This paper presents a Supply Curve Bidding (SCB) approach that complies with the notion of the Standard Market Design (SMD) in electricity markets. The approach considers the demand-side option and Locational Marginal Pricing (LMP) clearing. It iteratively alters Supply Function Equilibria (SFE) model solutions, then choosing the best bid based on market-clearing LMP and network conditions. It has been argued that SCB better benefits suppliers compared to fixed quantity-price bids. It provides more flexibility and better opportunity to achieving profitable outcomes over a range of demands. In addition, SCB fits two important criteria: simplifies evaluating electricity derivatives and captures smooth marginal cost characteristics that reflect actual production costs. The simultaneous inclusion of physical unit constraints and transmission security constraints will assure a feasible solution. An IEEE 24-bus system is used to illustrate perturbations of SCB in constrained power networks within the framework of SDM. By searching in the neighborhood of SFE model solutions, suppliers can obtain their best bid offers based on market-clearing LMP and network conditions. In this case, electricity producers can derive their best offering strategy both in the power exchange and the long-term contractual markets within a profitable, yet secure electricity market.