Demand Side Management (DSM) includes all activities that depend on changing consumer demand characteristics to match supply. This thesis is about demand side management, when customers are equipped with energy storage devices. To implement demand side management, consumers are interacting with energy producers and suppliers to optimally use energy. Game theory is considered as a set of analytical tools that provides an understanding of the phenomena whose decision makers interact with each other. In this dissertation, two games have been studied: in the first case, a non-cooperative game has been implemented between residential energy consumers, in the second case, a Stackelberg game has been implemented between the electricity provider and energy consumers. In this thesis, a logarithmic cost function is used to sell energy saved by consumers. The non-cooperative energy consumption game is played between users who schedule their energy use to minimize energy cost. The game is shown to have a unique Nash equilibrium that is also the global system optimal point. In the Stackelberg game, the utility provider sets the prices to maximize its profit knowing that users will respond by minimizing their cost. Unique results for the Stackelberg equilibrium are presented. The Stackelberg game is shown to be the general case of the minimum Peak-to-Average power ratio (PAR) problem. .The results of this thesis elucidate the interplay between storage capacity, energy requirements, number of users and system performance measured in total cost and peak-to-average power ratio (PAR). The Whale Optimization Algorithm (WOA) is used to optimize the energy consumption pattern. In this thesis, all simulations have been implemented in MATLAB software on a smart grid with a power supplier and ten residential users.

 In this research, optimal planning of a nine bus industrial micro-grid, in order to decrease the operating costs is investigated. For precise modeling of the micro-grid, electrical dispatch is also considered. The generation units of this industrial micro-grid consist of renewable units such as wind unit and solar collector unit. In this research, uncertainty of wind unit is modeled using scenario reduction algorithm. This micro-grid consists of two type of combined heat and power unit which region of operation of them is modeled precisely. In this micro-grid, besides power generation units, there are electrical, thermal and cooling storage resources. The loads of this micro-grid are electrical, thermal and cooling loads which the thermal and the cooling loads are provided with the power generation units of the micro-grid, but in order to supply the load demand, the micro-grid exchanges power with the main grid. In this micro-grid, there are some loads such as Plug-in Electric Vehicles which a location is considered for charging of them and optimization of time of charging them is accomplished. The operation of this micro-grid in presence of two simple and extended PV/T collectors is investigated and the impact of the two collectors on the operation of power generation units is discussed which the results show improvement of operation of micro-grid in presence of extended collector. Optimization of this micro-grid is accomplished in GAMS and the problem is solved with MINLP solver.

 in this thesis an integration of photovoltaic (PV) and Battery Energy Storage System (BESS) with compensating Nonlinear loads capability utility current, maximum power point tracking (MPPT) and dc bus regulation is presented. The dc/dc boost converter is controlled with Incremental Conductance and Integral regulator (ICIR) technique to extract maximum power in different solar irradiation. Instantaneous power theory is used to produce compensated current feeding to the point of common coupling (PCC). Energy storage system has been widely applied in power distribution sectors as well as in renewable energy sources to ensure uninterruptible power supply and dc bus regulation. Using BESS in microgrid voltage stability and distribution energy has particular importance thus control charge and discharge Battery time in different mode operation for maintains dc bus stability is used. The proposed system works in two modes: PV-APF mode which compensating nonlinear loads with feeding MPPT power to the PCC point and APF mode that compensating load reactive power when PV is unavailable (night or Repairs (. Finally, MATLAB simulations results were provided to validate the effectiveness of the proposed PV-BESS Active power filter performance in mitigation harmonics, MPPT and dc bus regulation.

The present study aims at investigating the collaboration of limited energy power plants i.e. wind and solar power plants in restructured power systems. With development of renewable energy sources in power systems, limited energy power plants can play a supplementary role to correct errors from their forecasts. In this study, pump storage power plants are considered as limited energy sources. These power plants collaborate with two wind power plants and a solar power plant and form a power company. The next-day power markets and reserve accessories market have been studied as the target markets of this company. In the proposed model of this study, random planning has been used and the amounts of wind speed, sunshine, and energy price have been considered as random variables of this planning. For each of these random variables, some scenarios have been imagined according to which the forward planning is based. In the previous studies in this field, scant attention has been paid to the accessories markets and only the energy market has been taken into account. Taking reserve accessories markets into consideration, the present study is an attempt to make up for this flaw. Also, in the last part of this study, a proposed model of the collaboration of two wind power plants, three pump storage power plans, and a combine heat and power (CHP) power plant has been presented. The output of the proposed model of this study is the amount of the production of this company in the next 24 hours to bring to the aforementioned markets in which the production share of all power plants is specified, and also to some extent takes power plants capacity to make up for wind speed and sunshine forecast errors into consideration.

 In recent years the use of electric vehicles to reduce greenhouse gas emissions, air pollution in cities and dependence on fossil fuels have increased.. Without planning battery charging vehicles at inappropriate times can enter additional load to the network and cause distribution system failure in the energy supply. But since these vehicles have the ability to exchange bilateral energy, Their battery charging and discharging time can be programmed so that even when the network is not able to supply some customers, electric vehicles parking provide the energy required part of the system. In this thesis, charge and discharge planning of battery PHEVs are in the parking done, with the the goal of increasing the reliability of the distribution system by reducing the number of outages and duration of power outages. To calculate the reliability indices of Monte Carlo simulation is used. Simulation has been done in MATLAB software area, with optimization command fmincon, on The IEEE 34 node test feeder. The results show that in the presence of parking and without controller, SAIFI and SAIDI of network do not change, But the energy not supplied and system customer outage costs are increased. The simulation results in the presence of parking with charge controller show that, reliability indices SAIFI, SAIDI, energy not supplied and system customer outage costs are improving

Scheduling of daily operation of an active radial distribution network (DN) with dispatchable thermal unit and determine the optimal production of renewable resources is very important. In this research, Thermal units are considered in a bilateral contract with DISCO.converter connected DGs, DFIG and PV units, are considered as a liable of reactive power generators. These units are owned by the DISCO. The renewable DGs formed integrated units with battery banks, in order to optimize utilization of resources. Combination of DFIG and battery bank due to presence in the common bus achieved, But combination of PV and battery bank due to presence in the common DC link are achieved. In addition, the presence of other storage devices such as parking PHEVs, are studied as the responsive loads. Task of DSO for parking lots are scheduling for charging and discharging but charging status of PHEVs must be full when they leave the parking. Continuing with the implementation of price based demand response programs (TOU), some percentage of customers, are participating in DR program. In this thesis, DSO for an active radial DN prepare a daily operation to increase profits. The DSO is required to maintain the distribution network constraints, including voltage profiles, congestion of lines etc. all optimization are done in GAMS software area.

 Demand side management (DSM) is one of the important functions in a smart grid. DSM allows customers to make intelligent decisions regarding their energy consumption, and helps the energy providers reduce the peak load demand and reshape the load profile. In conventional demand side management schemes, the energy consumption is optimized from the perspective of either the users or the power company. In this thesis, how energy consumption may be optimized by taking into consideration the interaction between both the parties are investigated. A energy price model as a function of total energy consumption are proposed and a new objective function, which optimizes the difference between the utility (or value) and cost of energy using SQP algorithm also are proposed. in this scheme the control center pulls consumers in a loop and provides them with dynamic energy cost function or dynamic coefficient and current consumption summary vector. Each user then optimizes his own schedule and reports it to the control center, which in turn updates its dynamic energy cost function or dynamic coefficient before pulling the next consumers. This interaction between the power company and its consumers is modeled through a two-step game that formulate an energy consumption scheduling game. The objective of method for the control center is to reduce the Peak to Average Ratio (PAR) by optimizing the users energy schedules and for consumers Is to reduce individual daily electricity charges. The performance of proposed approach is evaluated in matlab-based programming area. simulation results confirm that the proposed approach reduces the peak-to-average ratio of the total energy demand as well as each user’s individual daily electricity charge.

Transmissiom network is one of key parts in power systems. As the demand for electricity Energy is growing, expansion planning of power system sections including transmission network is inevitable. In regulated power systems generation expansion planning and transmission expansion planning are done togheter and almost the objective is to minimize investment cost of planning. Restructuring has exposed transmission planner to new objectives and uncertainties. Therefore, new criteria and approaches are needed for transmission planning in deregulated environments. in this new environment, the planner not only tries to have least investment cost and maintain reliability of power system in a reasonable level, but also must prepare a nondiscrimatory environment for all participants in electricity market; cost of line congestion is an efficient index to show the level of nondiscriminatory. so transmission expansion planning in deregulated systems is an optimization problem with multi objective functions. A common way to slove multi-objective optimization is to change multi-objective functions into a single objective problem but this procdure is very likely to trap in a local optimium point.
Here we tried to solve a multi objective optimization problem for transmission expansion planning so that to obtain optimium value for investment cost, congestion cost and reliability cost using a powerfull metaheuristic algorithm: NSGA II. With a comparision to method of changing multi objectives to single objective, answers of multiobjective were more acceptable. The result of a multi objective optimization is not a single point but is a set of points so with use of some criterias, a point is selected as final answer. Here two criterias are used. One of these criterias has mahtematical basic while the other configured only with respect to programmer's priorities. Comparison between answers resulted from each of these two criterias indicates that applying two criterias simultanously deals to a better answer . To deal with load uncertainty it was assumed different senarios for system load demand and final transmission plan was choosen among number on suggested plans by planning algorithm.
 

The main purpose of this paper is to minimize marginal cost market to maintain system constrains and preserve competition atmosphere between competitors.
In this study important aims of this paper is to explore market condition on inconstant load situation.
Then decoupled energy markets and reactive power in constant and voltage dependent load has been considered and results compared to each other, next coupled energy and reactive power market outcomes compared to decoupled energy and reactive market.
Also voltage dependent loads effects on market, have been discussed.
After that advantages and drawbacks being mentioned. The effectiveness of the proposed framework is examined on the IEEE 24 bus reliability test system by GAMS soft ware.
 

In recent years many efforts in the restructuring of the electricity industry in many countries has been done. The main goal of restructuring is to provide the condition through increase market competition to determine the price of electricity sand reduce the net cost. The elements included in the market included in the market and the market operator and market participants include TRANSCO, GENCO and DISCO and so are classified. An distribution company in the wholesale market buy energy at high voltage level and then transfers the energy to final costumers. In the company distributes planning, risk management means all regulatory measures( in general policies and organizational efforts) to shape responses to various risks. In the past, planning distribution companies only had a balance of performance and cost, but in the new method addition to the cost and the performance, the risks are balanced. With the increasing penetration of wind power in electric power generation, different effect on different aspects of power system include stability, reliability and the risks, should be examine. Thus, the aim of tthesis is " short-term risk management plan of distribution company(DISCO) in the wind farm". A mathematical model is presented to solve this problem and optimization process by using GAMS software is performed

In recent years, the number of PV located within distribution system is rapidly increasing. Capability of generating reactive power and ability of operating in wide range of PV need to be investigated thoroughly at a distribution level, if this scheme is allowed by the standards in the near future. The aim of this work is determining reactive power output of PV in profit based unit commitment for distribution company; voltage and reactive power in distribution system will be controlled without using other reactive compensator. the IEEE 6 bus system and a part of IEEE 14 bus system has been modified and extended to explore network stability impacts of variable PV generation, and the results demonstrated that voltage instability, power loss can effectively be solved and profit will increase by PV inverter active power support. For PV modeling MATLAB programing have been used and solving PBUC is done in GAMS.