Rearch Of Peak-valley Time-of-use Price Model Considering Reliability Performance And Profit Risks Of Power Systems

Based on the original intention of demand side response--to improve reliabilityperformance of power systems and reduce risks of market transactions, it has importantpractical significance to do research of peak-valley TOU price model consideringsystem reliability and profit risks which do guarantee the power supply reliability,power grid operation enterprise’s profit and improve social economic benefit. Focusingon pricing basis, key factors and optimization models of peak-valley TOU price, thepaper does the following researches：The evaluation of customers’ respond to the electricity price and the division ofpeak-valley periods are the basis of peak-Valley TOU price. At present, there is littleliterature given the analytical solution methods of electricity price elasticity matrix andit is difficult to reflect differences of elastic demand at different load levels andinterplay of periods by means of statistical methods. Aiming at these weaknesses, basedon customers’ cross-time demand response and the balance relations of power supplyand customers’ elastic demand, an analytical method for calculating electricity priceelasticity matrix is deduced in the paper. With this electricity price elasticity matrix,customers’ responses to changes of electricity price can be demonstrated fully andfactually. By the way, the numerical characteristics of self-elasticity and cross-elasticitycoefficient are pointed out in the example analysis. According to semi-trapezoid fuzzydistribution, the method based on F equivalent matrix fuzzy clustering is used to dividepeak-valley period and the division plan can be amended according to theimplementation of electricity price strategy. The numerical example of comparisonanalysis indicates that the method is simple, and can better reflect the peak-valleycharacteristics of load point.The profit risks of power grid operation enterprise and system reliability are keyfactors which should be taken into account for developing peak-valley TOU price. Lineloss is calculated by using multi-period load flow calculation method and in accordancewith market background under "power plants separated form electric network", the costof line loss taken by power grid operation enterprises is determined; through analysis ofrisks in electricity market and based on function relationship between spot marketelectricity prices and load levels, the profit model of power grid operation enterprise isproposed which takes the cost of line loss and the risk of purchasing electricity into account. The effect of the line loss and the risk of purchasing electricity on the profits ofpower grid operation enterprise is analyzed in the example which shows that electricitypricing should be developed with full consideration of line loss costs and purchasingrisks. Reliability evaluation for bulk power system is very complex, time-consuming,then system reliability as a function of load changes is developed using cubic splineinterpolation which can be used to simplify the solution process of optimization modelof peak-valley TOU pricing.Based on the original intention of demand response and taken improving systemreliability and reducing market trading risks as key factors, the peak-valley TOU pricingmodel is established to maximize profit of power grid operating enterprise consideringthe cost of line loss and the risk of purchasing electricity, also taking system reliability,customers’ benefit and their ability to adjust the power as the constraint conditions. Andadaptive genetic calculation is used to solve the model which the cubic splineinterpolation model of system reliability varying with system load is inserted in theprocess.The numerical example shows that, peak-valley TOU price model by motivatecustomers to response to the changes of electricity price, without adding additionalinvestment, through price regulation can be achieved to improve power supplyreliability, reduce outages losses and also reduce risks of purchasing electricity forpower grid operating enterprise. In addition, the different constraint of reliability indicesaffects the results of optimization, as well as customers’ demand for electricity priceelasticity decreases leading to the more significant adjustments of electricity price inorder to guarantee the reliability customers have come to expect.