Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.

Modeling and Design of Real-Time Pricing Systems Based on Markov Decision Processes

A real-time pricing system of electricity is a system that charges different electricity prices for different hours of the day and for different days, and is effective for reducing the peak and flattening the load curve. In this paper, using a Markov decision process (MDP), we propose a modeling method and an optimal control method for real-time pricing systems. First, the outline of real-time pricing systems is explained. Next, a model of a set of customers is derived as a multi-agent MDP. Furthermore, the optimal control problem is formulated, and is reduced to a quadratic programming problem. Finally, a numerical simulation is presented.

A real-time measuring technology for studying distortion of hydraulic turbine blade castings during heat treatment process

During heat treatment process, the distortion behavior inevitably appears in hydraulic turbine blade castings. In this research, a technology was developed for real-time measurement of the distortion in hydraulic turbine blade castings at the still air cooling and forced air cooling stages during heat treatment process. The method was used to measure the distortion behavior at the cooling stages in both normalizing and tempering processes. At the normalization, the distortion at the blade comer near outlet side undergoes four stages with alternating bending along positive and negative directions. At the tempering stage, the distortion could be divided into two steps. The temperature difference between the two surfaces of blade casting was employed to analyze the distortion mechanism. The measured results could be applied to guide the production, and the machining allowance could be reduced by controlling the distortion behavior.

Electricity Price Influence Factors Analysis Using Stochastic Matrix for Real-Time Electricity Price Forecasting

Real-time electricity price( RTEP) influence factor extraction is essential to forecasting accurate power system electricity prices. At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors. In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly, an augmented matrix is formulated, including RTEP influence factor data and RTEP state data. Secondly, data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius( MSR) is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method. Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.

Design of Real-time Electricity Prices and Wireless Communication Smart Meter

Under the background of smart grid’s real-time electricity prices theory, a real-time electricity prices and wireless communication smart meter was designed. The metering chip collects power consumption information. The real-time clock chip records current time. The communication between smart meter and system master station is achieved by the wireless communication module. The “freescale” micro controller unit displays power consumption information on screen. And the meter feedbacks the power consumption information to the system master station with time-scale and real-time electricity prices. It results that the information exchange between users and suppers can be realized by the smart meter. It fully reflects the demanding for communication of smart grid.

A Research of Real-Time Pricing Mechanism and Its Characteristics

Real-Time Pricing (RTP) is proposed as an effective Demand-Side Management (DSM) to adjust the load curve in order to achieve the peak load shifting. At the same time, the RTP mechanism can also raise the revenue of the supply-side and reduce the electricity expenses of consumers to achieve a win-win situation. In this paper, a real-time pricing algorithm based on price elasticity theory is proposed to analyze the energy consumption and the response of the consumers in smart grid structure. We consider a smart grid equipped with smart meters and two-way communication system. By using real data to simulate the proposed model, some characteristics of RTP are summarized as follows: 1) Under the condition of the real data, the adjustment of load curve and reducing the expenses of consumers is obviously. But the profit of power supplier is difficult to ensure. If we balance the profits of both sides, the supplier and consumers, the profits of both sides and the adjustment of load curve will be relatively limited. 2) If assuming the response degree of consumers to real-time prices is high enough, the RTP mechanism can achieve the expected effect. 3, If the cost of supply-side (day-ahead price) fluctuates dramatically, the profits of both sides can be ensured to achieve the expected effect.

Leading Indicators of Heating Coal Pricing in Turkey: A Coal Pricing Model (2003-2009)

In this study, a coal pricing model for Turkey is developed employing Granger causality and cointegration analysis by using monthly data between January 2003 and April 2009. Empirical results based on Granger causality tests indicate that foreign coal futures prices and domestic consumer price index for energy sector can be used as the leading indica- tors for domestic coal prices for Turkey. An error correction model for Turkish coal pricing is specified by taking into account the results of Granger causality. The forecast of the coal prices based on error correction model is giving very successful results. It is observed that the coal prices and forecasted coal prices values are almost moving together or very close to each other.

Verification of Real-Time Pricing Systems Based on Probabilistic Boolean Networks

In this paper, verification of real-time pricing systems of electricity is considered using a probabilistic Boolean network (PBN). In real-time pricing systems, electricity conservation is achieved by manipulating the electricity price at each time. A PBN is widely used as a model of complex systems, and is appropriate as a model of real-time pricing systems. Using the PBN-based model, real-time pricing systems can be quantitatively analyzed. In this paper, we propose a verification method of real-time pricing systems using the PBN-based model and the probabilistic model checker PRISM. First, the PBN-based model is derived. Next, the reachability problem, which is one of the typical verification problems, is formulated, and a solution method is derived. Finally, the effectiveness of the proposed method is presented by a numerical example.

An Approach to Quantify the Heat Wave Strength and Price a Heat Derivative for Risk Hedging

Mitigating the heat stress via a derivative policy is a vital financial option for agricultural producers and other business sectors to strategically adapt to the climate change scenario. This study has provided an approach to identifying heat stress events and pricing the heat stress weather derivative due to persistent days of high surface air temperature （SAT）. Cooling degree days （CDD） are used as the weather index for trade. In this study, a call-option model was used as an example for calculating the price of the index. Two heat stress indices were developed to describe the severity and physical impact of heat waves. The daily Global Historical Climatology Network （GHCN-D） SAT data from 1901 to 2007 from the southern California, USA, were used. A major California heat wave that occurred 20-25 October 1965 was studied. The derivative price was calculated based on the call-option model for both long-term station data and the interpolated grid point data at a regular 0.1~ x0.1~ latitude-longitude grid. The resulting comparison indicates that （a） the interpolated data can be used as reliable proxy to price the CDD and （b） a normal distribution model cannot always be used to reliably calculate the CDD price. In conclusion, the data, models, and procedures described in this study have potential application in hedging agricultural and other risks.

The Voice of Physics in Finance:A Glance on the Theoretical Application of Heat Equation to Stock Price Diffusions

Stock price volatility is considered the main matter of concern within the investment grounds.However,the diffusivity of these prices should as well be considered.As such,proper modelling should be done for investors to stay healthy-informed.This paper suggest to model stock price diffusions using the heat equation from physics.We hypothetically state that,our model captures and model the diffusion bubbles of stock prices with a better precision of reality.We compared our model with the standard geometric Brownian motion model which is the wide commonly used stochastic differential equation in asset valuation.Interestingly,the models proved to agree as evidenced by a bijective relation between the volatility coefficients of the Brownian motion model and the diffusion coefficients of our heat diffusion model as well as the corresponding drift components.Consequently,a short proof for the martingale of our model is done which happen to hold.

蓄热式电采暖参与消纳受阻风光的源荷协调滚动调度

蓄热式电采暖负荷具有时移性和连续可调性,可作为需求侧资源解决乡村地区新能源消纳困难与清洁供暖问题。当前实施的峰谷分时电价,不能根据源荷变化有效引导电采暖运行以消纳受阻风光。因此提出采用场景法描述风光荷的不确定性,根据源荷峰谷时段变化确定分时电价。并且考虑电采暖响应分时电价时出现用电同时率高问题,引入需求价格弹性系数,建立以蓄热式电采暖运行成本和系统负荷峰谷差期望最小的日前日内源荷协调优化模型,滚动调整每时段各灵活资源出力。最后,通过仿真验证模型的有效性。

考虑多能耦合共享储能的微网多智能体混合博弈协调优化

冷热电耦合的共享储能可以更显著地提高微网多种能源的利用效率与消纳水平。然而,多能耦合的共享储能进一步增加了多微网之间协调运行的难度,故而提出了一种考虑多能耦合共享储能的微网多智能体混合博弈协调优化模型。首先,围绕多能耦合共享储能进行建模,从冷、热、电3个维度构建元件的运行模型。其次,提出了一种计及多能耦合共享储能协作的微网混合博弈双层协调调度模型。上层部分为基于主从博弈的微网运营商日内电价优化模型,以微网运营商的日内收益最大化为目标,综合考虑电价上下限约束和购售电价平均值约束,为下层协作运行提供响应电价;下层部分为基于合作博弈的微网间协作运行策略模型,以产消者和共享储能电站的合作成本为目标,综合考虑机组出力上下限约束和功率平衡约束,为上层反馈合作成本用于指导电价优化调整。然后,在混合博弈模型求解时,以电价变动率为收敛判据,同时采用二分法处理电价约束以加速模型求解。最后,采用多智能体协调优化的微网系统验证了所提方法的有效性。

计及动态能源价格和共享储能电站的多主体综合能源系统双层优化调度策略

可再生能源不确定性背景下,为协调综合能源运营商、电热负荷聚集商及共享储能电站之间的利益关系,提出一种电热综合动态定价机制,基于综合需求响应特性,引导电热负荷聚集商参与综合能源系统运营商优化,促进储能高效应用和新能源就地消纳,实现多利益主体互利共赢。以综合能源系统运营商为主体,以电热负荷聚集商和共享储能运营商为从体,构建一主多从的综合能源多运营主体系统优化模型。充分挖掘共享储能运营商的运行模式,包括充电、放电和提供备用等模式。采用CPLEX对主从博弈模型迭代求解,算例结果验证了模型及方法的有效性。

基于谷电条件的几类典型户用供暖系统模拟分析

针对内蒙古蒙西地区实行清洁供暖采用峰谷分时电价政策,探究综合经济性最优的“煤改电”采暖系统以及峰谷时段运行时间组成。以内蒙古包头某居民住宅为研究对象,利用TRNSYS软件搭建了直热式电锅炉、太阳能+电辅助、超低温空气源热泵3种热源“峰谷分时电价”采暖系统模型,进行仿真模拟计算;通过对3种采暖模式的初装费、运行费、设备维护这3个因素进行综合经济性评价,结果表明:电锅炉、太阳能、空气源热泵3个系统峰谷电运行时间组成分别为3:7、2:8和3:7;从第3年开始,空气源采暖系统综合经济性凸显;第7年开始,太阳能采暖系统综合经济性才首次超过直热式电锅炉。若单纯考虑采暖经济性,建议首选空气源热泵采暖系统,直热式电锅炉为第二选项。该结果为后续“煤改电”的实施提供现实参考。

《热泵系统参与电网调峰技术规程》编制要点及相关展望

通过简述《热泵系统参与电网调峰技术规程》的编制背景、编制过程、主要内容,对规程编制过程中的要点进行了详细解读,包括提出热泵系统在参与电网调峰过程中的主要技术措施与应用场景,分析参与电网调峰的热泵系统用能负荷与日程,规范负荷削减效果、调峰响应执行效果与调峰响应对能源、经济、环境的影响等热泵系统调峰性能的量化指标与计算方法。进一步进行相关展望,阐述了建筑柔性用能系统对于电网调峰以及可再生能源消纳的重要性。期望通过该规程的制定和实施,更好地规范、引导、促进热泵等建筑柔性用能系统参与电网调峰的应用和发展,令建筑柔性用能成为未来低碳能源系统中的重要一环。

驻马店公司供热市场开拓及热价争取探索与实践

国能驻马店热电有限公司(以下简称驻马店公司)全力开拓热力市场,售热量突破瓶颈,大幅提升工业热价,促进公司提质增效。驻马店公司供热市场开拓及热价争取工作均取得突破进展,经验成效可供相关热电公司借鉴。

高速公路服务区建筑供暖方案对比分析

以山西省某高速公路服务区固体蓄热和空气源热泵供暖改造项目为案例,从理论上研究了环境温度、峰平谷电价对两种方案适用性和经济性的影响,综合分析可知,在一定工况条件下,当环境温度高于某个临界温度值时,宜采用空气源热泵供暖,且峰平谷电价差值越大,空气源热泵优势越明显。可为山西省高速公路收费站和服务区站点供暖方案的选择提供理论和实例基础。

西藏居民区清洁能源供暖方案设计研究

利用西藏丰富的太阳能资源建设清洁能源供暖系统,以解决高原居民采暖需求问题。研究提出了分布式太阳能热水供暖和电采暖配套光储系统两种技术方案。方案1平时运行时除供暖水泵外,没有其他耗电设备,年运行费用低;方案2电费采用“收支两条线”的方式,居民用电向电网公司支付电费、光伏发电取得电费收入。通过技术经济性分析,推荐方案1解决居民供暖,可供类似工程项目设计参考。

地源热泵耦合消防水池系统的经济性分析

为响应国家节能减排政策,降低工业用电成本,缓解高峰时段电网供电压力,以郑州某工程为例,采用地源热泵耦合消防水池系统为建筑供暖供冷,根据峰谷电价政策优化运行模式计算可知,较无消防水池的地源热泵系统,此方案每年运行成本可降低30%~40%,较传统的燃气锅炉+冷水机组供暖供冷系统,成本降低60%~70%。该方案可有效削减工厂电力开支,减轻用电高峰电网供电压力,同时降低碳排放量。

Electricity Pricing for Natural Gas CHP Projects The Higher, the Better?

Regarding the state's policy that gives a higher on-grid electricity price to natural gas CHP (combined heat and power) projects, this paper studies the effect of it on the operation of those projects by theoretical analysis and a case study. It concludes that on-grid electricity price on the high side, compared to heat price, will lead power plants to produce more electricity but less heat, thus causing decrease of the plants' thermal eff iciency and harm to energy saving of the whole society.