DER-CAM用户手册：分布式能源资源采纳模型

DER-CA

综合能源规划

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"DER-CAM (Distributed Energy Resources Customer Adoption Model) 是一款由Lawrence Berkeley National Laboratory（LBNL）开发的能源管理工具，部分资金来源于美国能源部的电力输送和能源可靠性办公室以及加州能源委员会的公共利益能源研究计划。DER-CAM的主要目标是模拟和推动分布式能源资源在客户层面的采纳和应用。该模型的最新版本为DER-CAM Version 5.x (DER-CAM+)，其界面设计为Version 2.x。" DER-CAM作为一个综合能源规划工具，它涵盖了多个关键知识点： 1. **分布式能源资源(DERs)**: 这包括太阳能、风能、小型热电联产、储能系统等，这些资源可在用户侧或电网边缘生成和存储电力，有助于提高能源效率和可靠性。 2. **客户采纳模型**: DER-CAM考虑了消费者对分布式能源技术的接受度和采用行为，这涉及到经济效益、政策激励、环境影响等多个因素。 3. **优化算法**: 该模型采用了高级的优化算法（如可能由G. Cardoso等人开发），用于确定最优的能源配置，最大化经济效益，同时满足各种约束条件，如供需平衡、环保目标等。 4. **图形用户界面(GUI)**: 设计者T. Takahashi、R. Gaur和G. Cardoso等人为DER-CAM创建了友好的用户界面，使得非专业用户也能方便地操作和理解复杂的能源系统模型。 5. **科研合作与贡献**: 来自不同领域的专家参与了DER-CAM的开发，他们的工作涉及算法设计、界面优化、模型应用等多个方面，体现了跨学科合作在能源领域的重要性。 6. **资助背景**: DER-CAM的研发得到了政府机构的支持，如美国能源部的电力输送和能源可靠性办公室以及加州能源委员会的公共利益能源研究计划，这表明此类模型在政策制定和能源策略中扮演着重要角色。 7. **加州能源政策**: 由于加州的能源政策倾向于推动清洁能源和分布式能源的发展，DER-CAM这样的工具对于评估和实施这些政策具有实际意义。 8. **持续发展**: 从2008年至2018年的版权信息可以看出，DER-CAM是一个不断发展和更新的项目，反映了能源技术和市场环境的快速变化。 DER-CAM是一款强大的决策支持工具，它整合了分布式能源资源的经济性、环境影响和用户行为等多个维度，旨在促进清洁能源的广泛应用，同时为政策制定者和能源管理者提供科学的规划依据。通过不断的研究和改进，DER-CAM有望在未来继续发挥其在综合能源规划中的重要作用。

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4. Main screen overview

After creating a new project, you will be presented with the main screen. As shown in

Figure 6, this main panel is divided in three areas: Parameters Menu, Tables Input Area, and

Help Area. The Parameters Menu enables a hierarchical navigation through the parameters

required by DER-CAM. By selecting each category of inputs, the corresponding input table

will appear in the Table Area. Help information about the parameters will be presented in

the Help Area, on the right side of the panel. Finally, at the bottom of the screen, the

information regarding the DER-CAM version being used is displayed.

Figure 6: Input Main Screen

III. Overview of input parameters

In this section, we detail the type of inputs required by DER-CAM that should be specified

in the Parameters Menu. The Parameters Menu changes according to the type of microgrid

model selected by the user in the New Project menu, (single-node or multi-node.) For

each category of the Parameters menu explained bellow, we will indicate if it is associated

with the single-node and/or multi-node version of DER-CAM.

1. Global Settings

The Global Settings menu contains the general optimization parameters. It also includes the

main financial and technical parameters, as well as the high level options associated with

the technologies to be considered in the optimization. Three subsections are included

within Global Settings: Options Table; Parameter Table; Number of Days.

1.1. Investment Options (multi-node only)

The Investment Options Table is only available in multi-node version of DER-CAM. In this

table, the user can enable of disable the new investments in generation and storage

technologies per node of the microgrid, by setting 1 or 0, respectively, for each type of

investment.

1.2. Options Table

The Options Table is used to define key aspects in each model. It consists of a set of binary

parameters, where 0 disables and 1 enables the action controlled by that parameter. For

instance, setting “DiscreteInvest” to 1 will enable the possibility of investing in discrete

technologies, which consist of conventional distributed generation technologies modeled

internally using discrete variables. This includes reciprocating engines, microturbines, fuel-

cells, or gas turbines, as opposed to "continuous technologies", whose capacity is modeled

using continuous variables. This is an important distinction, as “Discrete technologies” can

only be installed in discrete quantities of the nameplate capacity. In contrast, the optimal

capacity of “Continuous technologies”, can be any continuous non-negative number. This

distinction is justified by the flexibility of commercially available system sizes.

Exporting generation can be enabled with the parameter “NonPVSales”, which allows for

the sale of generation from conventional DG technologies; and “PVSales”, which allows for

the sale of generation from PV. Revenue from export are determined using prices found in

the “PX Price” table under “Advanced User Settings.

The optimization objective function can also be selected in this menu. By default, DER-CAM

will minimize the economic function. Setting “MinimizeCO2” to 1 the objective will change

to CO

minimization. Setting “MultiObjective” to 1 will select a weighted objective of both

costs and CO

aspects will be considered.

1.3. Parameters Table

In the Parameter Table several project related global values can be set, including the key

financial parameters such as the project discount rate, the maximum payback period, and

the reference costs (base case cost) for investment scenarios. The reference costs represent

total annual energy costs prior to new investments in distributed generation technologies

and can be obtained by running DER-CAM only with the existing on-site technologies (if

any). It should be noted that even in the reference case DER-CAM will optimize the dispatch

of any existing DER, and, therefore, the reference case may already suggest relevant

improvements. The possibility of enabling existing technologies will be discussed in the

Technology section.

It is important to take into account that the “BaseCaseCost” is a key input of DER-CAM,

since it strongly relates to the maximum payback and, hence, it will affect the technology

portfolio that can be included in the optimal solution. The maximum payback constrain is

active in every investment run that is performed, and forces that any new investments

generate savings against the reference cost that respect a simple payback period shorter

than the maximum allowed payback time. In order to obtain a relevant estimation of

environmental performance, the CO

emissions of the base case should also be introduced

in this table.

Furthermore, it should be noted that the maximum payback constraint is still active when

minimization is selected. For this reason, it may be necessary to either increase the

maximum payback period or increase the reference costs when looking for environmental

friendly solutions. This is not absolutely necessary, but failing to do so may lead to

solutions that have limited potential to reduce emissions.

If “MultiObjective” is being selected as the objective of the optimization, the solution found

by DER-CAM will lay between the cost optimal and CO

optimal solutions, and the

preference over one objective or the other is determined by weighting factors

“MultiObjectiveWCosts” and “MultiObjectiveWCO2”. However, as both these objectives are

defined with different units, scaling factors must also be used.

To set the appropriate scaling factors, two separate optimization runs must be performed:

the scaling factor for costs, “MultiObjectiveMaxCosts”, is determined by performing a CO

minimization and saving the correspondent cost. Similarly, the weighting factor for CO

“MultiObjectiveMaxCO2”, can be found by performing a cost minimization run and saving

the corresponding CO

emissions. Although this is the recommended approach when using

weighted objectives, it should be noted that other procedures are possible and will

naturally impact the results. The weighted objective function used by DER-CAM is:

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DER-CAM用户手册：分布式能源资源采纳模型

DER源码+案例.rar

der文件查看工具

derc-resources:所有DERC资源，例如徽标，视频模板和指南

openssl密钥编码格式转换

unable to load PKCS7 object 140508944938816:error:0909006C:PEM routines:get_name:no start line:crypto/pem/pem_lib.c:745:Expecting: PKCS7

-----BEGIN RKRD.der----- MCAGCiqGSIb3DQEJGQMxEgQQFn6w5yeB5JQBEiM0RVZneA== -----END RKRD.der-----请使用openssl接口解码上述数据，并给出详细的代码解析出oid，nid和随机数167EB0E72781E4940112233445566778

openssl 命令行解析pkcs8 私钥

group_org = der_org_info.groupby( by='asset_mgt_scale_region').size().reset_index(inplace=False)

已知sm2公钥，如何生成pem文件

X_test = np.vander(x_test, n_order + 1, increasing=True) reg = BayesianRidge(tol=1e-6, fit_intercept=False, compute_score=True))这段代码什么意思

是以“-----BEGIN PRIVATE KEY-----”作为开头， “-----END PRIVATE KEY-----” 作为结尾的私钥，建议您通过 openssl 工具进行格式转换，命令如下：

如何生成sm2国密算法的cer格式公钥

openssl 解析私钥命令

openssl rsa pem

求解Van der Pol微分方程

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