:Conditional value at risk (CVaR) and confidence degree theory are introduced to build scheduling model for VPP connecting with wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and incentive-based demand response (IBDR). Latin hypercube sampling method and Kantorovich distance are introduced to construct uncertainties analysis method. A risk aversion scheduling model is proposed with minimum CVaR objective considering maximum operation revenue. The IEEE30 bus system is used as simulation system. Results show: (1) Price-based demand response could realize peak load shifting, ESSs and IBDR could increase operation revenue. (2) Threshold α reflects risk attitude of decision maker, which has strong risk tolerant to gain the excess income with low α. (3) In peak period, decision maker would reduce WPP and PV for avoiding power shortage loss. Otherwise, WPP and PV would be called in priority since system reserve capacity is sufficient. (4) When 0.85≤β<0.95, the decreasing slope of CVaR value is big, decision maker is sensitive on risk. When β≥0.95, VPP scheduling scheme reach the most conservative, net revenue and CVaR value are ¥8995.34 and ¥18834. Therefore, the proposed model could describe VPP risk and provide decision support tool for decision maker. Key words:CVaR method; virtual power plant; demand response; risk aversion; dynamical scheduling 1 Introduction Energy shortage and environment pollution problems promote power industry put more attention in renewable energy power generation. Renewable energy power generation makes full use of wind energy, solar energy and hydro energy. They are playing increasingly important roles in energy structures with small pollutant emission, high efficiency and less transmission cost [1]. However, limited by small installed capacity, large quantity and decentralized distribution, distributed generators (DGs) has high grid connection cost [2], what's more, the volatility of DG output affects the stable operation of power grid [3].Virtual power plant (VPP) integrates DGs, energy storage systems (ESSs), controllable load and distributed energy resources (DERs) using refined control method and energy management [4], which can realize effective DG integration and polymerization [5].
We presented a low-noise, high-gain photodetector based on the bootstrap structure and the L-C (inductance and capacitance) combination. Electronic characteristics of the photodetector, including electronic noise, gain and frequency response, and dynamic range, were verified through a single-frequency Nd:YVO4 laser at 1064 nm with coherent output. The measured shot noise of 50 μW laser was 13 dB above the electronic noise at the analysis frequency of 2 MHz, and 10 dB at 3 MHz. And a maximum clearance of 28 dB at 2 MHz was achieved when 1.52 mW laser was illuminated. In addition, the photodetector showed excellent linearities for both DC and AC amplifications in the laser power range between 12.5 μW and 1.52 mW.
We present a mutual compensation scheme of three phase fluctuations, originating from the residual amplitude modulation (RAM) in the phase modulation process, in the bright squeezed light generation system. The influence of the RAM on each locking loop is harmonized by using one electro-optic modulator (EOM), and the direction of the phase fluctuation is manipulated by positioning the photodetector (PD) that extracts the error signal before or after the optical parametric amplifier (OPA). Therefore a bright squeezed light with non-classical noise reduction of π is obtained. By fitting the squeezing and antisqueezing measurement results, we confirm that the total phase fluctuation of the system is around 3.1 mrad. The fluctuation of the noise suppression is 0.2 dB for 3 h.
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