Optimal Load Scheduling For Smart Grid

Smart Grid is a new type of grid combining the latest information;communication and computer control technology with the existing transmission andpower distribution infrastructure to realize the intelligent power system, and has thecharacteristic of clean, low carbon and high efficiency. Smart Grid technology hasdeveloped rapidly in recent years in many counties and promotes the intelligent powergrid. Smart Grid becomes the development trend of the future power grid.Smart Grid demand side management is the real-time monitoring of users electricequipment, According to variation in load and price policy guidance, to achieve thereal-time response of users electric equipment. Developing electric power demandside management is helpful to alleviate the contradiction between supply and demand,improve the users’ efficient use of electric energy, promote energy conservation andemissions reduction, and guarantee the sustainable economic and social development.At present a two-way communication network is use to realize the interaction betweenpower grid and users, and problems we care about is power grid load balance, users’power utility fairness and electricity cost. Thus, price adjustment, intelligentscheduling, and balancing the electric load,which can improve users electricity utility,improve the users’ efficient use of electric energy, lower peak-to-average ratio andachieve energy saving, is a major task in the researches of Smart Grid.The main contents and innovations of this paper include the following aspects:First, the traditional electricity price policy can’t really reflect the relationshipbetween power supply and demand, and different user demands may appear the utilityunfairness problem. In this paper, we introduce the user’s fitting utility function intothe objective function of users’ utility maximization problem, which achieve real-timepricing method for utility proportional fairness, and the constraint term is that theamount of all users energy consumption is less than that provided by power supplier,and the objective function is to maximize the difference between all users pseudoutility and energy cost. This model is not only suitable for elastic demand users, but also suitable for inelastic demand users. Then we adopt the dual-gradient projectionalgorithm, so the power supply side and demand side algorithm are deduced. Whenwe get the optimal solution which can realize all users’ utility proportional fairness, itsdual variable namely Lagrange multiplier is exactly supply and demand ofequilibrium price in the competitive market. Also we validate the proposed algorithmthrough Matlab simulation platform, analyze the performance of the algorithms anddraw the relevant conclusions.Second, utilizing network bandwidth pricing model in the optimal residentialload with scheduling based on incentives for Smart Grid. This paper is introduced intoincentive price provided by power supply side, waiting function and additional costfunction provided by power supply side, so we construct the optimal residential loadwith scheduling and realizes the goal of maximizing the profits of the supply side,through optimizing incentive price issued by power supply side. This model willencourage terminal user transfer high load power consumption equipment to off-peakhours, which help users save the cost of power consumption and access to certainreward. For the power supply side, this model reduces chances of getting peak load,and plays the role of peak load shaving. In this paper, we also estimate the userwaiting function based on the time discounting of hyperbolic model. Also we analyzethe algorithms performance through Matlab simulation platform and the estimatedparameters with small fitting error are obtained.Third, the distributed energy access and battery charging and discharging whichare located in the user side not only clean energy effective utilization, reduce userelectricity cost, but also reduce power grid peak flat ratio. This paper is proposed loadoptimization scheduling model for distributed and battery charging and discharging,which is introduced distributed generation (PV Plate) and energy storage, throughoptimizing the electricity demand, power for charging, power which batterydischarging and PV Panel’s energy storage rate, establishing a new mathematicalmodel based on the maximization of user interests and social welfare. Through thedual-gradient projection algorithm and Matlab simulation analysis, we draw aconclusion. Compared with original model, electricity supply side is no longer a single electric power companies, energy storage device also acts as a part of the powersupply, users obtain parameters by optimization algorithm and interact with powergrid, which changes the way of power utilization, reduces the cost and power gridpeak flat ratio.