Showing 5 results for Game Theory
T. Barforoushi, M. P. Moghaddam, M. H. Javidi, M. K. Sheik-El-Eslami,
Volume 2, Issue 2 (4-2006)
Abstract
Medium-term modeling of electricity market has essential role in generation
expansion planning. On the other hand, uncertainties strongly affect modeling and
consequently, strategic analysis of generation firms in the medium term. Therefore, models
considering these uncertainties are highly required. Among uncertain variables considered
in the medium term generation planning, demand and hydro inflows are of the greatest
importance. This paper proposes a new approach for simulating the operation of power
market in medium-term, taking into account demand and hydro inflows uncertainties. The
demand uncertainty is considered using Monte-Carlo simulations. Standard Deviation over
Expected Profit (SDEP) of generation firms based on simulation results is introduced as a
new index for analyzing the influence of the demand uncertainty on the behavior of market
players. The correlation between capacity share of market players and their SDEP is also
demonstrated. The uncertainty of inflow as a stochastic variable is dealt using scenario tree
representation. Rational uncertainties as strategic behavior of generation firms, intending to
maximize their expected profit, is considered and Nash-Equilibrium is determined using the
Cournot model game. Market power mitigation effects through financial bilateral contracts
as well as demand elasticity are also investigated. Case studies confirm that this
representation of electricity market provides robust decisions and precise information about
electricity market for market players which can be used in the generation expansion
planning framework.
Sh. Gorgizadeh, A. Akbari Foroud, M. Amirahmadi,
Volume 8, Issue 2 (6-2012)
Abstract
This paper proposes a method for determining the price bidding strategies of
market participants consisting of Generation Companies (GENCOs) and Distribution
Companies (DISCOs) in a day-ahead electricity market, while taking into consideration the
load forecast uncertainty and demand response programs. The proposed algorithm tries to
find a Pareto optimal point for a risk neutral participant in the market. Because of the
complexity of the problem a stochastic method is used. In the proposed method, two
approaches are used simultaneously. First approach is Fuzzy Genetic Algorithm for finding
the best bidding strategies of market players, and another one is Mont-Carlo Method that
models the uncertainty of load in price determining algorithm. It is demonstrated that with
considering transmission flow constraints in the problem, load uncertainty can considerably
influences the profits of companies and so using the second part of the proposed algorithm
will be useful in such situation. It is also illustrated when there are no transmission flow
constraints, the effect of load uncertainty can be modeled without using a stochastic model.
The algorithm is finally tested on an 8 bus system.
P. Raja, P. Dananjayan,
Volume 10, Issue 1 (3-2014)
Abstract
Wireless Sensor Networks (WSNs) comprising of tiny, power-constrained nodes are getting very popular due to their potential uses in wide applications like monitoring of environmental conditions, various military and civilian applications. The critical issue in the node is energy consumption since it is operated using battery, therefore its lifetime should be maximized for effective utilization in various applications. In this paper, a game theory based hybrid MAC protocol (GH-MAC) is proposed to reduce the energy consumption of the nodes. GH-MAC is combined with the game based energy efficient TDMA (G-ETDMA) for intra-cluster communication between the cluster members to head nodes and game theory based nanoMAC (G-nanoMAC) protocol used for inter-cluster communication between head nodes. Performance of GH-MAC protocol is evaluated in terms of energy consumption, delay and compared with conventional MAC schemes. The results obtained using GH-MAC protocol shows that the energy consumtion is enormously reduced and thereby the lifetime of the sensor network is enhanced.
S. Arefi Ardakani, A. Badri,
Volume 13, Issue 4 (12-2017)
Abstract
Today due to increasing and evolving of electrical grids, the optimal and profitable energy production is among producers' major concerns. Thus, conventional ways of production and trading energy are being replaced by modern economical procedures. In addition, distributed energy resources (DERs) in form of renewable and conventional resources as well as responsive loads play an important role in this issue. The mutual problem of DERs in joining power market is their rather small production compared to other units and intermittency of the corresponding resources. Forming coalition is an effective way to overcome DER difficulties for participating in power market. In this paper the problem of optimal bidding strategy of DERs integrated as a virtual power plant is investigated. Based on the proposed method, cooperative game is employed to obtain optimal DER outputs and the results are compared with individual non-cooperative bidding model. In order to mitigate the intermittent nature of renewable energies, existence of electric vehicles (EVs) as energy storage facilities in the proposed coalition is investigated. Due to the associated uncertainties regarding EVs and DERs, a stochastic optimization model is used. Finally, Shapley value method is employed to obtain corresponding allocated profits. Results show the eminence of forming coalition in terms of acquiring payoffs and optimal contributions.
R. Mohammadi, H. Rajabi Mashhadi,
Volume 15, Issue 1 (3-2019)
Abstract
Distribution system reliability programs are usually based on improvement of average reliability indices. They have weakness in terms of distinguishing between reliability of different customers that may prefer different level of reliability. This paper proposes a new framework based on game theory to accommodate customers’ reliability requests in distribution system reliability provision. To do this, distribution reliability equations are developed so that it is recognized how game theory is suitable for this purpose and why conventional methods could not provide customer reliability requirements appropriately. It would be shown that customer participation in distribution system reliability provision can make conflict of interest and leads to a competition between customers. So, in this paper a game theoretic approach is designed to model possible strategic behavior of customers in distribution system reliability provision. The results show that by implementing the proposed model, distribution utilities would have the capability to respond to customers’ reliability requirements, such that it is beneficial for both utility and customers.
