Analysis and decomposition of active and reactive power spot price in deregulated electricity markets

Electricity markets have suffered important modifications in recent decades in many countries, in which a competition framework has been established with the aim of improving market efficiency and reducing energy prices. However, this new paradigm does not assure optimal solutions, as new constraints can be introduced in optimization processes that can affect the resulting prices. An example of this situation is the establishment of power purchase agreements between producers and consumers. A wide literature can be found regarding electricity markets. Some of this literature refers to the theory of spot prices and its application to them. This paper deals with the obtaining, decomposition and deduction of behavior rules of spot prices, and their influence on established contractual relationships in a deregulated market environment which allows power purchase agreements between consumers and producers. It is performed by a deterministic modeling of the complete generation-grid system. The influence of the existence of this kind of agreements on both total costs and spot prices is discussed.     

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

Multi-elite guide hybrid differential evolution with simulated annealing technique for dynamic economic emission dispatch

This paper proposes an improved multi-objective differential evolutionary algorithm named multi-objective hybrid differential evolution with simulated annealing technique (MOHDE-SAT) to solve dynamic economic emission dispatch (DEED) problem. The proposed MOHDE-SAT integrates the orthogonal initialization method into the differential evolution, which enlarges the population diversity at the beginning of population evolution. In addition, modified mutation operator and archive retention mechanisms are used to control convergence rate, and simulated annealing technique and entropy diversity method are utilized to adaptively monitor the population diversity as the evolution proceeds, which can properly avoid the premature convergence problem. Furthermore, the MOHDE-SAT is applied on the thermal system with a heuristic constraint handling method, and obtains more desirable results in comparison to those alternatives established recently. The obtained results also reveal that the proposed MOHDE-SAT can provide a viable way for solving DEED problems.     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

Trends and driving forces of low-carbon energy technology innovation in China’s industrial sectors from 1998 to 2017: from a regional perspective

Low-carbon energy technology (LC) innovation contributes to both environmental protection and economic development. Using the panel data of 30 provinces/autonomous regions/municipalities in China from 1998 to 2017, this paper constructs a two-layer logarithmic mean Divisia index (LMDI) model to uncover the factors influencing the variation of the innovation of LC in China’s industrial sectors, including the alternative energy production technology (AEPT) and the energy conversation technology (ECT). The results show that China’s industrial LC patent applications rapidly increased after 2005 and AEPT patent applications outweighed ECT patent applications all the time with a gradually narrowing gap. Low-carbon degree played the dominant role in promoting the increase in China’s industrial LC patent applications, followed by the economic scale, R&D (research and development) efficiency, and R&D share. Economic structure contributed to the increases in LC patent applications in the central and the western regions, while led to the decreases in the eastern region, the north-eastern region, and Chinese mainland Xizang(Tibet) Autonoomous Region is not considered due to lack of data. This note applies to the entire article.. Low-carbon degree and economic scale were two main contributors to the growths of both industrial AEPT patent applications and ECT patent applications in Chinese mainland and the four regions. Several policy recommendations are made to further promote industrial innovation in China.     

城市低碳群体建筑外部边缘空间规划仿真研究

针对当前空间规划方法存在的计算时间长、规划成本高等问题,提出一种基于蚁群算法的低碳群体建筑外部边缘空间规划方法。依据城市低碳群体建筑外部边缘空间的模糊特性,引入模糊集合理论对建筑外部边缘空间进行理解和建筑外部边缘空间模糊矩阵的构建,对边缘空间进行划分和限定。结合建筑外部边缘空间的特性和具体关系模式进行空间层次划分,计算空间属性权重,以此确立空间规划目标,根据空间规划目标函数构建空间规划模型,设定求解空间规划模型的蚁群算法信息素更新方式,依据个体信息素转移概率指导个体进行模型最优解搜索。实验结果表明,所提方法与传统的空间规划方法相比,有效减少了计算时间,降低了规划成本。     

我国两部制电价制度对天然气发电企业盈利能力的影响

上海、浙江和江苏等地陆续出台了两部制电价制度,以期解决天然气发电(以下简称气电)企业成本高、经营困难等问题。为了研究该电价制度对气电企业盈利能力的影响,在对比分析上述三地电价政策和实施效果的基础上,基于不同类型机组的三大经营指标(项目财务内部收益率、经济净现值、动态投资回收期),采用项目经济性分析模型探究了不同类型燃气电厂的经济性。研究结果表明:①现行两部制电价与单一制电价相比,电价水平小幅度下降,给企业经营带来了一定的冲击,但从长远看,则有利于形成可持续的发展机制;②两部制电价是各地政府经过充分调研和测算后根据该区具体情况制定的,在该政策下多数企业处于盈亏平衡点附近,综合条件优、管理水平高的企业能取得一定的盈利,反之则亏损;③当电量电价一定且大于盈亏平衡点时,企业效益随年利用小时数的增加而提升,反之则随年利用小时数的增加而降低。结论认为:①两部制电价能起到促进企业管理和技术水平提升,引导和鼓励电力投资的作用,符合我国电力体制改革的方向;②政策制定时应针对不同时期建成的项目加以区别对待,实现上网电价、天然气价格和供热蒸气价格的"三个联动";③应建立大数据平台,实行气网、电网联合调度;④发电企业应创新管理,降低电厂建设及维护成本,提升机组效率,降低气耗。     

基于混合蚁群算法的异质车队低碳VRP研究

针对货运车辆在配送调度过程中产生大量碳排放的问题，建立模型将多种影响碳排放量的因素协同优化。模型中考虑了不同载重量的异质车队，两个节点之间有多条道路的柔性路径，以及车辆重量随卸货而减少的动态负载等因素，以碳排放量、行驶时间和行驶路程为优化目标，并加入了节点需求时间窗、根据速度变化划分路段、交接和卸货时间的约束。提出了一种混合蚁群算法，利用蚁群算法信息素强度更新方式保持群体记忆性，利用粒子群算法的快速收敛特性增加计算效率。通过随机数值算例的仿真优化与对比分析，验证了算法和模型的有效性。     

低碳环境下钢铁企业燃气系统动态平衡调度仿真

在“节能减排、降本增效”的大背景下,从碳素流视角切入,在煤气介质预测基础上,建立了0-1混合线性规划模型,以能源成本和碳交易成本总和最小化为目标,研究钢铁行业副产煤气生产调度问题。采用基于遗传算法的动态迭代调度算法,通过混合交叉算子和平均变异算子提高遗传算法局部搜索能力,并以国内某大型钢铁企业为仿真对象进行系统仿真,结果表明:混合煤气柜可以根据煤气产耗特点调整存储量,并保证存储量在合理范围内;调节用户会起到一定的缓冲作用,可以根据某种副产煤气的产耗特点响应增加或减少该种煤气的消耗量;当某种副产煤气严重不足时,固定消耗用户会根据优先级响应停调,以满足生产需求。可见副产煤气的优化调度应用可以为中国钢铁行业的低碳发展和节能减排提供技术支撑。