Sharif Digital Repository

Recently, power system operators have initiated procurement of a new service in electricity markets named flexibleramping product (FRP). With the main goal of enhancing the grid flexibility, this product can provide a remarkable opportunity foran enhanced short-term profitability. Energy storage systems (ESSs) with high ramping capability can leverage their profitabilitywhen properly participating in this market. This study introduces a stochastic optimisation framework for participation of ESSs inthe FRP market. The proposed model formulates the optimal bidding strategy of ESSs considering the real-time energy, flexibleramp-up and ramp-down marginal price signals and the associated... 

This paper describes a new method that uses Simulated Annealing (SA) method for analyzing the competition among Generating Companies (Gencos) where they have incomplete information about their opponents. Each Genco models its opponents with their generating cost coefficients. The proposed methodology employs the Supply Function Equilibrium (SFE) for modeling a Genco's bidding strategy. Gencos change their bidding strategies until Nash equilibrium points are obtained. Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging up-todate. This paper uses SA to compute Nash equilibria... 

The present study presents a new risk-constrained bidding strategy formulation of large electric utilities in, presence of demand response programs. The considered electric utility consists of generation facilities, along with a retailer part, which is responsible for supplying associated demands. The total profit of utility comes from participating in day-ahead energy markets and selling energy to corresponding consumers via retailer part. Different uncertainties, such as market price, affect the profit of the utility. Therefore, here, attempts are made to make use of Information Gap Decision Theory (IGDT) to obtain a robust scheduling method against the unfavorable deviations of the market... 

In restructured and de-regulated power systems, generating companies (Gencos) are responsible for supplying electricity for both energy and reserve markets, which usually operate simultaneously. In this condition, the question is how much and for what price must each Genco generate for each market to maximize its profit, so this paper intends to answer to this question. In this paper, first, the combined energy and reserve markets are considered, and the Nash equilibrium points are determined. Then, the bidding strategies for each Genco at these points will be presented. The bids for the energy and 10 min spinning reserve (TMSR) markets are separated in the second stage, and again, the... 

In the restructured power systems, generating companies (Genco) are responsible for selling their product in the energy market. In this condition, the question is how much and for what price must each Genco generate to maximize its profit. Therefore, this paper intends to propose a rational method to answer this question. In the proposed methodology, the hourly forecasted market clearing price (FMCP) is used as a reference to model the possible and probable price strategies of Gencos. The forecasted price is the basis of the bidding strategies of each Genco, which can be achieved by solving a bi-level optimization problem using GAMS (general algebraic modeling system) language. The first... 

In the restructured power systems, they are typically scheduled based on the offers and bids to buy and sell energy and ancillary services (AS) subject to operational and security constraints. Generally, no account is taken of unit reliability when scheduling it. Therefore generating units have no incentive to improve their reliability. This paper proposes a new method to obtain the equilibrium points for reliability and price bidding strategy of units when the unit reliability is considered in the scheduling problem. The proposed methodology employs the supply function equilibrium (SFE) for modeling a unit's bidding strategy. Units change their bidding strategies and improve their... 

This paper describes a new method for analyzing the bidding strategies of Generating Companies (GENCOs) in the Independent System Operator (ISO) point of view. ISO uses these results to detect the participants that have the potential for market power or actual exercise of market power. ISO models all GENCOs with perfect information. The proposed methodology uses the marginal cost of GENCOs as an initial point for bidding strategies of GENCOs and improves bidding strategies based on the objective function of GENCOs, the state of them in each hour of the day and with regard to ISO's market clearing problem. ISO tries to maximize the social welfare or minimize consumer's payments. The model... 

Technical virtual power plant (TVPP) aggregates distributed energy resources in order to trade in wholesale electricity market while taking operational constraints of network into account and offering services to distribution system operator. This article presents a new framework to incorporate the reliability of distribution network into designing the optimal bidding strategy of a TVPP in day-ahead energy market. In the proposed framework, the TVPP determines the multisteps biddings as pairs of power and price aiming at maximizing its profit in market while minimizing the outage costs due to contingency occurrences. The model is formulated as a bilevel optimization problem in which the... 

This paper presented a combined scheduling and bidding algorithm for constructing the bidding curve of an electric utility that participated in the day-ahead energy markets. Day-ahead market price uncertainty was modeled using non-probabilistic information gap decision theory (IGDT). The considered utility consisted of generation units and a retailer part; the retailer part of the utility and its demand response program (DRP) could affect the utility's profit, which should be considered in the bidding strategy problem. The bidding strategy algorithm proposed in this paper dispatched units by optimizing the demand response programs of the retailer part. In addition, non-decreasing bidding... 

Reactive market power assessment is an important issue for ISOs and the regulators of the reactive power market. Due to the localized characteristics of reactive power as a technical support and its monopsonistic nature as an economic commodity, a vivid reactive market power index including market share, demand side and cost is not achieved yet. In this paper, a new reactive market power index is presented which is based on bidding strategy deviation of the GENCOs after establishing a uniform price auction reactive market. Not knowing others' offers to ISO, each unit faces a bidding strategy problem that is solved using game theory. Considering its production costs, the unit uses the... 

This paper presents a new approach for determining the day-ahead bidding strategies of a large-scale hybrid electric energy company. The company has both energy generation and energy retailing businesses in a competitive electricity market. Demand response programs are also considered in the retail side of the company in order to hedge the risk of participation in wholesale market. This paper introduces a max-min bilevel mathematical programming with equilibrium constraint model for offering a strategy that manages the risk of uncertain forecasted rivals' bids by robust optimization. The max-min bilevel model is converted to its equivalent single-level optimization using Karush-Kuhn-Tucker... 

Integrating independent dispatchable and non-dispatchable resources into a micro-grid platform enables the main power systems to benefit from the economic and environmental advantages of distributed generation while facilitating local, clean, and inexhaustible renewable energy production. Moreover, it makes the integrated components more visible and controllable for the whole power system. On the other hand, to properly handle multiple uncertainties inherent in the micro-grids, probabilistic energy management techniques are deployed. However, utilization of stochastic modeling and optimization tools for efficient, reliable, and cost-effective planning, operation, and control of micro-grids... 

Distributed energy resources (DERs) play an important role in the future vision of distribution energy networks. This paper with the aim of promoting DERs role in energy markets proposes a new framework for the optimal bidding strategy of a Technical Virtual Power Plant (TVPP) in different markets. In the proposed framework, it is assumed that the TVPP energy power is distributed throughout a multi-carrier energy network (MCEN) which consists of district heat networks (DHNs) and a distributed electricity network (DEN). In the MCEN, CHP units are the linkage between DHNs and DEN. With the goal of maximizing the profit of TVPP in different local and wholesale energy markets, a bi-level... 

Technical virtual power plant (TVPP) aggregates distributed energy resources in order to trade in wholesale electricity market while taking operational constraints of network into account and offering services to distribution system operator. This article presents a new framework to incorporate the reliability of distribution network into designing the optimal bidding strategy of a TVPP in day-ahead energy market. In the proposed framework, the TVPP determines the multisteps biddings as pairs of power and price aiming at maximizing its profit in market while minimizing the outage costs due to contingency occurrences. The model is formulated as a bilevel optimization problem in which the...